🟢 Beginner–Intermediate ⚙️ Type: AI News Radar / Aggregator 💸 Free & Open Source ⭐ 7,400+ GitHub Stars
What is Horizon?
Horizon (created by Thysrael) is a personalized, AI-powered “news radar” designed to cure doomscrolling. Instead of manually checking Hacker News, Reddit, Telegram, Twitter, and dozens of RSS feeds every morning, Horizon acts as your tireless, personal editor-in-chief.
It runs in the background, fetching hundreds of articles and posts from your configured sources. But Horizon is not just a standard RSS reader that dumps raw links into a feed. It deduplicates the stories and then uses an LLM (like Claude, GPT-4o, DeepSeek, or a local Ollama model) to aggressively evaluate and score each item from 0 to 10 based on your specific interests.
It filters out the clickbait and noise, generating a highly readable, summarized daily briefing. It even reads the community comments (e.g., from Reddit or Hacker News) and summarizes the debate for you, adding vital context. The final briefing can be output directly to your terminal, sent via Email, pushed to Feishu, or automatically published as a GitHub Pages daily website in both English and Chinese.
Who is it for?
- Information Junkies & Researchers who suffer from FOMO but don’t have the time to sift through thousands of daily tech and finance posts to find the actual signal.
- Developers who want to track specific GitHub releases, Hacker News trends, and Reddit programming communities without getting distracted by social media timelines.
- Bilingual Readers who want complex English technical news automatically summarized and translated into Chinese (or vice versa) in a single daily digest.
- Homelabbers & Automators looking to self-host a fully automated news pipeline on a Raspberry Pi or home server using Docker and Cron jobs.
What makes it special?
- Intelligent 0-10 Scoring — You can customize the scoring prompt. Tell the AI, “I only care about open-source AI tools and Python libraries,” and it will ruthlessly score generic tech news as a 2 and specific AI releases as a 9, only showing you the top-tier content.
- Community Discussion Summaries — An article is often only half the story; the real value is in the comments. Horizon fetches the comment threads from Hacker News and Reddit and includes a summary of the community’s reaction (e.g., “Users are criticizing the new pricing model”).
- Bring Your Own Model (BYOM) — You are not locked into an expensive subscription. You can use cheap, highly capable models like DeepSeek, standard OpenAI/Anthropic APIs, or run it 100% free and offline using Ollama.
- Rich Delivery Options — It doesn’t just spit out a text file. It can automatically compile the news into a beautiful static HTML site, send you a formatted email before you wake up, or ping your team’s chat app.
Requirements before you start
Horizon is a Python-based pipeline that is incredibly easy to configure. You will need:
- Python 3.10+ or Docker — Depending on how you prefer to deploy applications. (The modern
uvpackage manager is highly recommended if installing natively). - An LLM API Key — An active API key for OpenAI, Anthropic, DeepSeek, Gemini, Doubao, or a locally running Ollama instance.
- A JSON Config File — You will need to spend a few minutes defining your favorite RSS feeds, subreddits, and Telegram channels in a simple
config.jsonfile.
Step-by-step installation
You can run Horizon manually via Python, but the easiest and cleanest way to run it on a schedule is via Docker.
Method 1 — Docker Deployment (Recommended)
Open your terminal and clone the repository, then copy the example configuration files:
git clone https://github.com/Thysrael/Horizon.git
cd Horizon
cp .env.example .env
cp data/config.example.json data/config.jsonNext, open the .env file in a text editor and paste your API keys (e.g., your OpenAI or DeepSeek key). Then, open data/config.json and define which RSS feeds or Hacker News settings you want to track.
Once configured, run the Docker container to fetch, score, and generate your first briefing:
docker compose run --rm horizonMethod 2 — Native Installation via uv
If you prefer to run it natively on your machine or set it up in a custom Python virtual environment, the developers recommend using Astral’s blazing-fast uv package manager:
git clone https://github.com/Thysrael/Horizon.git
cd Horizon
uv sync(Optional: If you want to use the OpenBB financial news scrapers, install the extra dependencies: uv sync --extra openbb).
Edit your .env and config.json files, then trigger the script:
uv run python -m horizonThe resulting Markdown briefings will be saved locally in your output folder, or dispatched via your configured delivery method (Email/Feishu).
Common errors and fixes
| Error | What it means | How to fix it |
|---|---|---|
| Reddit or Twitter/X scraping returns empty results or errors | These platforms have extremely strict anti-bot measures. Fetching data from them anonymously often results in IP blocks or HTTP 403 Forbidden errors. | For Reddit, ensure you are not polling too aggressively. For X/Twitter, Horizon relies on RSS bridges or specific API configurations; you may need to provide auth tokens or use a service like RSSHub to reliably bypass Twitter’s login walls. |
| High LLM API Costs | Asking an LLM to read, evaluate, and score 300 different articles every day consumes a massive amount of input tokens. | Do not use GPT-4o for the bulk scoring process. Switch your primary LLM endpoint to a highly affordable, fast model like DeepSeek-Chat, Claude 3.5 Haiku, or a local Ollama model (like Llama 3 8B) to keep daily costs down to pennies. |
ModuleNotFoundError: No module named 'openbb' | You added OpenBB finance sources to your config.json, but you didn’t install the optional OpenBB Python dependencies. | Run uv sync --extra openbb to install the necessary financial SDKs. If you encounter wheel build errors, force binary installation: uv pip install --only-binary=:all: openbb. |
Free vs Paid comparison
| Feature | Horizon (Local Open Source) | Feedly AI / Matter SaaS |
|---|---|---|
| Software Cost | $0 (Free MIT License) | $8 to $12+ per month |
| AI Model Choice | 🟢 Choose any API (OpenAI, Claude, Local) | 🔴 Locked into proprietary vendor AI |
| Comment Thread Summarization | ✅ Yes (Invaluable for Reddit/HN context) | ❌ Rarely supported natively |
| Setup Effort | ⚠️ Requires managing JSON configs and API keys | 🟢 Instant 1-click UI setup |
Bottom line: Horizon is the ultimate antidote to information overload. While standard RSS readers force you to skim through hundreds of headlines, Horizon actually reads the articles and judges them based on your strict criteria. The inclusion of community comment summaries elevates it from a simple aggregator to a true research assistant. If you want a daily, high-signal brief without the doomscrolling, setting up Horizon on a daily cron job is highly recommended.
Alternatives — 3 similar tools
1. Omnivore
Omnivore was one of the most beloved open-source read-it-later apps, featuring excellent text extraction and organizational tools. While less focused on “autonomous AI scoring” than Horizon, it is fantastic for users who want a beautiful, mobile-friendly interface to manually save, highlight, and read articles later.
2. Huginn
If you want to build incredibly complex, multi-step automation logic for your news feeds, Huginn is the granddaddy of open-source “If This Then That” (IFTTT) alternatives. You can set it up to scrape a website, check for specific keywords, and then trigger an email. It is much more powerful than Horizon for general web scraping, but lacks Horizon’s out-of-the-box LLM scoring pipelines.
3. Feedly AI (Leo)
If you don’t want to mess with terminal commands, Docker, or API keys, Feedly’s premium tier is the commercial standard for enterprise news aggregation. Its “Leo” AI allows you to mute specific topics, track specific industry keywords, and summarize articles inside a highly polished web and mobile app.
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