# itsm
**Repository Path**: wq2811/itsm
## Basic Information
- **Project Name**: itsm
- **Description**: No description available
- **Primary Language**: Go
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2026-02-27
- **Last Updated**: 2026-02-27
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
# ITSM - Enterprise IT Service Management Platform
A modern, full-featured IT Service Management (ITSM) platform built with Go/Gin backend and Next.js/React frontend. Supports ITIL best practices with AI-powered features.
## Features
### Core ITSM Modules
- **Ticket Management** - Full ticket lifecycle, SLA support, automated workflows
- **Incident Management** - Real-time monitoring, intelligent triage, escalation
- **Problem Management** - Root cause analysis, known error database
- **Change Management** - Risk assessment, multi-level approvals
- **Service Catalog** - Self-service portal, service requests
### AI-Powered Features
- **Smart Triage** - LLM-powered ticket classification and priority suggestion
- **RAG Knowledge Base** - Retrieval Augmented Generation for intelligent Q&A
- **Auto-Summarization** - AI-generated ticket summaries and action items
### Workflow Engine
- **BPMN 2.0** - Full BPMN workflow engine with visual designer
- **Custom Processes** - Build custom approval and escalation workflows
- **Automation Rules** - Event-driven automation
### SLA & Monitoring
- **SLA Management** - Define and monitor service level agreements
- **Real-time Alerts** - Proactive SLA breach notifications
- **Performance Analytics** - Dashboards and reports
## Tech Stack
| Layer | Technology |
|-------|------------|
| Backend | Go 1.24, Gin, Ent ORM |
| Frontend | Next.js 15, React 19, TypeScript 5 |
| UI Library | Ant Design 5, Tailwind CSS 4 |
| Database | PostgreSQL |
| BPMN Engine | nitram509/lib-bpmn-engine |
| AI/ML | OpenAI API, pgvector (optional) |
| State Management | Zustand, TanStack Query |
## Quick Start
### Prerequisites
- Go 1.24+
- Node.js 18+
- PostgreSQL 14+
### Backend Setup
```bash
cd itsm-backend
# Install dependencies
go mod download
# Configure database (edit config.yaml)
vim config.yaml
# Run database migrations
go run -tags migrate main.go
# Start the server
go run main.go
```
The backend will start at `http://localhost:8080`
### Frontend Setup
```bash
cd itsm-frontend
# Install dependencies
npm install
# Configure environment
cp .env.example .env.local
# Edit .env.local with your API URL
# Start development server
npm run dev
```
The frontend will start at `http://localhost:3000`
### Docker Deployment
```bash
# Using docker-compose
docker-compose up -d
```
## Project Structure
```
itsm/
├── itsm-backend/ # Go/Gin backend
│ ├── controller/ # HTTP handlers
│ ├── service/ # Business logic
│ ├── ent/ # Database models (Ent ORM)
│ ├── middleware/ # Auth, RBAC, tenant isolation
│ ├── internal/domain/ # DDD domain layer
│ └── config.yaml # Configuration
│
├── itsm-frontend/ # Next.js frontend
│ ├── src/app/ # App Router pages
│ ├── src/components/ # React components
│ ├── src/app/lib/ # API clients, stores
│ └── .env.example # Environment template
│
├── nginx/ # Nginx configuration
├── scripts/ # Utility scripts
└── docker-compose.yml # Docker deployment
```
## API Documentation
API documentation available at `http://localhost:8080/swagger/index.html` after starting the backend.
## Environment Variables
### Backend (`itsm-backend/config.yaml`)
```yaml
database:
host: localhost
port: 5432
user: dev
password: "your-password"
dbname: itsm
llm:
provider: openai # openai, azure, local
model: gpt-4o-mini
api_key: "" # Set via environment
vector:
enabled: false # Set to true when pgvector is installed
dimension: 1536
```
### Frontend (`itsm-frontend/.env.local`)
```env
NEXT_PUBLIC_API_URL=http://localhost:8080
NEXT_PUBLIC_API_TIMEOUT=30000
```
## Key Features Deep Dive
### AI Triage Service
The intelligent triage system classifies incoming tickets using LLM:
- Automatic category detection (database, network, server, etc.)
- Priority suggestion based on urgency
- Assignee recommendation
- Falls back to keyword matching when LLM unavailable
### RAG Knowledge Base
Hybrid search combining vector similarity and keyword search:
- Semantic search using OpenAI embeddings
- Keyword fallback for exact matches
- Automatic knowledge article indexing
### BPMN Workflow Engine
Custom BPMN 2.0 workflow engine with:
- Visual process designer (bpmn-js)
- Version-controlled process definitions
- User task assignment and delegation
- Process monitoring and analytics
## Contributing
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Support
- Create an issue for bug reports
- Discussions for questions and ideas
- Wiki for documentation