NutriScan AI

NutriScan AI helps users understand packaged food using:

• Barcode scan
• Product name search
• Image upload (label or barcode)

Then it returns health score, disease risk hints, processing level, and better alternatives.

What You Get

• Fast product scan and lookup
• Health score and risk insights
• OCR-based image analysis
• AI ingredient explanation and chat
• Account login/signup
• Search history saved in SQLite

Tech Stack

• Frontend: Next.js, React, Tailwind CSS
• Backend: FastAPI, SQLite
• ML: scikit-learn, XGBoost, EasyOCR
• Data source: Open Food Facts

Project Structure

nutriscan-ai/
  backend/
  frontend/
  ml/
  requirements.txt
  start-dev.bat

Quick Start (Windows)

git clone https://github.com/Shikhar28-web/NutriScan.git
cd NutriScan\nutriscan-ai

python -m venv .venv
.\.venv\Scripts\Activate.ps1
pip install -r requirements.txt

cd frontend
npm install
cd ..

start-dev.bat

Run URLs

• Frontend: http://localhost:3000
• Backend API: http://127.0.0.1:8000
• Backend Docs: http://127.0.0.1:8000/docs

Environment (Optional)

Create .env in nutriscan-ai/:

JWT_SECRET_KEY=replace-with-a-long-random-string
NEXT_PUBLIC_BACKEND_URL=http://127.0.0.1:8000

Main API Routes

• POST /api/scan-product
• POST /api/analyze-food
• POST /api/analyze-image
• GET /api/recommendations
• POST /api/chat
• POST /api/auth/signup
• POST /api/auth/login
• POST /api/auth/logout
• GET /api/auth/me
• GET /api/auth/history
• POST /api/auth/history

License

See LICENSE.