每天刷Hacker News、Twitter、Reddit、GitHub，你烦不烦？全是水文、重复内容、噪音，跟垃圾堆一样。 我最近挖到一个新工具：Horizon，硬核科技新闻雷达。让它替你盯着全球科技圈，你只需要每天早上开一份简报。 核心就一个字：把噪音全干掉，精华端到你面前。 AI严格把关：支持DeepSeek、Claude等模型，每条资讯打0-10分，低分直接过滤，不糊弄你 神评论自动提取：把Hacker News和Reddit里真正有眼光的讨论总结出来 自动背景调查：遇到陌生术语、公司或技术，自动联网补知识，不用你瞎猜 全网智能去重：同一个新闻在多个平台刷屏，自动合并，只留一次 中英双语日报：生成干净专业的日报，方便快速浏览 一键推送分发：飞书、邮箱、微信、GitHub Pages等渠道随便选 信息差时代，晚知道24小时，可能就错过一轮机会。晚一天，你就落后一拍。感兴趣的去试试吧，DYOR。 https://github.com/Thysrael/Horizon…

Thysrael/Horizon

Source: https://github.com/Thysrael/Horizon

Screenshots

Ranked Daily Briefing

Context, Summary & Discussion

More Screenshots

Terminal Output

Feishu Notification

Email Delivery

Why Horizon?

Good news is scattered; bad news is endless. Horizon gives you a personal first pass over Hacker News, Reddit, Telegram, RSS, and GitHub: it fetches, deduplicates, scores, filters, and enriches stories with background context and community discussion.

But Horizon is not just another summarizer. AI is great at reducing noise, but news still needs human taste: the sources you trust, the comments that change how you read a story, and the hidden gems only people can share. Horizon keeps that human layer in the loop with customizable sources, thresholds, models, languages, delivery channels, comment summaries, and a community source hub.

Features

• 📡 Watch Your Own Sources — Track Hacker News, RSS, Reddit, Telegram, Twitter/X, and GitHub releases or user activity in one pipeline
• 🤖 Turn Noise Into a Reading List — Score each item from 0-10 with Claude, GPT, Gemini, DeepSeek, Doubao, MiniMax, or any OpenAI-compatible API
• 🔗 Merge Repeated Stories — Deduplicate the same story across platforms before it reaches your briefing
• 🔍 Understand the Background — Add web-researched context for unfamiliar concepts, companies, projects, and technical terms
• 💬 Read the Conversation — Collect and summarize community comments from Hacker News, Reddit, and other supported sources
• 🌐 Publish in Two Languages — Generate English and Chinese daily briefings from the same source set
• 📝 Ship a Daily Site — Publish generated Markdown as a GitHub Pages daily briefing site
• 📧 Deliver by Email — Run a self-hosted SMTP/IMAP newsletter with automatic subscribe and unsubscribe handling
• 🔔 Push to Chat or Automations — Send templated results to Feishu/Lark, DingTalk, Slack, Discord, or custom webhook endpoints
• 🧙 Start From Your Interests — Use the setup wizard to generate a personalized source configuration
• ⚙️ Tune the Radar — Customize sources, thresholds, models, languages, and delivery channels from one JSON config

How It Works

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  "themeVariables": {
    "fontFamily": "ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, Segoe UI, sans-serif",
    "fontSize": "18px",
    "primaryTextColor": "#2d2a3e",
    "primaryBorderColor": "#e0dbd3",
    "lineColor": "#7c7891",
    "tertiaryColor": "#faf8f5",
    "clusterBkg": "#f3f0eb",
    "clusterBorder": "#e0dbd3"
  }
}}%%
flowchart LR
    classDef config fill:#fbbf24,stroke:#d4a017,color:#2d2a3e,stroke-width:1.5px;
    classDef source fill:#ede7fb,stroke:#6d4aaa,color:#2d2a3e,stroke-width:1.5px;
    classDef process fill:#ffe8db,stroke:#e0652e,color:#2d2a3e,stroke-width:1.5px;
    classDef output fill:#f9d7e5,stroke:#be185d,color:#2d2a3e,stroke-width:1.5px;

    config["⚙️ Config<br/>sources, thresholds, models, outputs"]

    subgraph sources["Configured Sources"]
        rss["📡 RSS"]
        hn["📰 Hacker News"]
        reddit["💬 Reddit"]
        telegram["✈️ Telegram"]
        twitter["🐦 Twitter / X"]
        github["🐙 GitHub"]
    end

    fetch["📥 Fetch"]
    dedup["🧹 Deduplicate"]
    score["🤖 AI Score & Filter"]
    enrich["🔎 Enrich"]
    summary["📝 Summarize"]

    subgraph outputs["Outputs"]
        direction TB
        site["🌐 Pages"]
        email["📧 Email"]
        webhook["🔔 Webhooks"]
        mcp["🧩 MCP"]
    end

    config --> fetch
    rss --> fetch
    hn --> fetch
    reddit --> fetch
    telegram --> fetch
    twitter --> fetch
    github --> fetch

    fetch --> dedup --> score --> enrich --> summary
    config --> score
    config --> summary
    config --> outputs

    summary --> site
    summary --> email
    summary --> webhook
    summary --> mcp

    class config config
    class rss,hn,reddit,telegram,twitter,github source
    class fetch,dedup,score,enrich,summary process
    class site,email,webhook,mcp output

1. Define — Configure sources, thresholds, models, languages, and delivery from one JSON config.
2. Fetch — Pull latest content from all configured sources concurrently.
3. Deduplicate — Merge items pointing to the same story or URL across platforms.
4. Score & Filter — Use AI to rank items and keep only those above your threshold.
5. Enrich — Search the web for background context and collect community discussion for important items.
6. Summarize — Generate a structured Markdown briefing with summaries, tags, and references.
7. Deliver — Publish the result to GitHub Pages, email, webhooks such as Feishu, MCP, or local files.

Quick Start

1. Install

Option A: Local Installation

git clone https://github.com/Thysrael/Horizon.git
cd horizon

# Install with uv (recommended)
uv sync

# Install test/development extras when needed
uv sync --extra dev

# Or with pip
pip install -e .

dev is currently defined as an optional extra in pyproject.toml, so use uv sync --extra dev for pytest and other development dependencies.

Option B: Docker

git clone https://github.com/Thysrael/Horizon.git
cd horizon

# Configure environment
cp .env.example .env
cp data/config.example.json data/config.json
# Edit .env and data/config.json with your API keys and preferences

# Run with Docker Compose
docker-compose run --rm horizon

# Or run with custom time window
docker-compose run --rm horizon --hours 48

2. Configure

Option A: Interactive wizard (recommended)

uv run horizon-wizard

The wizard asks about your interests (e.g. “LLM inference”, “嵌入式”, “web security”) and auto-generates data/config.json.

Option B: Manual configuration

cp .env.example .env          # Add your API keys
cp data/config.example.json data/config.json  # Customize your sources

Minimal manual configuration:

{
  "ai": {
    "provider": "openai",
    "model": "gpt-4",
    "api_key_env": "OPENAI_API_KEY"
  },
  "sources": {
    "rss": [
      { "name": "Simon Willison", "url": "https://simonwillison.net/atom/everything/" }
    ]
  },
  "filtering": {
    "ai_score_threshold": 6.0
  }
}

For the full reference, see the Configuration Guide.

3. Run

Local Installation

uv run horizon           # Run with default 24h window
uv run horizon --hours 48  # Fetch from last 48 hours

With Docker

docker-compose run --rm horizon           # Run with default 24h window
docker-compose run --rm horizon --hours 48  # Fetch from last 48 hours

The generated report will be saved to data/summaries/.

4. Automate (Optional)

Horizon works great as a GitHub Actions cron job. See .github/workflows/daily-summary.yml for a ready-to-use workflow that generates and deploys your daily briefing to GitHub Pages automatically.

Supported Sources

Where Your Briefing Goes

Horizon can publish or deliver the generated briefing in several ways:

For setup details, see the Configuration Guide. For MCP tool references and client setup, see src/mcp/README.md and src/mcp/integration.md.

Documentation

Project Status

Horizon already supports the full daily briefing loop: multi-source collection, AI scoring, deduplication, enrichment, comment summaries, bilingual generation, GitHub Pages publishing, email delivery, webhook delivery, Docker deployment, MCP integration, and the setup wizard.

Planned improvements:

• More source types, such as Twitter/X and Discord
• Custom scoring prompts per source
• Publish releases on GitHub
• Publish the package to PyPI for pip install

Contributing

Contributions are welcome! Feel free to open issues or submit pull requests.

Share Sources

Want to share valuable source discoveries with the Horizon community? Please submit them through horizon1123.top.

Great candidates: niche RSS discoveries, active subreddit trends, notable GitHub updates, or Telegram channel highlights in your area of expertise.

Acknowledgements

• Special thanks to LINUX.DO for providing a promotion platform.
• Special thanks to HelloGitHub for valuable guidance and suggestions.
• Special thanks to AIGC Link for the promotions on XiaoHongShu.

License

MIT