AIHOT
一个自己找热点、自己写日报的网站框架。把信源和精选标准换成你的，它就是你的行业热点站。
The Lens
By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.
Updated Sep 2026
AIHOT is the full code behind aihot.news, a Chinese AI news site. It pulls items from RSS, web pages, APIs, X and WeChat accounts, has an LLM filter and score each one twice, writes Chinese headlines and summaries for what passes, and publishes daily, weekly and monthly digests. Swap in your own sources and scoring prompts and you get a news site for law, finance, or whatever you follow. MIT, free.
Self-hosting is Docker Compose with five containers on a server with at least 2 cores and 4 GB of RAM. You need an OpenAI-compatible LLM key, and X or WeChat collection goes through paid per-request APIs. The author's own test run used about 930 model calls to import 152 demo items, so budget for tokens.
The live site is free, and its RSS, API and MCP feeds need no key. Solo: read aihot.news, or deploy your own for a niche. Small teams: a cheap way to run an industry briefing without a human editor.
The catch: everything is in Chinese, the docs and the output. It ships 18 demo feeds, not the live site's real source list, so the curation that makes aihot.news good is yours to rebuild. And the AIHOT name and logo aren't covered by the MIT license.
Free vs Self-Hosted vs Paid
fully freeFree: aihot.news is free with no registration. Its RSS feeds, public API and MCP server are anonymous and read-only, no API key needed. The framework is MIT (the AIHOT name and logo are excluded).
Self-hosted: Docker Compose (Postgres 17, api, worker, web, setup), recommended server 2 cores / 4 GB RAM. Costs are your own:
- LLM: required, any OpenAI-compatible provider (the docs suggest DeepSeek, Qwen or Zhipu). Every item is pre-filtered, likely picks are scored twice, and winners get a written headline and summary. The author's test import of 152 items took about 930 model calls.
- Optional paid collectors: X accounts via SocialData, WeChat official accounts via Dajiala, Jina Reader as a page-rendering fallback. All billed per request, all off until you add a key, all with per-minute/hour/day caps.
Paid: None from the author.
Free code and a free live site. Running your own copy costs whatever your LLM provider charges.
What to do by team size
- Solo
- free to read; self-hosting costs LLM tokens
- Small team
- free code; budget for LLM calls and a 4 GB server
- Medium team
- free, if someone can maintain Chinese-language prompts and sources
- Large team
- free code, but it's a single-site snapshot, not a supported product
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License: MIT License
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