winget install --id=dagaza.Qube.Vulkan -e Qube is a fully local, privacy-first, voice-to-voice AI desktop assistant. It integrates speech-to-text, text-to-speech, retrieval-augmented generation, and local LLM inference into a native PyQt6 desktop shell. This package is the Vulkan GPU offload build for AMD and Intel GPUs. Install only one Qube variant; user data is shared across variants.
Your AI Model. Your Intelligence. Your Hardware. Complete Privacy & Sovereignty.
Grounded answers from your Library, memory, and trusted sources — with citations you can inspect.
Quick Start · Landing page · Website · Features · See it in action · Docs · Help · Support
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Qube is a native desktop AI assistant for privacy-sensitive work on your own hardware. Chat in text, ingest documents into a Library, let Qube distill long-term memory you can edit in Memory Manager, and pull Live Sources — scientific literature, filings, case law, and more — with numbered citations and per-turn INSPECT RETRIEVAL.
Inference stays local. Web and research tools run only when you ask. Help, settings tours, and troubleshooting live inside the app — Library → Qube, @[tool:help], and ? guided tours — not on a separate wiki.
Optional voice input, text-to-speech, and a Desktop Companion orb are available when you want hands-free turns; precision routing with @ composer tools and skills is richest from the main window with keyboard and mouse.
@ tools; weak retrieval is dropped instead of faked citations@research reports@help and ? tours on every major screenComposer & @ routing — Per-message control: @library, @file, @evidence, @finance, @legal, @research, @internet, @memory, @help, custom @[tool:user:…] presets, and @[skill:…] reasoning frameworks. The cognitive router handles everyday phrasing; attach @ when you want a specific pathway.
Library — A persistent document corpus: ingest PDFs, EPUBs, and text; search titles and indexed body text; preview from the vector index; Chat with document prefills @file. Shipped help lives in Library → Qube and is reachable via @help without mixing into your uploads.
Memory Manager — Long-term facts distilled from chat — preferences, projects, knowledge — with tier filters, edit/flag/delete, export, and a negative list so deleted memories stay gone.
Live Sources — Institutional adapters beyond generic web search: trusted/Wikipedia, scientific literature, SEC EDGAR, U.S. case law, page fetch, and multi-step @research reports (async, non-blocking). 58+ adapters with per-source toggles; build your own via My knowledge presets and Custom sources (REST, GraphQL, MCP, …).
Transparency — Advanced Telemetry (local hardware + routing stats), per-reply INSPECT RETRIEVAL, and Settings → Diagnostics / Settings → Privacy & data diagnostic logs with redaction options. Web discovery defaults to private search (DuckDuckGo + Wikipedia); point at your SearXNG when you want self-hosted SERP.
Model Manager — Search Hugging Face, browse curated picks, read model READMEs in-app, and download .gguf quantizations with disk-space guardrails. Run natively or point at an external server.
Built-in help — Full guides in Library → Qube, searchable with @[tool:help] from chat (same retrieval pipeline as your docs, separate scope). ? guided tours on every major screen.
Voice & Desktop Companion (optional) — Speech-to-text and TTS when voice models are installed; interrupt mid-sentence with barge-in. Optional floating orb for quick voice turns and glanceable status. Uncheck voice downloads at bootstrap if RAM is tight — chat and routing work fully without them.
| Library | Model Manager | Telemetry |
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> Before launch: capture a Desktop Companion orb screenshot for this section — see launch documentation guidelines Phase 4.
Get builds from GitHub Releases. For GPU acceleration with the built-in engine, pick the installer that matches your hardware (see below). Homebrew uses the CPU build by default; WinGet and Chocolatey also offer GPU packages.
| Platform | Install |
|---|---|
| Windows | CPU: winget install -e --id dagaza.Qube or choco install qube · GPU: winget install -e --id dagaza.Qube.Vulkan / choco install qube-vulkan (AMD/Intel) or dagaza.Qube.CUDA / qube-cuda (NVIDIA) · or download from Releases |
| macOS | brew tap dagaza/qube then brew install --cask qube · or download the .dmg (Apple Silicon or Intel) from GitHub Releases |
| Linux | AppImage, .deb, .rpm, or .tar.gz (amd64) — Install on Linux |
GPU build variants (Windows & Linux) — install one variant; all share user data in ~/.qube/ or %LOCALAPPDATA%\Qube:
| Variant | Best for |
|---|---|
| cpu | Any PC; slowest chat inference |
| vulkan | AMD / Intel GPU |
| cuda | NVIDIA GPU (recent driver) |
Windows package managers — same three variants on WinGet and Chocolatey:
| Variant | WinGet | Chocolatey | GitHub Releases installer |
|---|---|---|---|
| cpu | dagaza.Qube | qube | Qube--Setup.exe |
| vulkan | dagaza.Qube.Vulkan | qube-vulkan | Qube--vulkan-Setup.exe |
| cuda | dagaza.Qube.CUDA | qube-cuda | Qube--cuda-Setup.exe |
# CPU (works on any PC)
winget install -e --id dagaza.Qube
choco install qube -y
# Vulkan (AMD / Intel GPU)
winget install -e --id dagaza.Qube.Vulkan
choco install qube-vulkan -y
# CUDA (NVIDIA GPU — recent driver required)
winget install -e --id dagaza.Qube.CUDA
choco install qube-cuda -y
To upgrade, use the same ID as your installed variant (winget upgrade -e --id … or choco upgrade qube-vulkan -y, etc.). Switching GPU builds means installing the other package or running the matching .exe from Releases — see Update Qube.
macOS (Homebrew custom tap) — one cask, Metal GPU when available (no separate Vulkan/CUDA packages):
| Tap | dagaza/qube |
| Cask | qube |
| Releases | Qube--arm64.dmg (Apple Silicon) · Qube--x86_64.dmg (Intel) |
# One-time: add the custom tap
brew tap dagaza/qube
# Install (Homebrew picks arm64 or x86_64 automatically)
brew install --cask qube
# Or install without adding the tap permanently:
brew install --cask dagaza/qube/qube
To upgrade: brew upgrade --cask qube. Or download the matching .dmg from GitHub Releases and replace Qube.app in /Applications.
> Gatekeeper (unsigned DMG): On first launch, use System Settings → Privacy & Security → Open Anyway, or run:
>
> bash > xattr -dr com.apple.quarantine "/Applications/Qube.app" >
>
> See homebrew-qube.
Linux artifact examples: Qube--x86_64-vulkan.AppImage, qube-vulkan__amd64.deb, qube-vulkan--1.x86_64.rpm. Windows direct download: Qube--vulkan-Setup.exe, Qube--cuda-Setup.exe.
Maintainers: winget/README.md · chocolatey/README.md · homebrew/README.md
@library or @evidence when you want grounding, or press ? for a guided tour. Enable voice under Settings → Voice & Audio when you want hands-free input.> Tip: At 16 GB RAM, start with a small model (for example Nemotron 3 Nano 4B). See Settings → General → Discovery to enable hardware-fit suggestions in Model Manager.
See Install from source for clone, venv, GPU builds, and developer flags.
Quick start:
git clone https://github.com/dagaza/Qube.git && cd Qube
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt && python main.py
@[tool:library] / @[file:…]. Citations link back to source chunks.@ — Try @[tool:evidence] for papers, @[tool:finance] for SEC filings, or @[tool:research] for an async evidence report — or let the router infer from your wording.Qube ships with a full help library — no browser required.
@[tool:help] in chat and ask how to do something ("How do I set GPU layers?", "Memory vs Library?").Guided tours (? buttons) on each screen walk you through the layout step by step.
More workflows: How to use Qube.
| Minimum | Recommended | |
|---|---|---|
| RAM | 16 GB | 20 GB |
| OS | Windows 10+ (x64), macOS 12+ (Apple Silicon or Intel), Linux amd64 (AppImage / .deb / .rpm / .tar.gz, or source) | Same |
| Storage | ~2 GB for app + optional voice models; plan extra for each chat model; CUDA/Linux GPU builds are larger | SSD strongly recommended |
| Audio | Optional — microphone and speakers for voice features | Same |
| GPU | Optional — pick vulkan or cuda release builds on Windows/Linux, or Metal on macOS; CPU builds work everywhere | Discrete GPU or Apple Silicon with enough VRAM for your chosen model |
Full hardware guidance (models, GPU paths, storage): System requirements.
Qube uses a native PyQt6 desktop shell — not Electron and not a browser tab — so more of your 16 GB budget stays available for models and context. See System requirements for hardware guidance.
| Audience | Start here |
|---|---|
| Users | docs/user/ — install (Windows WinGet & Chocolatey GPU packages, Linux .rpm, Homebrew tap), requirements, workflows |
| In-app | Library → Qube or @[tool:help] (see Built-in help) |
| Contributors | docs/architecture/ — memory, pipeline, stack |
| Contributing | CONTRIBUTING.md — setup, tests, PRs |
| Launch doc playbook | docs/launch_documentation_guidelines.md — re-run before official launch |
| Landing page | dagaza.github.io/Qube · setup |
| Website | qubeapp.eu |
| Social preview | assets/social/qube-social-preview.png — upload in repo Settings |
| Release notes | CHANGELOG.md — what changed in each version |
The pre–launch rewrite README (453 lines of technical detail) is preserved at docs/archive/readme-pre-launch-rewrite.md.
What's new: v1.0.1 — first-run bootstrap, phased model downloads, WinGet first-launch fixes.
LM Studio excels at running and serving models; SillyTavern at prompt craft and character workflows; Odysseus at a broad self-hosted workspace. Qube targets a different job: a native desktop assistant with automatic routing to Library, memory, or live sources; @ composer control; an editable Memory Manager; and in-app help — with optional voice and a lean PyQt shell on tight RAM. Qube can use LM Studio or Ollama as its inference backend.
Qube is free, open-source software built with care. If it saves you time or helps you learn, consider supporting continued development:
Qube stands on the shoulders of excellent open-source projects:
Kokoro-82M · Faster-Whisper · Nomic Embed · LanceDB · PyMuPDF · OpenWakeWord · Hugging Face Hub · LM Studio · Ollama · PyQt6 · llama.cpp
Thank you to everyone who encouraged this project along the way.
This project is licensed under the MIT License. You may use, modify, and distribute it freely — including in commercial projects — as long as you include the original copyright notice. See LICENSE for details.
Clone, test, and contribute: CONTRIBUTING.md · Install from source · Architecture
