raveberry VS marked

Raveberry is probably worth checking out.

You don't need to use that project, though. You could probably use Traefik, although I've never worked with it and I'm not sure whether this is the right tool for this purpose. You could also modify the nginx config and mount it into the raveberry-nginx container:

The default streaming password is "raveberry:raveberry". You can change it on the icecast admin interface at http://raveberry.local:8000/admin, see also here.

Github: https://github.com/raveberry/raveberry

You can try Raveberry. It does support also local files.

Raveberry is a project that makes parties more fun by allowing everybody to influence the music. With an LED ring in the transparent case of the Raspberry Pi, I tried to make it visually interesting as well. I want to share with you how the ring is connected and controlled, how I made the lights react to the music and how I modified the colors to make them a little more appealing.

Improved documentation on the remote feature in this file, adding example steps for a minimal setup.

For anyone else stumbling upon something similar, we moved to Github.

Take a look at Raveberry, it can play spotify playlists (though you need to set it up yourself)

Sounds like Raveberry

Next, install gray-matter to extract metadata from the front matter of markdown files, and marked to convert the markdown files to HTML:

📑 Marked Markdown parser. Use it to create your own markdown editor.

Vrite SDK provides a few built-in input and output transformers. These are functions, with standardized signatures to process the content from and into Vrite. In this case, gfmInputTransformer is essentially a GitHub Flavored Markdown parser, using Marked.js under the hood.

Another contestant in this realm is Bright[1]. It runs entirely on the server and doesn't increase bundle size as seen here[2]. Regarding parsing speed tree-sitter is without a doubt performant since it is written in Rust, but I don't have any problems "parsing on every keystroke" with a setup containing Marked[3], highlight.js[4] and a sanitizer. I did however experience performance issues with other Markdown parser libraries than Marked.

[1]: https://bright.codehike.org/

[2]: https://aihelperbot.com/test-suite

[3]: https://github.com/markedjs/marked

[4]: https://highlightjs.org/

The project uses markedJS to convert markdown into HTML, this is their GitHub page.

To handle pasting block Markdown content like this, I had to tap into ProseMirror and implement a custom mechanism (though somewhat based on TipTap’s paste rules), detecting starting and ending points of the blocks and parsing them with Marked.js.

I am using marked for markdown parsing together with marked-highlighting to handle syntax highlighting and everything is working as it should.

I'm trying to render user input using SvelteMarkdown (that uses marked).

GPT API returns data in markdown format. You can parse it using a Markdown library and string manipulation. On Electron app I developed https://jhappsproducts.gumroad.com/l/gpteverywhere, I used https://github.com/markedjs/marked and a code syntax highlighting package to display code blocks. And used JavaScript string manipulation to detect when code blocks start and end so I could add COPY/SAVE buttons to the blocks. I hope this helps, and happy coding! :)

Again, with streaming enabled, you’ll now receive new tokens as soon as they’re available. Given that OpenAI’s API uses Markdown in its response format, a full message will need to be put together from the incoming tokens and parsed to HTML, as accepted by the replaceContent function. For this purpose, I’ve used the Marked.js parser.