Binge — Food Discovery App

An interactive food discovery platform where users swipe through restaurant and recipe suggestions that adapt to their personal tastes.

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Repository Structure

Binge-SWE/
└── my-app/      # Next.js 14 (App Router, TypeScript, Tailwind, Supabase)

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Core Idea

Most food discovery platforms rely on manual searching. Binge introduces a discovery-first approach: users swipe through curated food cards and the system learns from their reactions.

The platform adapts to:

• Likes / skips / super-likes
• Dietary restrictions and allergies
• Cuisine preferences
• Past activity

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Key Features (Planned)

Feature	Status
Swipe-based food discovery	In progress
Personalized onboarding	Planned
Restaurant recommendations	Planned
Recipe discovery	Planned
Favorites system	Planned
AI food assistant	Planned

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Architecture

┌──────────────────────────────────────────┐
│   Next.js (my-app/)                      │
│                                          │
│  Pages / Components (React)              │
│  ↕                                       │
│  /app/api/* (Next.js Route Handlers)     │
│  ↕                                       │
│  Supabase JS client (server-side)        │
└──────────────────┬───────────────────────┘
                   │
      ┌────────────▼────────────┐
      │  Supabase (PostgreSQL)  │
      │                         │
      │  profiles               │
      │  user_preferences       │
      │  foods                  │
      │  swipes                 │
      │  favorites              │
      │  RLS enabled            │
      └─────────────────────────┘

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API Routes

Method	Route	Description
GET	/api/users/me	Get current user profile
PUT	/api/users/me	Update profile
GET	/api/users/me/preferences	Get dietary/cuisine preferences
PUT	/api/users/me/preferences	Save preferences
POST	/api/swipes	Record a swipe
GET	/api/swipes	Swipe history (paginated)
GET	/api/favorites	List favorites
POST	/api/favorites	Add a favorite
DELETE	/api/favorites/:foodId	Remove a favorite
GET	/api/recommendations	Get personalized food recommendations

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Quick Start

1. Clone

git clone https://github.com/GGlencoe/Binge-SWE
cd Binge-SWE/my-app

2. Set up Supabase

1. Create a free project at supabase.com
2. Open SQL Editor in your Supabase dashboard
3. Run each file in my-app/db/ in order (001 → 005)
4. Optionally run db/seed.sql for sample data

3. Configure environment

cp .env.local.example .env.local
# Fill in your Supabase credentials (see .env.local.example for field descriptions)

4. Run

npm install
npm run dev   # http://localhost:3000

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Available Scripts

Command	Description
npm run dev	Start local development server at http://localhost:3000
npm run build	Build for production
npm run start	Start production server
npm run lint	Run ESLint
npm run seed-recipes	Fetch recipes from Spoonacular and upsert into Supabase
npm run seed-recipes -- --dry-run	Preview what would be seeded without writing to the DB

Seeding recipes

Spoonacular's free tier allows 50 API points per day. The script requests the maximum (100 recipes per cuisine) and lets Spoonacular's daily quota naturally stop it with a 402 — no point estimation needed. Run once daily via the GitHub Action.

Use --dry-run to verify output without consuming your write quota or hitting the database. The flag still fetches from Spoonacular, so avoid running it repeatedly.

The script checks how many Spoonacular recipes are already in the DB before fetching. If the count is at or above the limit (default: 500), it exits early without making any API calls. Override the limit with the SEED_MAX env var:

SEED_MAX=1000 npm run seed-recipes

Duplicate recipes are also handled at the DB level — upsert on external_id ensures the same recipe is never inserted twice regardless of how many times you run the script.

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Technology Stack

Area	Technology
Framework	Next.js 14 (App Router)
Language	TypeScript
Styling	Tailwind CSS
Animation	Framer Motion
Database	PostgreSQL via Supabase
Auth	Supabase Auth
Icons	Lucide React

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Project Goals

• Build a modern, engaging food discovery experience
• Apply recommendation system concepts
• Practice full-stack development with Next.js and Supabase
• Learn collaborative software development

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Link to repo

https://github.com/GGlencoe/Binge-SWE

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Team

Developed as part of CSCI-3300 Software Engineering at Saint Louis University.

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License

TBD