this website is entirely written with Claude Code, and I also used three agents (markdown file) to help: landing-page-creator.md, nextjs-test-analyzer.md, seo-article-writer.md

if you find any mistake, please let me know

Wait is Claude writing the articles, then?

I felt there should be a CV maker that’s both easy to use and truly works, so I just built one. It’s simple, effective, and completely free.

Thx, fixed now.

It does, but I used Flask previously for comparison, so I came to that conclusion.

It seems like you've already proved your conclusion false though if you ended up using an HTTP server anyway. The conclusion seems to be that Flask wasn't suitable for the task.

You are right, the conclusion should be revised to: "I ended up using an HTTP server anyway, but I choosed the more efficient one", because Flask's http server is for testing only. Sorry for the unclear. I think using a Unix Socket could be more efficient but I don't want to be over-engineering :)

Sorry for that, could you please provide screenshots or description in here: https://drawingpics.canny.io/feedback So that I can investigate the issue

This idea is really cool, I'll try :)

The Controlnets model is too large(maybe 2GB? extra download), which means it requires more memory. The line control model that I used in drawingpics is about 300MB, which is suitable for light users

Krita is a great drawing app, but the Krita SD plugin is not easy to set up.

I think DrawingPics installation is more friendly, I wrote a blog about it https://docs.drawing.pics/index/getting-started/drawingpics-...

To setup the Krita SD plugin, literally all you have to do is download it and import it into Krita. It installs the backend all by itself.

Hi, I found the Krita SD plugin docs here: https://www.interstice.cloud/plugin

It seems it needs Docker to be installed? It might consume more power than running in a local Python environment.

By the way, the plugin is great.

that's "dockers" as in a "panel in the Krita interface" (which is somewhat modular), not Docker as in "Docker the container environment"

I'm developing a StableDiffusion client that runs entirely locally and benefits from LCM LoRA. I use an old MacBookAir M1, It took about 7s to process 1 image, but I think it's acceptable since it doesn't require an expensive GPU. Is there anyone intersted in early access?

you can fill in this form for free early access: https://forms.gle/dwwouGndRyESnLj29