AI Goofish Monitor is a web-based monitoring and analysis system for Xianyu, the secondhand marketplace operated by Alibaba.
The tool solves the problem of finding desired products among vast quantities of listings on Xianyu by automating product discovery and filtering. It uses Playwright for browser automation combined with AI models to monitor listings in real time or on a schedule. Users define search tasks with natural language, and the system applies AI-driven analysis to evaluate products against custom criteria. The tool supports multiple concurrent monitoring tasks, each with independent keyword filters, price ranges, geographic filters, and AI prompts. It includes advanced filtering options such as free shipping, publication date ranges, and three-level regional selection by province, city, and district. Notifications can be sent through multiple channels including ntfy.sh, enterprise WeChat, Bark, Telegram, and webhooks. The system manages multiple Xianyu accounts and proxy rotation with automatic retry on failure, and supports Cron-based scheduling for periodic monitoring.
Developers should choose this tool if they need to automate product discovery on Xianyu with AI-powered filtering and want a complete management interface. It suits projects requiring multi-account monitoring with flexible scheduling and notification routing. The system is designed for Docker deployment with Chromium included in the container, eliminating the need to install browsers on the host machine. Data is stored in SQLite with automatic schema creation on startup, and the tool can migrate historical data from previous file-based storage formats. Web UI access requires username and password authentication, with default credentials provided.
The project maintains active development with regular updates to its Docker images and database schema. The codebase includes comprehensive configuration documentation covering environment variables, data storage paths, and deployment options. The tool provides persistent storage for multiple data types including task definitions, monitoring results, price history, login state cookies, and application logs, with clear guidance on which directories should be mounted for data persistence.
