AIHOT is a self-hosted news aggregation and daily digest framework that automatically discovers trending topics and generates summaries for any industry.
The tool solves the problem of manually curating industry-specific news by automating the entire pipeline from source collection through publication. It pulls content from multiple RSS feeds, uses large language models to filter and score articles independently across two passes, clusters related stories from different sources into single events, ranks them by discussion volume, and generates Chinese titles and summaries for a daily digest. The framework includes the complete curation logic, clustering algorithms, hotness ranking, and all prompt templates with their selection thresholds.
Anyone building an industry-specific news site should consider this if they want to customize every stage of the pipeline to their domain expertise. The tool is designed for operators who understand their industry's information sources and can identify what constitutes a genuine trend in their field. It ships with eighteen public English-language AI news sources as examples to demonstrate functionality, but you replace these with sources relevant to your industry and adjust the selection criteria to match your knowledge. The project explicitly positions itself as a framework snapshot extracted from a live production system rather than a polished generic tool, so adopters should expect to modify and maintain the codebase themselves.
Development activity shows the maintainer actively synchronizes updates from the live AIHOT service back to the repository, though not every change is guaranteed to be mirrored immediately. The maintainer acknowledges limited software engineering background and welcomes issue reports while noting response times may be slow. The codebase was substantially rewritten with AI assistance to improve clarity compared to earlier versions, indicating ongoing refinement of code quality.
