Meera: A Fully Offline AI Assistant for Linux Gnome Built on Qwen3.5-2B

Meera is a local AI assistant for Linux Gnome Desktop that runs completely offline. Built by a hardware engineer new to software development, it uses Cursor (AI-assisted coding) and is designed to work on modest hardware. The installer sets up llama-cpp and downloads the model — no cloud dependency.

Key Architecture Details

• Primary model: Qwen3.5-2B-Q4_K_M (1.2 GB, ~2B params)
• Inference engine: llama-cpp with Vulkan backend (auto-detects GPU: Nvidia/AMD/Intel/iGPU)
• Tool selection: A second tiny embedding model shortlists closest tool matches and RAG chunks instead of embedding all tool schemas in the prompt — critical for reliability with small models
• Hardware tested: Ubuntu 24.04 + RTX 5090 (desktop), Fedora Silverblue + Intel i3 (laptop) — sufficiently fast on both

What Meera Can Do

Tool calls examples (from source):

• Add team meeting at 10 AM tomorrow to calendar
• Remind me to email someone in 30 minutes
• Volume, brightness, Wi-Fi control
• Switch to dark/light mode, turn night light on/off
• Search and open file "project_description" in Documents
• Check which processes use too much CPU
• Check for package updates

For new Linux users:

• Recommend software for a given task
• Explain grep/sed/awk usage
• Provide commands to compress/decompress zip/tar files

Repo Structure and Customization

The GitHub repo (currently only useful on Linux) provides an architecture documented in the wiki. Non-Linux users can repurpose the code — only the tools and rag_data directories need modification. The model can be swapped for a larger one.

GitHub: achinivar/meera

The author plans to add voice-to-text and text-to-speech next. Bugs and tool ideas are welcome via GitHub issues or comments.