NutriGenie 🥗

An AI-powered meal planning application that generates personalized, budget-conscious meal plans with accurate grocery pricing and store integration.

🎯 Overview

NutriGenie combines the power of AI with real-world grocery data to create practical meal plans that fit your budget and nutritional needs. Using GPT-4 with RAG (Retrieval Augmented Generation), it generates intelligent meal suggestions based on ingredients actually available at your local stores.

✨ Key Features

• 🤖 AI-Powered Meal Planning: Uses GPT-4 with semantic ingredient matching
• 💰 Budget-Conscious: Stays within your specified budget using real grocery pricing
• 🏪 Multi-Store Support: Kroger, Safeway, Walmart, Whole Foods, and more
• 🔍 Smart Ingredient Matching: Vector similarity search for ingredient alternatives
• 📱 Modern UI: Clean, responsive React/Next.js interface
• 📊 Nutritional Tracking: Detailed macro and calorie breakdowns
• 🛒 Smart Shopping Lists: Auto-generated lists with store-specific pricing
• 📄 PDF Export: Export meal plans and grocery lists

🍽️ Detailed Functionality

🎯 User Onboarding & Profile Management

• Comprehensive Onboarding: Collects age, weight, height, activity level, and fitness goals
• Automatic Macro Calculation: Uses Mifflin-St Jeor equation to calculate TDEE and optimal macronutrient distribution
• Dietary Preferences: Supports vegetarian, vegan, gluten-free, keto, paleo, and custom restrictions
• Location-Based Setup: ZIP code integration for nearby store discovery
• Profile Persistence: Secure user data storage with Supabase authentication

🤖 AI-Powered Meal Generation

• GPT-4 Integration: Advanced language model creates realistic, varied meal plans
• RAG Enhancement: Retrieval Augmented Generation ensures ingredient availability and pricing accuracy
• Function Calling: Structured JSON schema ensures consistent meal plan format
• Budget Optimization: AI considers ingredient costs to stay within weekly budget constraints
• Nutritional Balance: Ensures daily calorie and macro targets are met across all meals
• Recipe Variety: Generates diverse recipes to prevent meal plan monotony

🏪 Store Integration & Pricing

• Multi-Store Support: Integrates with major grocery chains:
  • Kroger: Full API integration with real-time pricing
  • Safeway: Web scraping with intelligent fallback pricing
  • Walmart: Product availability and price matching
  • Whole Foods, Target, ALDI: Research-based price multipliers
• Geographic Discovery: Finds nearby stores using ZIP code lookup
• Price Validation: Filters out unrealistic prices (e.g., uniform $5.00 errors)
• Store-Specific Adjustments: Applies realistic price multipliers for unsupported stores
• Automated Price Refresh: Daily GitHub Actions workflows update pricing data

🔍 Smart Ingredient System

• Vector Embeddings: OpenAI text-embedding-3-small for semantic ingredient matching
• Similarity Search: pgvector database for finding ingredient alternatives
• Unit Conversion Intelligence:
  • Weight ↔ Volume conversions (g↔ml, lb↔oz)
  • Liquid density calculations for accurate milk/juice pricing
  • Package size assumptions (realistic portions vs. bulk quantities)
• Ingredient Availability: Cross-references meal plan ingredients with store inventory
• Substitution Suggestions: Recommends alternatives when ingredients are unavailable

📊 Nutritional Analysis

• Detailed Macro Tracking: Protein, carbohydrates, fat, and calorie counts per meal and day
• Nutritional Goals: Customizable targets based on fitness objectives (weight loss, muscle gain, maintenance)
• Serving Size Accuracy: Precise portion calculations for accurate nutritional data
• Dietary Compliance: Ensures generated meals adhere to specified dietary restrictions
• Visual Nutrition Display: Clean charts and progress indicators for macro tracking

🛒 Intelligent Shopping Lists

• Auto-Generated Lists: Consolidates ingredients across all meals into organized shopping lists
• Store-Specific Pricing: Shows current prices from selected grocery stores
• Quantity Optimization: Calculates exact amounts needed to minimize waste
• Category Organization: Groups ingredients by store sections (produce, dairy, meat, etc.)
• Cost Breakdown: Displays individual item costs and total estimated spending
• Multi-Store Support: Generates separate lists if shopping at multiple stores

📱 User Experience Features

• Responsive Design: Works seamlessly on desktop, tablet, and mobile devices
• Loading States: Skeleton loaders and progress indicators during meal generation
• Error Handling: Graceful error recovery with helpful user feedback
• Real-Time Updates: Live status updates during meal plan generation
• Accessible UI: WCAG compliant design with keyboard navigation support
• Dark/Light Mode: Theme options for user preference

📄 Export & Sharing

• PDF Generation: Professional meal plan and grocery list exports
• Print Optimization: Clean, printer-friendly layouts
• Email Integration: Share meal plans via email
• Recipe Details: Complete cooking instructions, prep times, and serving information
• Nutritional Summaries: Exportable nutrition data for tracking apps

🔒 Security & Privacy

• Supabase Authentication: Secure user registration and login
• Row-Level Security: Database-level access controls
• API Key Management: Secure storage of third-party API credentials
• Data Encryption: All sensitive data encrypted at rest and in transit
• Privacy Compliance: GDPR-compliant data handling practices

⚡ Performance Optimizations

• Caching Strategy: Intelligent caching of pricing data and store information
• Batch Processing: Efficient ingredient embedding and price lookups
• Database Optimization: Indexed queries for fast meal plan retrieval
• CDN Integration: Fast asset delivery for global users
• Background Jobs: Non-blocking price updates and data processing

🔧 Developer Experience

• Comprehensive API: RESTful endpoints for all application functionality
• Type Safety: Full TypeScript implementation across frontend and backend
• Error Logging: Detailed logging for debugging and monitoring
• Testing Suite: Unit and integration tests for critical functionality
• Development Tools: Hot reloading, debugging, and development server setup

🛠️ Tech Stack

Backend

• FastAPI - Modern Python web framework
• Supabase - PostgreSQL with pgvector for embeddings
• OpenAI GPT-4 - Meal plan generation and RAG
• Python 3.9+ - Core backend language

Frontend

• Next.js 14 - React framework with App Router
• TypeScript - Type-safe development
• Tailwind CSS - Utility-first styling
• Shadcn/UI - Modern component library

Key Services

• Price Scraping: Real-time pricing from Kroger, Walmart, Safeway
• RAG System: Semantic ingredient matching with OpenAI embeddings
• Unit Conversion: Smart quantity conversions (g↔ml, lb↔oz, etc.)
• Store Integration: Multi-store price comparison and availability

🚀 Quick Start

Prerequisites

• Node.js 18+
• Python 3.9+
• Supabase account
• OpenAI API key

Backend Setup

1. Clone and setup:

git clone <repository-url>
cd NutriGenie/backend
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

2. Environment variables: Create .env file:

OPENAI_API_KEY=your_openai_api_key
SUPABASE_URL=your_supabase_url
SUPABASE_ANON_KEY=your_supabase_anon_key
SUPABASE_SERVICE_ROLE_KEY=your_supabase_service_role_key
KROGER_CLIENT_ID=your_kroger_client_id
KROGER_CLIENT_SECRET=your_kroger_client_secret

3. Start backend:

uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

Frontend Setup

1. Setup and start:

cd ../frontend
npm install

2. Environment variables: Create .env.local:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key  
NEXT_PUBLIC_API_URL=http://localhost:8000

3. Start frontend:

npm run dev

🏗️ Architecture

Database Schema

• Users: Authentication and preferences
• Meal Plans: Generated plans with dates and costs
• Recipes: Individual recipes with nutrition data
• Ingredients: Master list with vector embeddings
• Stores: Grocery store locations and details
• Pricing: Real-time prices by store and ingredient

Core Components

RAG Meal Planning (app/services/rag_meal_plan.py):

• Semantic ingredient matching using vector similarity
• Context-aware GPT prompts with available ingredients
• Budget-conscious recipe generation with real pricing

Pricing System (app/services/pricing.py):

• Multi-store price aggregation and validation
• Store-specific multipliers for unsupported locations
• Price outlier detection and fallback logic

Unit Conversion (app/services/unit_conversion.py):

• Smart quantity conversions between units
• Liquid density calculations for accurate pricing
• Package size assumptions for realistic quantities

📝 Usage

1. Account Setup: Create account and complete onboarding
2. Set Preferences: Budget, nutrition goals, dietary restrictions, stores
3. Generate Plan: AI creates personalized 7-day meal plan
4. Review & Export: View recipes, ingredients, costs, and export to PDF
5. Shop Smart: Use generated grocery list with store-specific pricing

🔧 Development

Price Refresh System

Automated daily price updates via GitHub Actions:

PYTHONPATH=backend python backend/scripts/refresh_prices.py

Required secrets:

• SUPABASE_URL / SUPABASE_SERVICE_KEY
• KROGER_CLIENT_ID / KROGER_CLIENT_SECRET

Database Migrations

Add SQL migrations to backend/migrations/ and apply via Supabase dashboard.

Testing

cd backend && pytest

API Endpoints

Authentication

• POST /auth/signup - User registration
• POST /auth/signin - User login
• GET /auth/verify - Email verification

User Management

• GET /profiles - Get user profile
• PUT /profiles - Update user profile
• POST /profiles/macros - Calculate and update macros

Meal Planning

• POST /meal-plans/generate - Generate new meal plan
• GET /meal-plans - List user's meal plans
• GET /meal-plans/{id} - Get specific meal plan
• DELETE /meal-plans/{id} - Delete meal plan

Store & Pricing

• GET /stores/nearby - Find nearby grocery stores
• GET /stores/{id}/prices - Get store-specific pricing
• POST /stores/refresh-prices - Trigger price refresh

Ingredients & RAG

• GET /ingredients/search - Search ingredients with embeddings
• POST /ingredients/embed - Generate ingredient embeddings
• GET /ingredients/suggestions - Get ingredient alternatives