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youtube2rss

This Telegram bot allows you to turn YouTube videos into podcast feed that you can listen to in your favorite podcast app. Simply send a YouTube link to the bot and it will download the video, extract the audio, and generate an RSS feed that you can host on your server or use S3 storage.

The bot is built using Bun and uses the youtube-dl-exec library to download and extract the audio from the YouTube videos. It also uses the podcast library to generate the RSS feed.

To use the bot, you'll need to set up a Telegram bot and get an API token. You'll also need to have Bun and Node.js installed.

Installation

  1. Clone this repository:

    git clone https://github.com/uqe/youtube2rss

  2. Install dependencies:

    bun install

  3. Create SQLite database:

    bun run prepare

  4. Create the .env or .env.dev file with your Telegram bot token and Server URL (both are required) like in the .env.example file.

  5. Start a Teleram bot (production):

    bun run start

    or in development mode:

    bun run start:dev

How to use

  1. Start a chat with your bot in Telegram.

  2. Send the bot a YouTube link.

  3. The bot will download the video, extract the audio, and generate an RSS feed.

  4. Host the RSS feed on your server and subscribe to it in your favorite podcast app.

Bun static file server usage (optional)

  1. Start the static file server (production):

    bun run serve

    or development mode:

    bun run serve:dev

S3 file storage usage (optional)

  1. Fill env variables: TELEGRAM_BOT_TOKEN, SERVER_URL, S3_BUCKET, S3_ACCESS_KEY, S3_ENDPOINT and S3_SECRET_KEY in the .env or .env.dev file.

If all variables are set, the bot will store .mp3 files and generated rss.xml file in your S3 bucket. I'm using Cloudflare R2 as S3 compatible storage. The free plan is sufficient for my needs.

License

This project is licensed under the MIT License. See the LICENSE file for details.

TODO list

  • Update README
  • Add pm2
  • Better logging
  • Add thumbnails podcast episodes
  • Parse timestamps in video description and add them to the podcast feed