What problem it solves

Users need to search large volumes of Xianyu listings and identify products that match specific requirements. The project addresses this with configurable monitoring tasks, automated analysis, filtering, scheduling, and notification channels, while providing a web interface for managing accounts, prompts, logs, and results.

Key features

• AI-assisted task creation and analysis — Create tasks from natural-language requirements and analyze listings with a multimodal model. AI task generation runs as a background job with separate progress feedback.

  Source: README

• Multiple concurrent monitoring tasks — Configure separate keywords, price ranges, filters, schedules, and AI prompts for concurrent monitoring tasks.

  Source: README

• Detailed search filters — Narrow searches with shipping, newly published time range, and province, city, and district filters.

  Source: README

• Multi-channel notifications — Send matching listing notifications through ntfy.sh, WeCom, Bark, Telegram, Webhook, and other supported channels.

  Source: README

• Web management and runtime controls — Manage tasks, accounts, AI standards, logs, and results through the Web UI. The system also supports scheduled execution, account and proxy rotation, and failure retries.

  Source: README, web-ui

Quick start

Copied verbatim from the project's README.

chmod +x start.sh
./start.sh

Who it may suit

This project may suit users who want to automate the discovery and evaluation of Xianyu listings through scheduled or real-time monitoring. It may also suit developers who need a Web interface for integrating Playwright, AI analysis, notification services, and SQLite-backed task data.

Topics to discuss

• Which natural-language requirements produce the most reliable AI task standards?

• Which notification and proxy configurations work best for different deployment environments?

• How should monitoring tasks balance region and freshness filters against broader result coverage?

Written by ReadmeX AI from the project's README, source and public GitHub data; it may contain mistakes.

Read the original README https://github.com/Usagi-org/ai-goofish-monitor#readme

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