Can I vibecode Heptabase?

Build a usable personal replacement for the core loop of Heptabase.
Use exactly this stack: Tauri 2 + React + TypeScript + SQLite.
Primary job: Build a local-first visual knowledge mapping app with fast capture, full-text search, backlinks, tags, and Markdown export.
Start from an empty folder and create the complete working project.

Functional Requirements:
- Whiteboard Interface: Create an infinite canvas where users can double-click to create markdown note cards. Cards can be moved, resized, and visually connected with lines/arrows.
- Note Editor: Implement a robust block-based or markdown text editor inside each card supporting headers, lists, code blocks, and embedded images.
- Knowledge Graph: Automatically generate bi-directional backlinks when a user links one card to another using [[wiki-links]]. Provide a "graph view" showing how tags and notes intersect.
- Sidebar & Search: A collapsible left sidebar for quick capture (journals/daily notes) and an omnibar (Cmd/Ctrl+K) for instant full-text search across all notes.

Architecture & State:
- Make the default mode single-user and private.
- Store user data locally in SQLite. File blobs (images) should be saved to the local file system.
- Do not add analytics, telemetry, ads, or third-party accounts.
- Put every secret and external credential in .env and provide .env.example.

UI/UX & States:
- Implement the smallest polished interface that completes the core loop end to end. The UI must feel native and performant even with hundreds of cards on the canvas.
- Include clear empty, loading, validation, success, and failure states.
- Use accessible keyboard navigation, labels, focus states, and sensible contrast. Smooth zooming and panning are critical.

Security & Constraints:
- Validate untrusted input and never log secrets or private file contents.
- Deliberately exclude these paid-product advantages: conflict-safe multi-device sync; mature importers and exporters; collaborative editing and sharing.
- Do not fake integrations, network effects, proprietary data, model quality, compliance, or security claims.

Testing & DevOps:
- Write focused unit tests for the data model, link parsing, and search indexing.
- Add one end-to-end smoke test that proves the core loop works.
- Create a README with setup, permissions, architecture, data location, backup, and limitations.
- Add scripts for install, development, test, build, and a production-style local run.
- Run the tests and build before finishing, then fix errors rather than merely describing them.