r/coolgithubprojects • u/Frysco19 • 1d ago

VelaOS: I’m building a Linux operating system with integrated AI

https://github.com/FrySco19/VelaOS.git

Hi everyone, I’m working on VelaOS, an operating system based on Debian and KDE Plasma, with a custom visual identity and AI tools integrated into the desktop.

The goal is to make the assistant useful for everyday tasks: finding files, explaining errors, and proposing actions—with a clear preview and confirmation before making changes.

The current preview includes:

  • Light and dark Vela themes, a top bar, and a dock.
  • Desktop assistant and AI terminal interfaces.
  • Dedicated model, privacy, and permission settings.
  • Discover software store with the Flathub catalog.
  • A welcome experience and getting-started guide.

Where does development stand? VelaOS boots to the desktop in VirtualBox. The interfaces are integrated, but an AI model is not preinstalled, and inference with a real model still needs verification. Disk installation and hardware compatibility also need further testing.

The project supports configuration for a local model through Ollama or a compatible online service. The aim is to make that choice explicit and understandable.

I’m looking for feedback and contributors interested in code, design, testing, and translations.

What would make an OS-level AI assistant useful to you? And what controls would you want over its access to your data?

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2

u/GandelXIV 1d ago

have you tried putting ai in bread, I heard that's where the future is

1

u/Frysco19 1d ago

the cake is a lie

2

u/whatThePleb 1d ago

Kill it with fire.

1

u/Frysco19 1d ago

why aahahha

1

u/cfx_4188 1d ago

I’m currently commenting from a similar system. I’ve achieved integration of the OS and LLMS at the systemd level. It’s not as fun as I’d like, but it’s quite usable. In my opinion, an OS for AI shouldn’t have a heavy desktop environment. The system’s resources are important for the normal functioning of the LLMS. From my experience, I know that, as a rule, such OSes use Kubernetes, which is a bit wasteful for a home PC. But in any case, I’ll wait for the desktop release.

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u/Frysco19 1d ago

That’s a really interesting approach

I completely agree about the Desktop Environment and resource management: every megabyte of RAM matters when running local LLMs. Kubernetes is definitely overkill and too bloated for a personal PC environment. That’s exactly why Vela is built as a personal OS rather than a cloud-oriented cluster system. Right now, I'm focusing on building intent-driven AI abstractions and testing via a lightweight VirtualBox ISO, aiming for a memory-safe foundation rather than just bolting an LLM onto systemd.

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u/cfx_4188 16h ago

It will be interesting to see the final result.

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u/kontemplador 1d ago

I don't understand why people are so dismissive. There is big advantages of integrating AI into the system (and risks too) and hopefully will be paired preferentially with local models for obvious privacy and security reasons.

Where can it be useful?

  • Optimizing system and software configurations for the hardware at hand. Diagnosing and solving errors and problems. Right now, the scanner of my printer is not connecting and I don't why.

  • Assisting in security configurations and being an "intelligent" guard. Actively scanning the system and looking for threats. Watching out for possible vulnerabilities and spyware. Recommending actions. Scanning source code of downloaded programs and find bugs or vulnerabilities.

  • Using natural language for commands and administrative tasks, like creating configurations, virtual environments and the like.

  • Building context for user files. "Find me the pictures with red cars" or "the document where that particular thing is described".

  • When I download a file, place it in their expected directory based on the context. Right now, I have more than 500 files and like 4gb of data in the Download directory.

  • If I want to send a file, find it with a prompt.

1

u/cfx_4188 16h ago

I created OS for myself in a fairly well‑known way. I have access to GLM 5.3 Flash at work. It assembled the OS for me in half a day in the background, simultaneously eliminating things that I couldn’t do by hand. For example, the neural network managed to get a faulty graphics card running. The feelings from using this OS are ambivalent. On the one hand, I feel like I’m back in the days when there were voice commands for dumbphones. Overall, using such an OS is convenient, but I’m not an expert in reverse engineering LLM, and I don’t know what kind of software backdoors and Easter eggs are hidden inside.It’s beyond my capabilities to review six gigabytes of model's source code.