Knovum 0.0.2: Building an Open-Source Local-First AI Canvas with Tauri 2, Vue 3, and Rust

Like many developers and researchers, I've spent the past two years experimenting with local LLMs (via Ollama) and local RAG. But existing desktop frontends repeatedly hit two frustrating walls:

To solve this, we built Knovum — an open-source, local-first desktop AI knowledge workspace built on an infinite 2D canvas with Tauri 2, Rust, and Vue 3.

Today we just shipped v0.0.2, so I wanted to share the engineering decisions behind the architecture, what we learned building it, and what's new.

┌────────────────────────────────────────────────────────┐ │ Vue 3 Spatial Frontend │ │ (Konva Infinite 2D Canvas + JSON Canvas Specification) │ └───────────────────────────┬────────────────────────────┘ │ Tauri 2 IPC (Channels) ┌───────────────────────────▼────────────────────────────┐ │ Rust Backend Core │ │ ┌────────────────────┐ ┌────────────────────┐ │ │ │ SQLite Storage │ │ Embedded LanceDB │ │ │ │ (Notes, Boards, │ │ (In-Process Vector │ │ │ │ Numbered Migr.) │ │ Search Engine) │ │ │ └────────────────────┘ └────────────────────┘ │ │ ┌────────────────────┐ ┌────────────────────┐ │ │ │ Ollama API │ │ Embedded Whisper │ │ │ │ (Local LLM Router) │ │ (Speech-to-Text) │ │ │ └────────────────────┘ └────────────────────┘ │ └────────────────────────────────────────────────────────┘ Enter fullscreen mode Exit fullscreen mode 1. Why Tauri 2 + Vue 3? By leveraging native OS WebViews (WKWebView on macOS, WebView2 on Windows) orchestrated by a compiled Rust backend, Knovum cold-boots in sub-second time and idles around 45MB of RAM.

This leaves virtually all of your machine's physical memory dedicated to loading model weights.

Every visual workspace is stored directly on your local filesystem using the open JSON Canvas (.canvas ) specification. You can open, edit, and inspect any Knovum board directly in Obsidian Canvas or parse it with custom scripts.

Here are the key improvements shipped in our 0.0.2 release:

In traditional vector RAG setups, updating a document collection often triggers expensive full re-indexes. In 0.0.2:

Streaming LLM answers now respect clear block boundaries instead of erasing or slicing through previous turns. Concurrency is strictly owned by a single writer per execution run.

Knovum includes an on-device Whisper transcription engine. In 0.0.2, the voice library can be audited and heard before selection, and visualizes the active speaker in real time.

When an LLM synthesizes an insight from your notes, the citation anchors to exact sentence-level character spans in the source note. If you edit or mutate the source note later, the citation badge automatically flags that the source has evolved—preventing silent hallucination decay.

Knovum is 100% free and open-source under the Apache-2.0 license.

If you're interested in local-first software, spatial computing, or running LLMs on your own hardware, give the repository a ⭐ on GitHub and let us know your feedback!

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