An AI-powered assistant for recommending internships and job opportunities for students, designed to help users find the perfect internship or job placement.

• AI Chat Interface: Modern, responsive chat interface with real-time communication
• Job Scraping: Automated scraping of job offers from multiple sources (PWR, Nokia, SII)
• Location Services: GPS integration for location-aware responses
• Student-Focused: Specialized recommendations for student internships
• Real-time Updates: Live data scraping and vector search
• Modern UI/UX: Clean, aesthetic design with smooth animations

The project consists of three main components:

• API Server: FastAPI-based REST API
• AI Agent: LangChain-powered conversational AI
• Data Scraping: Automated job offer collection from multiple sources
• Vector Database: PostgreSQL with pgvector for semantic search
• Data Management: Efficient storage and retrieval of job offers

• Modern UI: React 18 with TypeScript and Tailwind CSS
• Responsive Design: Mobile-first approach with smooth animations
• Real-time Chat: WebSocket-like experience with streaming responses
• Audio Integration: Text-to-speech and voice input capabilities
• Toast Notifications: User-friendly feedback system

• Vector Storage: Semantic search capabilities
• Job Offers: Structured storage of scraped opportunities
• Metadata: Rich information about each job posting

• FastAPI: Modern Python web framework
• LangChain: AI agent framework
• PostgreSQL: Primary database
• pgvector: Vector similarity search
• Docker: Containerization

• React 18: UI framework
• TypeScript: Type safety
• Vite: Build tooling
• Tailwind CSS: Styling
• Axios: HTTP client
• Lucide React: Icons

• Docker and Docker Compose
• Node.js 18+ (for local development)
• Python 3.9+ (for local development)

1. Clone the repository:

   git clone <repository-url>
   cd InternBot

2. Start with Docker Compose:

   # Production setup
   docker-compose up --build
   
   # Development setup with hot reload
   docker-compose -f docker-compose.dev.yml up --build

3. Access the application:

   • Frontend: http://localhost:3000
   • Backend API: http://localhost:8000
   • Database: localhost:5432

cd backend
pip install -e .
uvicorn intern_bot.api.api:app --reload --host 0.0.0.0 --port 8000

cd frontend
npm install
npm run dev

InternBot/
├── backend/                 # FastAPI backend
│   ├── src/intern_bot/
│   │   ├── agent/          # AI agent implementation
│   │   ├── api/            # API routes and models
│   │   ├── data_scraper/   # Web scraping modules
│   │   ├── data_manager/   # Database operations
│   │   └── settings/       # Configuration
│   ├── Dockerfile
│   └── pyproject.toml
├── frontend/                # React frontend
│   ├── src/
│   │   ├── components/     # Reusable UI components
│   │   ├── views/          # Page components
│   │   ├── services/       # API services
│   │   └── lib/            # Utilities
│   ├── Dockerfile
│   └── package.json
├── postgres/               # Database schema
├── docker-compose.yml      # Production setup
├── docker-compose.dev.yml  # Development setup
└── README.md

• Frontend: Deploy to Vercel with automatic builds
• Backend: Deploy to Railway or Render
• Database: Use managed PostgreSQL with pgvector

• Frontend: Deploy to Netlify
• Backend: Deploy to DigitalOcean App Platform
• Database: Managed PostgreSQL droplet

• VPS: Deploy entire stack on a VPS
• Cloud: Use cloud providers (AWS, GCP, Azure)
• Orchestration: Docker Swarm or Kubernetes

DB_HOST=your-db-host
DB_PORT=5432
DB_USER=postgres
DB_PASSWORD=your-password
DB_NAME=internbot

VITE_BACKEND_URL=https://your-backend-url.com
VITE_NODE_ENV=production

The system scrapes job offers from:

• PWR (Politechnika Wrocławska): Academic job board
• Nokia: Corporate career portal
• SII: IT consulting company

• POST /agent/invoke - Chat with AI agent
• POST /agent/stream - Stream chat responses
• POST /scrape/data - Trigger data scraping

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

This project is licensed under the MIT License.

For support and questions:

• Create an issue in the repository
• Check the documentation in each component's README
• Review the API documentation at /docs when running the backend

• Real-time notifications
• Advanced filtering and search
• User authentication and profiles
• Mobile app (React Native)
• Multi-language support
• Advanced analytics dashboard
• Integration with more job boards
• Machine learning for job matching