For a long time, I'd been looking for a news reader that could filter out noise and surface only stories that really interest me. I couldn’t find one, so I built it myself. That's the way, right? :-D
In my case (over 1000 news/day), it filters out over 80% of news (those that are irrelevant for me), saving me a corresponding amount of time.
Here’s how it works:
- For each news entry, the reader automatically assigns multiple tags.
- You can create scoring rules like `books + sci-fi -> +5 score`, `politics + new-york -> -10 score`.
- News entries are sorted by score, putting the most relevant content on top.
The reader is open-source, self-hosted, and can work without proprietary LLM APIs. You can replace the APIs entry points with your self-hosted OpenAI-compatible API, or fully disable them, or implement custom non-LLM tag processors.
I'd love your feedback, questions, or suggestions!
For a long time, I'd been looking for a news reader that could filter out noise and surface only stories that really interest me. I couldn’t find one, so I built it myself. That's the way, right? :-D
In my case (over 1000 news/day), it filters out over 80% of news (those that are irrelevant for me), saving me a corresponding amount of time.
Here’s how it works:
- For each news entry, the reader automatically assigns multiple tags.
- You can create scoring rules like `books + sci-fi -> +5 score`, `politics + new-york -> -10 score`.
- News entries are sorted by score, putting the most relevant content on top.
The reader is open-source, self-hosted, and can work without proprietary LLM APIs. You can replace the APIs entry points with your self-hosted OpenAI-compatible API, or fully disable them, or implement custom non-LLM tag processors.
I'd love your feedback, questions, or suggestions!
Follow development here:
- GitHub: https://github.com/Tiendil/feeds.fun
- Reddit: https://www.reddit.com/r/feedsfun/
- Discord: https://discord.gg/C5RVusHQXy
- Blog: https://blog.feeds.fun/