sweet! I sent you the invite.
Currently, SSH key management is not supported, but it would probably be possible to implement the SSH agent protocol in the Rust part of the application. I see that russh has a SSH agent server implementation. Let me know if you are interested in contributing such a feature - I am currently working on exposing all the custom entry fields in the UI, so the project ~~would almost be ready.~~ edit: would be ready to add that feature now
thanks for your interest! I have sent you a response with an invite link.
Since it doesn't come installed by default on a fresh system, my guess would be that you won't break anything fundamental, but this is pure speculation.
The mirrorlist is a configuration file listing servers that updates can get pulled in from.
When a package update is installed that contains a configuration file, it will not overwrite the old file but be installed with a pacnew extension so that you can merge the files (like you did). It will keep complaining at you until you remove the pacnew file, which is fine to do after you have merged successfully.
The graphical issues are probably due to something else that happened during the update.
Thanks for the comment. I have had exposure to similar claims, but wasn't seeing anyone using AMD GPUs for AI unless they were somehow incentivized by AMD, which made me suspicious.
In principle, more competition in the AI hardware market would be amazing, and Nvidia GPUs do feel overpriced, but I personally don't want to deal with the struggles of early adoption.
For inference (running previously-trained models that need lots of RAM), the desktop could be useful, but I would be surprised if training anything bigger than toy examples on this hardware would make sense because I expect compute performance to be limited.
Does anyone here have practical recent experience with ROCm and how it compares with the far-more-dominant CUDA? I would imagine that compatibility is much better now that most models are using PyTorch and that is supported, but what is the performance compared to a dedicated Nvidia GPU?
Lucky for you, the post contains an animated JPEG showing the change over time. Lemmy clients that don't support playback will only show a static image
This will work in general. One point of improvement: right now, if the request fails, the panic will cause your whole program to crash. You could change your function to return a Result<Html, SomeErrorType> instead, and handle errors more gracefully in the place where your function is called (e.g. ignoring pages that returned an error and continuing with the rest).
Look into anyhow for an easy to use error handling crate, allowing you to return an anyhow::Result<Html>
12.5/8=1.5625, so the Euro price went up by 56.25%
What I am doing is to create a
omnikee-libcrate within the project that will get compiled to WASM, not just plainkeepass, because I need additional adapter methods to interface with the web part of the application. I don't have the bandwidth to turnkeepassinto a general WASM package that could benpm installed at the moment. As I am dogfooding the crate, I might get to a point where I know what a good JS interface for it would be, though, and theomnikee-libcrate could become the official WASM interface forkeepass.