/auto-news

A personal news aggregator to pull information from multi-sources + LLM (ChatGPT via LangChain) to help us reading efficiently with less noises, the sources including: Tweets, RSS, YouTube, Web Articles, Reddit, and personal Journal notes.

Primary LanguagePythonMIT LicenseMIT

Auto-News: An Automatic News Aggregator with LLM

A personal news aggregator to pull information from multi-sources + LLM (ChatGPT) to help us read efficiently with less noise, the sources including Tweets, RSS, YouTube, Web Articles, Reddit, and random Journal notes.

Why need it?

In the world of this information explosion, we live with noise every day, it becomes even worse after the generative AI was born. Time is a precious resource for each of us, How to use our time more efficiently? It becomes more challenging than ever. Think about how much time we spent on pulling/searching/filtering content from different sources, how many times we put the article/paper or long video as a side tab, but never got a chance to look at, and how much effort to organize the information we have read. We need a better way to get rid of the noises, focus on reading the information efficiently based on our interests, and stay on track with the goals we defined.

See this Blog post and these videos Introduction, Data flows for more details.

auto_news_300k.mp4

Features

  • Pull from Feed sources (including RSS, Reddit, Tweets, etc) and summarize them
  • Summarize YouTube videos (generate transcript if needed)
  • Filter content based on personal interests and remove 80%+ noises
  • Generate TODO list from Takeaways/Journal-notes
  • Weekly top-k aggregations
  • Journal notes summarization and insights generating
  • A unified/central reading experience (e.g., RSS reader-like style, Notion based)

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Architecture

  • UI: Notion-based, cross-platform (Web browser, iOS/Android app)
  • Backend: Runs on Linxu/MacOS

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Backend System Requirements

Component Minimum Requirements Recommended
OS Linux, MacOS Linux, MacOS
CPU 2 cores 4 cores
Memory 6GB 12GB
Disk 20GB 50GB

Quick Start Guide

Preparison

[UI] Create Notion Entry Page

Go to Notion, create a page as the main entry (For example Readings page), and enable Notion Integration for this page

[Backend] Create Environment File

Checkout the repo and copy .env.template to build/.env, then fill up the environment vars:

  • NOTION_TOKEN
  • NOTION_ENTRY_PAGE_ID
  • OPENAI_API_KEY
  • [Optional] REDDIT_CLIENT_ID and REDDIT_CLIENT_SECRET
  • [Optional] Vars with TWITTER_ prefix

[Backend] Build Services

make deps && make build && make deploy && make init

[Backend] Start Services

make start

Now, the services are up and running, it will pull sources every hour.

[UI] Set up Notion Tweet/RSS/Reddit list

Go to the Notion entry page we created before, and we will see the following folder structure has been created automatically:

Readings
├── Inbox
│   ├── Inbox - Article
│   └── Inbox - YouTube
│   └── Inbox - Journal
├── Index
│   ├── Index - Inbox
│   ├── Index - ToRead
│   ├── RSS_List
│   └── Tweet_List
│   └── Reddit_List
└── ToRead
    └── ToRead
  • Go to RSS_List page, and fill in the RSS name and URL
  • Go to Reddit_List page, and fill the subreddit names
  • Go to Tweet_List page, and fill in the Tweet screen names (Tips: Paid Account Only)

[UI] Set up Notion database views

Go to Notion ToRead database page, all the data will flow into this database later on, create the database views for different sources to help us organize flows easier. E.g. Tweets, Articles, YouTube, RSS, etc

Now, enjoy and have fun.

Operations

[Monitoring] Control Panel

For troubleshooting, we can use the URLs below to access the services and check the logs and data

Service Role Panel URL
Airflow Orchestration http://localhost:8080
Milvus Vector Database http://localhost:9100
Adminer DB accessor http://localhost:8070

Stop/Restart Services

In case we want, apply the following commands from the codebase folder.

# stop
make stop

# restart
make stop && make start

Redeploy .env and DAGs

make stop && make init && make start

Upgrade to the latest code

make upgrade && make stop && make init && make start

Rebuild Docker Images

make stop && make build && make init && make start