A self-hostable application that tracks product prices from nearly any online store, notifying users when prices meet their targets. It appeals to privacy-conscious users and bargain hunters seeking to manage their data and savings on their own infrastructure.

How It Works

This web application periodically checks product prices, stores historical data for charting, and sends customizable notifications. Its key advantage is broad store compatibility, often working out-of-the-box or with minimal configuration. An optional AI assist feature leverages user-provided AI models (OpenAI, Anthropic, Gemini, Ollama) to aid in price extraction and scraping rule generation for complex sites.

Quick Start & Requirements

• Installation: Recommended via Docker and docker-compose.
  • Command: touch .env && docker compose up -d
• Prerequisites: Docker, docker-compose.
• Default Login: admin@example.com / admin (change immediately).
• Documentation: Links to "docs", "screenshots", "product overview", and "price history" are implied.

Highlighted Details

• Universal Store Support: Tracks products from virtually any online store, extensible via configuration.
• AI-Assisted Scraping: Optional AI integration helps extract prices and bootstrap scraping rules for difficult sites.
• Cross-Retailer Comparison: Monitors the same product across multiple retailers to find the lowest current price.
• Price History & Analysis: Charts price trends for informed purchasing decisions.
• Flexible Notifications: Supports alerts via email, Pushover, Telegram, Discord, Apprise, and ntfy.
• Availability & Unit Pricing: Detects stock status and calculates unit prices for accurate value comparison.
• Integrated Search: Connects with SearXNG for in-app product discovery.
• Multi-User Support: Allows shared instances with individual user profiles.
• Responsive UI: Features a modern, mobile-friendly interface with light and dark modes.

Maintenance & Community

Maintained by Jeremy Graham. Development adheres to coding standards (Pint, PHPStan) and uses testing frameworks (Pest/PHPUnit), with a Lando-based dev environment. No specific community channels or sponsorship details were provided in the README snippet.

Licensing & Compatibility

The specific license is detailed in LICENSE.md (not provided in the snippet). As a self-hostable application, it offers strong data privacy and control. Commercial use compatibility is not explicitly detailed.

Limitations & Caveats

Web scraping functionality may break if target websites change their structure. The specific software license terms require consulting LICENSE.md. Users must provide their own AI service credentials or local models for the AI assist feature.