A modern backend project built with Django REST Framework, featuring JWT authentication, AI-powered task suggestions via OpenAI, and complete API documentation.

Technology	Badge
Python
Django
DRF
OpenAI
License

• 📝 Full CRUD operations on tasks
• 🔐 JWT Authentication (Simple JWT)
• 🤖 AI task suggestion endpoint using OpenAI GPT-3.5
• 📄 API documentation with Swagger & ReDoc
• 🛠 Admin panel for managing users and tasks
• 🆕 Signup / Login / Logout pages for user management
• 🔧 Recent modifications:
  • Added AI task suggestion improvements
  • Refactored views.py for clarity and stability
  • Added proper signup/login integration
  • Updated API endpoints table for clarity
  • LATEST: Complete code refactoring with improved quality
    • Fixed duplicate model fields (user/owner)
    • Updated to modern OpenAI ChatCompletion API
    • Added comprehensive error handling and logging
    • Improved authentication and permissions
    • Enhanced test coverage (7 tests)
    • Applied Black code formatting
    • Added environment validation command
    • Ready for production deployment 🚀
      • Deployment guides for Heroku, Railway, Docker, AWS, VPS
      • Production-ready Dockerfile and docker-compose.yml
      • Heroku Procfile and runtime.txt
      • Nginx configuration for reverse proxy

# Clone repository
git clone <your-repo-url>
cd task-manager

# Create virtual environment
python -m venv venv
source venv/bin/activate   # Linux / Mac
venv\Scripts\activate      # Windows

# Install dependencies
pip install -r requirements.txt

# Copy environment template and configure
cp .env.development .env
# Edit .env and add your settings (especially OPENAI_API_KEY if you want AI features)

# Check environment configuration (optional but recommended)
python manage.py check_env

# Run migrations
python manage.py makemigrations
python manage.py migrate

# Create a superuser (for admin access)
python manage.py createsuperuser

# Start the server
python manage.py runserver

curl -X POST http://127.0.0.1:8000/api/suggest-task/ \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <your-jwt-token>" \
-d '{"prompt":"study Django"}'

Response Example:

{
  "suggestion": "Review Django models and build a small CRUD project."
}

Backend: Django 5.2, Django REST Framework

Authentication: JWT (Simple JWT)

AI: OpenAI GPT-3.5

Docs: drf-yasg (Swagger & ReDoc)

Database: SQLite (default, can switch to PostgreSQL)

Code Quality: Black, isort

• Make sure OPENAI_API_KEY is set in .env to use the AI endpoint
• Use python manage.py check_env to validate your environment configuration
• All links above are local URLs, accessible when the server runs
• The AI suggestion endpoint requires authentication (JWT token)

This application is production-ready and can be deployed to various platforms:

• Heroku: git push heroku main (see DEPLOYMENT.md)
• Railway: One-click deploy from GitHub
• Docker: docker-compose up -d
• Digital Ocean: App Platform auto-deploy
• AWS: Elastic Beanstalk or ECS
• VPS: Traditional server deployment with Nginx

📖 Full deployment guide: See DEPLOYMENT.md for detailed instructions for each platform.

• ✅ Procfile - Heroku/Railway deployment
• ✅ runtime.txt - Python version specification
• ✅ Dockerfile - Production-ready container image
• ✅ docker-compose.yml - Multi-container orchestration
• ✅ nginx.conf - Reverse proxy configuration
• ✅ .dockerignore - Optimized Docker builds

python manage.py check --deploy  # Check deployment readiness
python manage.py test            # Run all tests
python manage.py collectstatic   # Collect static files

This project is actively maintained, with recent comprehensive refactoring to improve code quality, security, and maintainability.

This project is licensed under the MIT License.