scrypt VS marked

Check out the scrypt encryption tool.

Given that the encryption algorithm is open source (https://github.com/Tarsnap/scrypt) can you try to explain what you mean here?

I wouldn't use OpenSSL personally. If you just need simple but secure symmetric encryption, checkout the scrypt(1) encryption utility from Tarsnap. If you need support for public keys, check out age(1).

scrypt if you strictly only need symmetric encryption.

^ "scrypt page on the Tarsnap website". Retrieved 21 January 2014.

First of all I know that "implementing your own cryptography is bad". However, at some point, one does stumble upon a use-case that is not (well) covered by existing tools.

Now, assuming one has already done his due-diligence and has read (and hopefully understood at least the main ideas of) cryptography related articles / posts / etc. (especially in the area pertaining to what one wants to build), and thus we can assume one is not a complete newbie in this mater, however, nor is he an expert. Basically we can assume he is an "amateur".

Where would one go with his design to ask for feedback about it, in the hope to at least eliminate some weaknesses that one (as a non expert) might have overlooked. (I'm not speaking here about "proofs" or "audits".)

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More specifically ---- but please let's not get into this right now, this being just an example ---- I'm trying to implement something similar to `scrypt` (the encryption utility, that uses the `scrypt` PBKDF, ) or `age` (), as a replacement to my current solution that relies on GnuPG.

It entirely does and that's exactly my point. Most "hashes" are designed to be fast, for data validation/checking whatever. For securing data (passwords, anonymisation, etc) you want a "hash" to be as slow as possible. Scrypt for example is designed to be extremely slow and use much memory (making GPU-based parallelisation useless and driving up the cost of CPU-based work). The default settings for five-second hashes changes their 18 hour estimate to a bit over two years... and that's assuming you don't turn it up further.

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.