AI-powered resume analysis and skill gap detection with a modern monorepo architecture.

This monorepo contains:

• Backend (apps/backend/): FastAPI Python server with AI-powered resume analysis
• Frontend (apps/frontend/): Next.js React application with TypeScript and Tailwind CSS

• Node.js 18+ and npm 8+
• Python 3.11+
• pip

1. Install root dependencies:

   npm install

2. Install all workspace dependencies:

   npm run install:all

3. Set up Python backend:

   cd apps/backend
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

Start both frontend and backend in development mode:

npm run dev

This will start:

• Backend API server on http://localhost:8001
• Frontend development server on http://localhost:3000

Start services individually:

# Backend only
npm run dev:backend

# Frontend only
npm run dev:frontend

Build and start for production:

npm run build
npm run start

resume-tweaker-monorepo/
├── apps/
│   ├── backend/           # FastAPI Python backend
│   │   ├── controllers/  # AI processing modules
│   │   ├── models/       # ML models and data
│   │   ├── templates/    # HTML templates
│   │   ├── main.py       # FastAPI application
│   │   └── requirements.txt
│   └── frontend/         # Next.js React frontend
│       ├── src/
│       ├── public/
│       └── package.json
├── packages/             # Shared packages (future)
├── package.json         # Root workspace configuration
└── README.md

• npm run dev - Start both frontend and backend in development
• npm run build - Build frontend for production
• npm run start - Start both services in production mode
• npm run install:all - Install dependencies for all workspaces
• npm run clean - Clean all node_modules and build artifacts
• npm run lint - Run ESLint on frontend code
• npm run type-check - Run TypeScript type checking

• PDF resume parsing and text extraction
• AI-powered PII (Personal Information) extraction
• Enhanced skill extraction with categorization
• Skill gap analysis
• Feedback collection and model retraining
• RESTful API with automatic documentation

• Modern React with TypeScript
• Responsive design with Tailwind CSS
• File upload interface
• Real-time analysis results
• Interactive feedback forms
• Progressive Web App capabilities

The frontend communicates with the backend API at http://localhost:8001. Key endpoints:

• POST /submit/ - Upload resume and job description for analysis
• POST /submit_pii_feedback - Submit PII extraction feedback
• POST /submit_skills_feedback - Submit skills extraction feedback
• GET /lexicon_stats - Get skill lexicon statistics
• GET /feedback_summary - Get feedback collection summary

• Located in apps/backend/
• Uses FastAPI with automatic API documentation
• AI models for PII and skill extraction
• Feedback collection system for continuous improvement

• Located in apps/frontend/
• Next.js 15 with App Router
• TypeScript for type safety
• Tailwind CSS for styling
• ESLint for code quality

• Python virtual environment with all dependencies
• FastAPI with Uvicorn ASGI server
• Environment variables for configuration

• Static export or server-side rendering
• Optimized production build
• CDN-ready assets

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test both frontend and backend
5. Submit a pull request

This project is licensed under the MIT License.