hnbot 0.0.3

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Hacker News Bot

A Telegram bot that monitors Hacker News for trending articles, generates AI-powered summaries of the discussions, and delivers them straight to your Telegram chat.

Features

• RSS feed monitoring — fetches top stories from hnrss.org filtered by minimum points
• AI-powered summaries — uses OpenAI to distill HN comment threads into concise, structured articles
• Telegraph publishing — creates readable long-form pages on Telegraph
• Telegram notifications — sends formatted messages with links to the original article, HN discussion, and the generated summary
• Redis deduplication — tracks processed entries to avoid sending duplicate notifications
• Concurrent processing — handles multiple articles in parallel with configurable concurrency limits
• Retry with backoff — automatically retries transient HTTP failures

How It Works

hnrss.org RSS feed
        │
        ▼
  Filter by points
        │
        ▼
  Fetch HN comments ──► HTML → Markdown
        │
        ▼
  OpenAI summarisation
        │
        ▼
  Publish to Telegraph
        │
        ▼
  Notify via Telegram

Quick Start

Prerequisites

• Python 3.12+
• uv
• A Telegram Bot Token and a target chat ID
• An OpenAI API key
• A running Redis instance (for deduplication)

Install & Run

# Clone the repository
git clone https://github.com/narumiruna/hnbot.git
cd hnbot

# Install dependencies
uv sync

# Configure environment variables
cp .env.example .env
# Edit .env and fill in the required values

# Run the bot
uv run hnbot

Install from PyPI

pip install hnbot

Docker

docker build -t hnbot .
docker run --env-file .env hnbot

Configuration

All settings are loaded from environment variables (or a .env file). See .env.example for the full template.

Required

Variable	Description
OPENAI_API_KEY	OpenAI API key
BOT_TOKEN	Telegram bot token
CHAT_ID	Telegram chat ID to receive notifications

Optional

Variable	Default	Description
OPENAI_BASE_URL	(OpenAI default)	Custom OpenAI-compatible API endpoint
OPENAI_MODEL	gpt-5-mini	LLM model to use for summarisation
LOGFIRE_TOKEN	—	Logfire token for observability
REDIS_HOST	localhost	Redis host
REDIS_PORT	6379	Redis port
REDIS_DB	0	Redis database number
FEED_POINTS	100	Minimum HN points threshold for feed entries
HTTP_TIMEOUT_SECONDS	10.0	HTTP request timeout (seconds)
HTTP_USER_AGENT	hnbot/0.0.0	HTTP User-Agent header
COMMENTS_FETCH_CONCURRENCY	1	Max parallel comment fetches
ARTICLE_PIPELINE_CONCURRENCY	3	Max parallel article generation tasks
CHUNK_SIZE	200000	Max characters per chunk for LLM processing
BATCH_SLEEP_SECONDS	0.5	Delay before processing a batch

Development

# Install all dependencies (including dev)
uv sync

# Run the full development gate (format → lint → type-check → test)
just all

# Or run individual steps
just format   # ruff format
just lint     # ruff check --fix
just type     # ty check
just test     # pytest with coverage

License

MIT