Trainix is a modern full-stack web application for personal fitness, progress analysis, and nutrition planning.
It uses AI to analyze photos, generates individual workout and nutrition plans, stores measurements, sends notifications, and allows you to track your progress.

⚡️ Free Render server — cold start up to 3 minutes
👉 View Demo

• Frontend: Next.js, React, Tailwind CSS, Redux Toolkit, TanStack Query
• Backend: Express.js, MongoDB, JWT Auth, AWS S3, OpenAI API
• Testing: Jest, Playwright, Supertest
• DevOps: Docker, Render

• AI photo progress analysis
• Fitness and nutrition plan generation
• Body measurements and progress history
• Notifications and advice
• User authentication (JWT)
• Photo storage on AWS S3 with CDN CloudFront
• OpenAI integration with python api using

• POST /api/auth/login — Login
• POST /api/auth/register — Register
• GET /api/fitness-plan — Get fitness plan
• POST /api/fitness-plan — Generate fitness plan
• GET /api/nutrition-plan — Get nutrition plan
• POST /api/measurements — Add measurements
• GET /api/notifications — Get notifications

• Unit & Integration: Jest
• E2E: Playwright
• Backend API: Supertest

Run tests:

# Frontend
npm run test --- not still working   # Jest
npx playwright test    # Playwright

# Backend
npm run test           # Jest & Supertest

git clone https://github.com/gaykun1/Trainix.git
cd Trainix
cd frontend && npm install
cd ../backend && npm install

• Copy .env.example to .env in both frontend/ and backend/
• Fill in your MongoDB URI, AWS keys, OpenAI API, JWT secret

Frontend:

cd frontend
npm run dev

Open http://localhost:3000

Backend:

cd backend
npm run dev

cd backend
docker build -t trainix-backend .
docker run -p 5200:5200 trainix-backend

This project is licensed under the GNU GPL v3.

Made with ❤️ by gaykun1