From what I can tell, CyberChef is a more comprehensive and well-established project. Of course, there are many projects like this. I wanted to work on a project like this because I thought it would be a good fit for Vibecoding. It would also be a good opportunity to try out Tauri and other tools.
Really cool project! Tauri is fantastic for keeping the memory footprint small compared to Electron.
You mentioned 'Vibecoding' and building this to get used to AI coding tools. I'm curious: which parts of the Tauri/Rust boundary were the hardest for the AI to get right? In my experience, LLMs are great at the frontend JS/React, but sometimes hallucinate bad IPC (Inter-Process Communication) calls when talking to the Rust backend. Did you run into that issue?
I definitely agree with what you said about Tauri. Tauri’s performance surprised me.
As for what you said, to be honest, this project was just a starting point for me in terms of getting to know Tauri. So, in the context of this project, I’d say Tauri was more of a shell designed to deliver the application natively, rather than a tool where I fully utilized all its capabilities. In that regard, I didn’t encounter the kind of issue you mentioned. I mostly noticed that the AI initially struggled with window control and couldn’t grasp the situation. In short, when it came to ACL, I had to identify the problem and guide it. The AI had written reasonable window control code but had overlooked what to do regarding permissions.
Nice! Reminds me a little of https://github.com/gchq/CyberChef
From what I can tell, CyberChef is a more comprehensive and well-established project. Of course, there are many projects like this. I wanted to work on a project like this because I thought it would be a good fit for Vibecoding. It would also be a good opportunity to try out Tauri and other tools.
Really cool project! Tauri is fantastic for keeping the memory footprint small compared to Electron. You mentioned 'Vibecoding' and building this to get used to AI coding tools. I'm curious: which parts of the Tauri/Rust boundary were the hardest for the AI to get right? In my experience, LLMs are great at the frontend JS/React, but sometimes hallucinate bad IPC (Inter-Process Communication) calls when talking to the Rust backend. Did you run into that issue?
I definitely agree with what you said about Tauri. Tauri’s performance surprised me.
As for what you said, to be honest, this project was just a starting point for me in terms of getting to know Tauri. So, in the context of this project, I’d say Tauri was more of a shell designed to deliver the application natively, rather than a tool where I fully utilized all its capabilities. In that regard, I didn’t encounter the kind of issue you mentioned. I mostly noticed that the AI initially struggled with window control and couldn’t grasp the situation. In short, when it came to ACL, I had to identify the problem and guide it. The AI had written reasonable window control code but had overlooked what to do regarding permissions.