I built a self-hosted news digest that re-ranks itself based on what you actually read

Описание и применение

Создано самодостаточное приложение CondenseIt, которое ежедневно собирает, суммирует и ранжирует новости, учитывая пользовательские предпочтения, используя локальную LLM и прозрачные сигналы ранжирования.

Задача

RSS readers are stateless and repeat the same feed order daily, offering no personalization or memory of user preferences.

Результат

CondenseIt delivers a personalized, self-hosted daily news digest that learns from explicit and implicit user interactions, providing transparent ranking explanations and running efficiently on a Mac Mini without a discrete GPU.

Рабочий процесс

• Configure source feeds via admin panel
• Schedule daily run
• Fetch articles from RSS, YouTube, Reddit, Hacker News, GitHub, Google News, and website change detection
• Summarize each article locally with Ollama (or OpenRouter)
• Score articles using 11 signals (keyword overlap, bigram matching, TF-IDF similarity, category/source averages, implicit engagement, explicit ratings)
• Apply exponential decay to ratings
• Render ranked list in web app with transparency panel
• Allow user to rate articles and adjust preferences

Доказательства

I use RSS readers constantly. The problem I kept running into was that they are stateless.

Источник

CondenseIt is a self-hosted daily news digest. You point it at your sources, it runs on a schedule, summarises everything using a local LLM, and serves the results as a web app you can read in the browser.

Источник

Summaries run through Ollama locally, Metal-accelerated on Apple Silicon. No discrete GPU needed.

Источник