Restaurant AI

AI-powered restaurant discovery and recommendation engine.

Features

• Restaurant discovery via Google Places and Yelp APIs
• Personalized recommendations based on taste profile
• Mood-based restaurant matching (Comfort, Healthy, Indulgent, Fast)
• Save favorite restaurants
• Like/dislike swipe interface
• Real-time business hours
• Menu data scraping and analysis

Setup

1. Install dependencies

npm install

2. Set up environment variables

cp .env.local.example .env.local
# Edit .env.local with your API keys

3. Set up Supabase database

1. Create a new Supabase project
2. Run the SQL migrations in supabase/sql/ in this order:
   • create_restaurants_table.sql
   • create_restaurant_interactions.sql
   • 20250927_safe_database_setup.sql (for venues and menu_items)

4. Run the development server

npm run dev

Database Tables

Table	Purpose
restaurants	Restaurant records from Google Places
venues	Alternative restaurant records (Yelp)
menu_items	Menu items per venue
saved_restaurants	User's saved/favorited restaurants
restaurant_interactions	User likes/dislikes/skips
restaurant_loyalty	Repeat visit tracking
likes	General likes for menu items

API Endpoints

• GET /api/nearby - Find restaurants near a location
• POST /api/recommend-restaurants - Get personalized recommendations
• POST /api/recommend-dishes - Get dish recommendations
• GET /api/real-time-hours - Get current business hours
• POST /api/taste - Update taste profile

Migration from Food-AI

This project was extracted from the food-ai monorepo to create a standalone restaurant discovery application.

License

Private - All rights reserved