Flyer Crawler - Grocery AI Analyzer

Flyer Crawler is a web application that uses Google Gemini AI to extract, analyze, and manage data from grocery store flyers. Users can upload flyer images or PDFs, and the application automatically identifies items, prices, and sale dates, storing structured data in a PostgreSQL database for historical analysis, price tracking, and personalized deal alerts.

Our mission: Help people save money by finding good deals that are only advertised in store flyers. The app makes uploading flyers as easy and accurate as possible, and matches sales to users' needs.

Features

AI-Powered Data Extraction: Upload PNG, JPG, or PDF flyers to automatically extract store names, sale dates, and detailed item lists with prices and quantities
Bulk Import: Process multiple flyers at once with summary reports of successes, skips (duplicates), and errors
Personalized Watchlist: Create a watchlist of specific grocery items you want to track
Active Deal Alerts: See current sales on your watched items from all valid flyers
Price History Charts: Visualize price trends of watched items over time
Shopping List Management: Create multiple shopping lists, add items from flyers or your watchlist, and track purchased items
User Authentication: Secure sign-up, login, profile management, and account deletion
Dynamic UI: Responsive interface with dark mode and metric/imperial unit systems

Tech Stack

Layer	Technology
Frontend	React, TypeScript, Tailwind CSS
AI	Google Gemini API (`@google/genai`)
Backend	Node.js, Express
Database	PostgreSQL with PostGIS
Authentication	Passport.js (Google, GitHub OAuth)
Charts	Recharts

Quick Start

# Install dependencies
npm install

# Run in development mode
npm run dev

See INSTALL.md for detailed setup instructions.

Documentation

Document	Description
INSTALL.md	Local development setup with Podman
DATABASE.md	PostgreSQL setup, schema, and extensions
AUTHENTICATION.md	OAuth configuration (Google, GitHub)
DEPLOYMENT.md	Production server setup, NGINX, PM2

Environment Variables

This project uses environment variables for configuration (no .env files). Key variables:

Variable	Description
`DB_HOST`, `DB_USER`, `DB_PASSWORD`	PostgreSQL credentials
`DB_DATABASE_PROD`	Production database name
`JWT_SECRET`	Authentication token signing key
`VITE_GOOGLE_GENAI_API_KEY`	Google Gemini API key
`GOOGLE_MAPS_API_KEY`	Google Maps Geocoding API key
`REDIS_PASSWORD_PROD`	Redis password

See INSTALL.md for the complete list.

Scripts

Command	Description
`npm run dev`	Start development server
`npm run build`	Build for production
`npm run start:prod`	Start production server with PM2
`npm run test`	Run test suite
`npm run seed`	Seed development user accounts

License

[Add license information here]

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