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A framework for a site that finds and writes its own news digests

AIHOT is an open-source engine for a self-made media site: it gathers sources, scores the news, and publishes a ready digest every day.

01KKKKhazix/AIHOT 8.7kTypeScript

It's website code that scans chosen sources daily, uses a language model to pick what matters, and turns that into headlines and short digests.

When it helps

Useful if you want your own topic-focused news site (law, HR, finance, AI, etc.) without hiring an editorial team. Skip it if manual news monitoring is enough or you have no LLM API access.

Pros

  • Runs on an ordinary computer, no GPU needed
  • Automatically merges news from different sources into one card
  • Customizable for any topic and your own selection criteria
  • A cheap language model is enough, no need for an expensive one

Cons

  • Site and prompts default to Chinese — you'll need to translate them
  • Requires a paid LLM API key, even if a cheap one
  • First news processing run takes about half an hour

How to set it up — step by step

  1. 1Install Docker and Node.js 24 — the site won't start without them.
  2. 2Clone the repo and launch it via Docker using the command from the README, with your model's API key.
  3. 3Get an LLM API key with an OpenAI-compatible interface, e.g. DeepSeek, Qwen, or Zhipu GLM.
  4. 4Open the site at http://localhost:3000, the admin panel is at /admin.
  5. 5Send the agent the text from the block below to configure sources and language for your topic.
  6. 6Check the daily digest the next day — the first processing run takes about half an hour.

Text for your agent

Copy this and send it to your agent — Claude Code, Codex, any of them:

Deploy AIHOT from https://github.com/KKKKhazix/AIHOT — bring it up via Docker following the README, tune it to my topic (I'll tell you which sources matter and what I care about), and show me the daily briefing at http://localhost:3000. You'll need a key for an OpenAI-compatible LLM API — ask me for it if needed.

Light: a regular computer with Docker and Node.js is enough, no GPU needed. All the model work runs through an API key for any OpenAI-compatible LLM — DeepSeek, Qwen or Zhipu GLM, for instance.

Open on GitHub