IngreScan-AI 🥗🔍

Smart Food Risk Analyzer - AI-powered food ingredient analysis platform supporting the Label Padhega India movement.

🌟 Overview

IngreScan-AI empowers Indian consumers to make informed, healthy food choices by analyzing packaged food ingredients using AI technology. The platform combines cutting-edge technology with trusted health data from WHO and FSSAI to provide personalized risk assessments and safer alternatives.

Supporting the Label Padhega India Movement 🇮🇳 - Promoting food literacy and consumer awareness across India.

✨ Features

🔬 Smart Ingredient Scanner

• Text Input: Manually enter ingredient lists
• Image Upload with OCR: Take photos of ingredient labels for automatic extraction
• AI-Powered Analysis: Comprehensive health risk assessment using LLM technology

📊 Risk Analysis Engine

• Personalized Health Scores: Based on user profile, medical conditions, and dietary preferences
• Scientific Backing: Data from WHO, FSSAI, and PubMed
• Detailed Insights: Short-term, long-term health impacts, and side effects
• Misleading Claims Detection: Identifies hidden sugars, salts, oils, and harmful additives

👤 Personal Health Profile

• Track medical conditions and medications
• BMI calculation and exercise frequency
• Diet type preferences (veg, non-veg, vegan, keto, etc.)
• Personalized risk assessments

💬 AI Chatbot

• Food-focused conversational AI
• Context-aware responses based on scan results
• Ingredient explanations and health impact Q&A
• Safer alternative suggestions

📈 Visual Analytics

• Interactive charts (bar, pie, radar)
• Ingredient breakdown visualization
• Risk level indicators
• Historical trend tracking

📝 Scan History & Reports

• Access all previous scans
• Saved analysis reports
• Track food choices over time

🚀 Tech Stack

Frontend

• React 19 - Modern UI library
• TypeScript - Type-safe development
• Tailwind CSS 4 - Utility-first styling
• Wouter - Lightweight routing
• tRPC - End-to-end type-safe APIs
• shadcn/ui - Beautiful component library

Backend

• Node.js - Runtime environment
• Express 4 - Web framework
• tRPC 11 - Type-safe API layer
• Drizzle ORM - Database toolkit
• MySQL/TiDB - Database

AI & Services

• LLM Integration - AI-powered analysis and chatbot
• OCR - Image text extraction
• S3 Storage - File storage

📦 Installation

Prerequisites

• Node.js 22.x or higher
• pnpm package manager
• MySQL/TiDB database

Setup

1. Clone the repository

git clone https://github.com/shivrajpatare/IngreScan-AI.git
cd IngreScan-AI

2. Install dependencies

pnpm install

3. Set up environment variables

cp .env.example .env
# Edit .env with your configuration

4. Run database migrations

pnpm db:push

5. Start development server

pnpm dev

The application will be available at http://localhost:3000

🗂️ Project Structure

├── client/                 # Frontend React application
│   ├── src/
│   │   ├── pages/         # Page components
│   │   ├── components/    # Reusable UI components
│   │   ├── lib/           # Utilities and tRPC client
│   │   └── index.css      # Global styles
│   └── public/            # Static assets
├── server/                # Backend Express + tRPC
│   ├── routers.ts         # API endpoints
│   ├── db.ts              # Database queries
│   └── _core/             # Core server functionality
├── drizzle/               # Database schema and migrations
│   └── schema.ts          # Database models
└── shared/                # Shared types and constants

🎯 Key Features Implementation

Ingredient Analysis

The platform uses AI to analyze ingredients against:

• WHO food safety guidelines
• FSSAI regulations
• Scientific research from PubMed
• User's personal health profile

Label Padhega India Support

• Educational content about hidden ingredients
• Misleading marketing claims detection
• Special focus on children's products
• Consumer awareness messaging

Personalization

• Risk scores adjusted for individual health conditions
• Dietary preference considerations
• Medication interaction warnings
• Age and BMI-based recommendations

🔒 Privacy & Security

• Secure authentication with Manus OAuth
• HTTPS encryption for all data transmission
• User data stored securely in database
• No sharing of personal health information
• GDPR-style user rights and data control

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

📧 Contact

Project Maintainer: Shivraj Patare

• GitHub: @shivrajpatare

🙏 Acknowledgments

• Label Padhega India Movement - Inspiring consumer awareness
• Revant Himatsingka (@foodpharmer) - Food literacy advocacy
• WHO & FSSAI - Trusted health data sources
• Open Source Community - Amazing tools and libraries

🌐 Links

• Live Demo: https://foodriskanaly-yjkguatc.manus.space/
• Documentation: [Coming Soon]
• Label Padhega India: Learn more about the movement

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Made with ❤️ for a healthier India 🇮🇳

"Know What You Eat - Make Informed Choices"