CVImprover API

A Django REST API backend for AI-powered CV optimization and improvement services. The platform allows users to submit questionnaires with their career information and receive AI-generated, optimized CVs tailored to specific job applications.

🚀 Features

• User Authentication & Authorization

  • JWT-based authentication
  • Google OAuth integration
  • User profiles with subscription management

• AI-Powered CV Generation

  • OpenAI GPT-4 integration for CV optimization
  • PDF resume upload and text extraction
  • Questionnaire-based job targeting
  • Markdown to PDF conversion for generated CVs

• Subscription Management

  • Stripe integration for payments
  • Multiple subscription plans (Free, Basic, Pro, Premium)
  • Webhook handling for subscription events
  • Billing portal integration

• Background Tasks

  • Celery for asynchronous task processing
  • Redis as message broker and cache
  • Scheduled tasks with Celery Beat

• API Documentation

  • OpenAPI 3.0 schema
  • Interactive Swagger UI
  • Comprehensive endpoint documentation

🏗️ Tech Stack

• Backend: Django 5.2.1 + Django REST Framework
• Database: PostgreSQL
• Cache/Queue: Redis
• Task Queue: Celery with Eventlet
• AI: OpenAI GPT-4
• Payments: Stripe
• PDF Processing: WeasyPrint, PyPDF2
• Containerization: Docker + Docker Compose
• Deployment: PM2, GitHub Actions

📋 Prerequisites

• Python 3.11+
• Docker & Docker Compose
• PostgreSQL (or use Docker)
• Redis (or use Docker)
• OpenAI API key
• Stripe account (for payments)

🛠️ Installation

Using Docker (Recommended)

1. Clone the repository

   git clone <repository-url>
   cd cvimprover-api

2. Create environment file

   cp .env.example .env

3. Configure environment variables

   # Django
   SECRET_KEY=your-secret-key
   DEBUG=True
   
   # Database
   DB_NAME=cvimprover
   DB_USER=postgres
   DB_PASSWORD=password
   DB_HOST=postgres_master
   DB_PORT=5432
   
   # Redis & Celery
   CELERY_BROKER_URL=redis://redis:6379/0
   CELERY_RESULT_BACKEND=redis://redis:6379/0
   CACHE_URL=redis://redis:6379/1
   
   # OpenAI
   OPENAI_API_KEY=your-openai-api-key
   
   # Stripe
   STRIPE_SECRET_KEY=your-stripe-secret-key
   STRIPE_PUBLISHABLE_KEY=your-stripe-publishable-key
   STRIPE_WEBHOOK_SECRET=your-webhook-secret
   
   # Google OAuth
   GOOGLE_CLIENT_ID=your-google-client-id
   GOOGLE_CLIENT_SECRET=your-google-client-secret
   
   # CORS
   CORS_ALLOWED_ORIGINS=http://localhost:3000
   FRONTEND_URL=localhost:3000
   BACKEND_URL=localhost:8000

4. Start the services

   docker-compose up -d

5. Run migrations and create superuser

   docker-compose exec web python manage.py migrate
   docker-compose exec web python manage.py createsuperuser
   docker-compose exec web python manage.py seed_plans

Local Development Setup

1. Create virtual environment

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

2. Install dependencies

   pip install -r requirements.txt

3. Set up database

   python manage.py migrate
   python manage.py seed_plans

4. Start Redis and Celery

   # Terminal 1: Redis
   redis-server
   
   # Terminal 2: Celery Worker
   celery -A cvimprover worker --loglevel=info
   
   # Terminal 3: Celery Beat
   celery -A cvimprover beat --loglevel=info

5. Start Django server

   python manage.py runserver

🚦 Usage

API Endpoints

The API provides the following main endpoints:

• Authentication: /auth/

  • User registration, login, logout
  • Google OAuth integration
  • JWT token management

• CV Management: /cv/

  • Questionnaire submission
  • AI response generation
  • PDF generation from AI responses

• Subscription Management: /core/

  • Plan listing
  • Checkout session creation
  • Billing portal access
  • Webhook handling

Example API Usage

1. Create a questionnaire

   curl -X POST http://localhost:8000/cv/questionnaire/ \
     -H "Authorization: Bearer <your-jwt-token>" \
     -H "Content-Type: application/json" \
     -d '{
       "position": "Software Engineer",
       "industry": "Technology",
       "experience_level": "3-5",
       "company_size": "medium",
       "application_timeline": "1-3 months",
       "job_description": "Looking for a full-stack developer..."
     }'

2. Generate AI response

   curl -X POST http://localhost:8000/cv/ai-responses/ \
     -H "Authorization: Bearer <your-jwt-token>" \
     -H "Content-Type: application/json" \
     -d '{
       "questionnaire": 1,
       "prompt": "Please optimize my CV for this software engineering position"
     }'

🧪 Testing

Run the test suite:

# Using Docker
docker-compose exec web python manage.py test

# Local development
python manage.py test

📚 API Documentation

Access the interactive API documentation at:

• Swagger UI: http://localhost:8000/
• OpenAPI Schema: http://localhost:8000/schema/

🔧 Configuration

Stripe Setup

1. Create a Stripe account and get your API keys
2. Set up webhook endpoint: your-domain/core/payments/webhook/stripe/
3. Configure subscription plans in Django admin or using the seeder

OpenAI Setup

1. Get your OpenAI API key from the OpenAI platform
2. Add it to your environment variables
3. The system uses GPT-4 for CV optimization

Google OAuth Setup

1. Create a Google Cloud project
2. Configure OAuth 2.0 credentials
3. Add authorized redirect URIs
4. Set the client ID and secret in environment variables

🚀 Deployment

Production Deployment with PM2

The project includes PM2 configuration for production deployment:

# Start all services
pm2 start ecosystem.prod.config.js

# Monitor services
pm2 monit

# View logs
pm2 logs

GitHub Actions

Automated deployment is configured via GitHub Actions:

• Tests run on pull requests
• Automatic deployment to production on main branch pushes

📁 Project Structure

cvimprover-api/
├── core/                   # Core app (users, plans, payments)
│   ├── models.py          # User and Plan models
│   ├── views.py           # Authentication and payment views
│   └── serializers.py     # API serializers
├── cv/                    # CV management app
│   ├── models.py          # Questionnaire and AI Response models
│   ├── views.py           # CV-related API endpoints
│   └── serializers.py     # CV serializers
├── cvimprover/            # Main project settings
│   ├── settings.py        # Django configuration
│   ├── urls.py           # URL routing
│   └── celery.py         # Celery configuration
├── docker-compose.yml     # Docker services configuration
├── Dockerfile            # Docker image definition
└── requirements.txt      # Python dependencies

🤝 Contributing

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

📝 License

This project is licensed under the GNU Affero General Public License v3.0 - see the LICENSE file for details.

🆘 Support

If you encounter any issues or have questions:

1. Check the API documentation
2. Review the logs: docker-compose logs web
3. Open an issue on GitHub

🔮 Roadmap

• Additional AI model integrations
• Cover letter generation
• LinkedIn profile optimization
• Interview preparation features
• Multi-language support
• Advanced analytics dashboard

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Built with ❤️ using Django and modern web technologies.