LyAhn ae3d6e1034 fix(search): close three P2 correctness gaps from code review
- vector: increment embedding_revision whenever delete_embedding is
  called so the HNSW cache is invalidated after image/folder deletions,
  not just after inserts

- hnsw_index: fix race in build_index — read the revision before
  fetching embeddings and again after the parallel_insert; retry the
  whole build if the revision advanced during construction, ensuring
  the cached index always reflects a consistent snapshot

- commands: replace the fixed 4× over-fetch in semantic_search_images
  with a progressive doubling loop; start at exactly `limit` candidates
  and double the batch (capped at 8192) until the page is filled or the
  vector table is exhausted, preventing both under- and over-fetching
2026-06-07 22:46:05 +01:00
2026-04-05 19:12:48 +01:00

Phokus

A local-first desktop media library for browsing, filtering, and curating image and video folders.

Features

  • Add and remove media folders; background indexing with live progress
  • Browse all media or filter by folder, type (image/video), favorites, or star rating
  • Filename search, semantic search (/s query), and tag search (/t tag)
  • Similar image search — find visually similar media by image or selected region
  • AI tagging via WD tagger (ONNX, CPU/DirectML) with confidence threshold control
  • Explore view — visual cluster map and tag cloud for browsing by theme
  • Duplicate finder — scan for exact duplicates by file hash with bulk delete
  • Lightbox preview with keyboard navigation, inline tag editing, and rating controls
  • Sort by date, name, size, rating, or duration
  • Grid density controls (compact / comfortable / detail)

Supported formats

Images Videos
jpg, jpeg, png, gif, bmp mp4, mov, m4v
tiff, tif, webp, avif, heic, heif webm

Stack

  • Tauri 2 + Rust backend
  • React 19 + TypeScript + Zustand
  • SQLite + sqlite-vec (vector search)
  • ONNX Runtime (ort) for AI tagging
  • Candle (Rust ML) for visual embeddings
  • FFmpeg sidecar for video thumbnails and metadata
  • Vite + Tailwind CSS v4

Development

Prerequisites: Node.js 20+, pnpm, Rust toolchain, Tauri system prerequisites for Windows.

pnpm install

# Run with hot-reload (frontend + Rust)
pnpm dev:app

# Frontend only
pnpm dev:vite

# Production build
pnpm build:app

How it works

  1. Add a folder from the sidebar — the Rust indexer walks it recursively.
  2. Supported files are written to SQLite with metadata (path, dimensions, media type, etc.).
  3. Background workers generate thumbnails, compute visual embeddings, and run AI tagging.
  4. Progress events stream back to the UI while the gallery updates incrementally.
  5. Embeddings power semantic search and the similar images feature via an HNSW index.
S
Description
Local-first image gallery with semantic search and AI tagging (Tauri + React + Rust)
Readme MIT 14 MiB
Languages
TypeScript 60.4%
Rust 37.5%
CSS 1.3%
Shell 0.4%
JavaScript 0.2%
Other 0.2%