HN Summary Project Introduction
Overview
HN Summary is an impressive open-source project designed to simplify the process of staying updated with the latest stories on Hacker News. This project features a bot that summarizes the top stories presented on Hacker News and then conveniently publishes these summaries to a Telegram channel. By joining the HN Summary channel on Telegram, users can easily witness the bot's operations and benefit from concise story synopses. The channel is accessible here: https://t.me/hn_summary.
HN Summary also has a web presence where individuals can find summaries of current top Hacker News articles at news.jiggy.ai. Feedback is invaluable to this project, as evident in their encouragement for users to flag poor summaries with a thumbs-down emoji on the Telegram channel. For further involvement, users are welcomed to contribute by opening pull requests or issues, and by directly messaging the project owner on Telegram or Twitter (@wskish).
How It Works
The bot's functionality begins whenever a new story appears on the Hacker News API endpoint for top stories. HN Summary uses OpenAI's GPT-3.5-turbo model to create a brief summary of these stories. Once summarized, the bot sends the story's title, its respective summary, and the link to the story to the specified Telegram channel. The broader aim of this project is not just to showcase top content from Hacker News but also to develop an understanding of how modern large language models work. Additionally, HN Summary serves as a testing ground for leveraging other language model capabilities, such as semantic search.
Limitations
Despite its usefulness, the project does face some challenges. The large language model, GPT-3, is known for occasional hallucinations—generating information that isn't accurate but presented convincingly. Moreover, the bot's ability to extract text from HTML is basic and occasionally inaccurate. Websites with paywalls or those structured in a way that complicates text extraction can lead to increased issues. When such challenges arise, the bot might produce incorrect summaries based on insufficient information.
Currently, the bot ignores non-PDF and non-HTML content links and struggles with content from platforms like Reddit and Twitter. These limitations can result in misleading summaries. Another important point is the Telegram message size limitation; posts are truncated to fit within a 4K character limit.
Major Dependencies
HN Summary relies on several major dependencies which are configured through environment variables. These include:
OpenAI:
- Requires an API key for accessing GPT-3 services (
OPENAI_API_KEY).
PostgresQL:
- Utilizes a database to keep track of stories already summarized and related data, requiring details such as the host, user, and password (
HNSUM_POSTGRES_HOST,HNSUM_POSTGRES_USER,HNSUM_POSTGRES_PASS).
Telegram:
- Involves the bot’s Telegram API token and the channel ID where summaries are posted (
HNSUM_TELEGRAM_API_TOKEN,HNSUM_TELEGRAM_CHANNEL_ID).
In summary, the HN Summary project is a robust tool that leverages cutting-edge language models to distill and disseminate Hacker News content conveniently. While it faces certain technical limitations, its open-source nature encourages community participation and continuous improvement.