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InternBot

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

🚀 Features

  • 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

🏗️ Architecture

The project consists of three main components:

Backend (FastAPI + Python)

  • 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

Frontend (React + TypeScript)

  • 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

Database (PostgreSQL + pgvector)

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

🛠️ Tech Stack

Backend

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

Frontend

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

🚀 Quick Start

Prerequisites

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

Development Setup

  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:

Local Development

Backend

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

Frontend

cd frontend
npm install
npm run dev

📁 Project Structure

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

🌐 Deployment

Platform Options

1. Vercel (Frontend) + Railway/Render (Backend)

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

2. Netlify (Frontend) + DigitalOcean (Backend)

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

3. Full Docker Deployment

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

Environment Variables

Backend

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

Frontend

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

🔧 Configuration

Data Sources

The system scrapes job offers from:

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

API Endpoints

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

🤝 Contributing

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

📄 License

This project is licensed under the MIT License.

🆘 Support

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

🔮 Future Enhancements

  • 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