🚀 Helpdesk Project

A modern, scalable, and AI-powered Helpdesk System designed for enterprises, startups, and support teams. This solution provides a seamless ticketing system, real-time communication, knowledge base, and AI-driven assistance to optimize customer support operations.

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🏗 Architecture Overview

The system follows a modular, service-oriented architecture with three primary components:

1. Backend (API Layer) – Built with Node.js & Express, powered by MongoDB for flexible and scalable data storage.

   • Handles authentication, ticket workflows, user management, and knowledge base APIs.
   • Implements role-based access control (RBAC) for secure multi-user environments.

2. Frontend (Client Layer) – A React + Vite web application delivering a clean, responsive, and interactive user interface.

   • Optimized for performance with modern bundling tools.
   • Provides intuitive dashboards for agents, admins, and end-users.

3. Agent Worker (AI Layer - Optional) – A Python FastAPI microservice for AI-driven automation.

   • Ticket classification using NLP.
   • Smart reply suggestions and response drafting.
   • Can be extended with OpenAI/GPT or custom ML models.

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⚡ Key Features

• 🔐 Authentication & Authorization

  • Secure JWT-based login and signup
  • Role-based access (Admin, Agent, Customer)

• 🎫 Ticket Management System

  • Create, assign, track, and close tickets
  • Priority & SLA management
  • Comment threads and attachments support

• 📚 Knowledge Base

  • Create and manage help articles
  • Searchable knowledge system for customers
  • Markdown editor for article creation

• 🤖 AI Capabilities (Optional)

  • Automated ticket categorization
  • Suggested responses for agents
  • Sentiment analysis on customer messages

• 🔔 Real-Time Notifications

  • WebSocket-based live updates
  • New ticket alerts, status changes, and agent mentions

• 📊 Admin Dashboard

  • Ticket volume analytics
  • Agent performance monitoring
  • SLA compliance reports

• ☁️ Cloud & Container Support

  • Docker-based deployment
  • Scalable with Kubernetes or Docker Swarm
  • CI/CD ready

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🛠 Development Setup

Prerequisites

• Node.js v18+
• Python 3.8+
• MongoDB (local or cloud e.g., MongoDB Atlas)
• Docker (optional for containerized deployment)

Setup Instructions

1. Backend Setup

cd backend
npm install
npm run dev

2. Frontend Setup

cd frontend
npm install
npm run dev

3. Agent Worker Setup (Optional)

cd agent-worker
pip install -r requirements.txt
python -m app.main

4. Docker Setup (Full System)

cd config
docker-compose up -d

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📂 Project Structure

helpdesk-project/
├── backend/           # Node.js Express API
│   ├── src/           # API source code
│   ├── tests/         # Unit & integration tests
│   └── docs/          # API Documentation
├── frontend/          # React Vite application
│   ├── src/           # React components & pages
│   └── public/        # Static assets
├── agent-worker/      # Python FastAPI AI service
├── config/            # Docker, env files, deployment configs
└── scripts/           # Database seeding & maintenance scripts

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📖 API Documentation

Detailed API docs available in: 👉 Backend README 👉 Swagger UI available at /api/docs when running the backend service.

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🚀 Future Enhancements

• AI-powered chatbots integrated with the knowledge base
• Multi-channel support (Email, WhatsApp, Slack, MS Teams)
• Customizable workflows for different industries
• Plugin architecture for third-party integrations (CRM, ERP, Slack, etc.)

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🤝 Contributing

We welcome contributions from the community!

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

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🎯 Why This Project?

• Built with modern technologies ensuring performance & scalability
• AI integration for smarter customer support
• Flexible deployment – works on local, cloud, or containerized environments
• Designed for real-world support teams handling large ticket volumes