NutriAI

Overview

NutriAI is a sophisticated nutrition analysis platform designed to provide real-time insights into food product ingredients. Utilizing high-performance Google Gemini Large Language Models (LLMs) and computer vision, the system analyzes ingredient lists and nutritional labels to deliver a comprehensive health assessment, categorized highlights, and an interactive nutritionist chat interface.

Technical Architecture

Frontend

• Framework: React 19 (Vite-powered Single Page Application)
• Styling: Tailwind CSS
• State Management: React Context API (NutriContext)
• Image Handling: Custom cropping and webcam integration via react-image-crop and react-webcam.

Backend

• Server: Python Flask
• AI Engine: Google Gemini 1.5 Series
  • Integrated multimodal analysis using Gemini 1.5 (Pro/Flash) for unified image recognition, nutritional reasoning, and conversational interaction.
• Architecture: Blueprint-based modular structure with service-oriented logic.

API Documentation

Production Base URL: <YOUR_BACKEND_URL>

Local Development: http://localhost:10000

Endpoint	Method	Description
/health	GET	Service status and health monitoring.
/samples	GET	Fetches a list of standardized product samples for testing.
/analyze	POST	Primary analysis engine. Accepts Base64 image data or raw ingredient text.
/chat	POST	Stateful conversational interface for nutritional follow-ups.

Installation & Setup

Prerequisites

• Node.js (v18+)
• Python (v3.10+)
• Google Gemini API Key

Repository Initialization

git clone https://github.com/Sayan-CtrlZ/NutriAI.git
cd nutriAI

Backend Configuration

1. Navigate to the server directory:

   cd server

2. Create and activate a virtual environment:

   python -m venv venv
   source venv/Scripts/activate  # Windows

3. Install dependencies:

   pip install -r requirements.txt

4. Configure environment variables in .env:

   GEMINI_API_KEY=your_gemini_api_key_here
   ALLOWED_ORIGINS=<YOUR_FRONTEND_URL>,http://localhost:5173
   PORT=10000

5. Execute the server:

   python run.py

Frontend Configuration

1. Navigate to the client directory:

   cd ../client

2. Install dependencies:

   npm install

3. Configure environment variables in .env:

   VITE_API_URL=<YOUR_BACKEND_URL>

4. Start the development environment:

   npm run dev

• Dynamic Scoring: A 0-100 proprietary health score based on ingredient quality.

Production Deployment

Backend Deployment

1. Set the following environment variables on your hosting provider:
   • GEMINI_API_KEY: Your Google Gemini API Key.
   • ALLOWED_ORIGINS: Comma-separated list of your frontend URLs (e.g., https://your-frontend-app.com).
   • PORT: Usually 10000 or as required by your provider.
2. Set the Health Check Path to /health.

Frontend Deployment

1. Set the following environment variable on your hosting provider:
   • VITE_API_URL: The URL of your deployed backend (e.g., <YOUR_BACKEND_URL>).
2. Build the project:

   npm run build

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