marked VS Jinja2

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.

But, on the other hand, I can read in the jinja repository that there is not the same Switching From Other Template Engines and also exists documentation about Support for templates engines

jinja: Default templating engine for and dependency of flask

or as complex as bringing Jinja into the picture. Some other options include mustache templates, the built in Template class, and some libraries noted here.

Jinja

Hey u/GuzTech , this issue is mostly related to an old version of jinja that you might be using, here is the report: https://github.com/pallets/jinja/issues/1585

Turns out it wasn't how I was getting the variable -- registered from the api call VS lookup('file') -- it was mainly that for some reason, using 'map()' sometimes needs ' | list | to_json ' tacked on to the end to correctly output the results without the "generator object do_map at xxxx" instead (as mentioned here).

- Link: https://github.com/pallets/jinja/blob/master/jinja2/sandbox.py

Cookiecutter is a command-line utility that creates projects from templates. There's a list of templates maintained by the cookiecutter team and plenty of community awesome lists. It's built with python and uses the jinja templating framework (found in python web frameworks like flask). You can use it to make a template for pretty much anything! All you need to get started is pip install cookiecutter.

This major release of Flask is accompanied by major releases of Werkzeug, Jinja2, click, and itsdangerous which we'd also welcome and appreciate testing (their pre releases are installed with the Flask pre release).