Phokus

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

Features

Library

• Add and remove media folders; background indexing with live progress
• Live file tracking — a filesystem watcher keeps the library in sync as files are added, changed, or removed; renames and moves are handled in place, preserving thumbnails and embeddings
• Browse all media or filter by folder, type (image/video), favorites, or star rating
• Sort by date added, date taken (EXIF), name, size, rating, or duration
• Grid density controls (compact / comfortable / detail)
• Desktop notifications, batched per folder, with per-folder mute and a global pause

Search & discovery

• Filename search, semantic search (/s query), and tag search (/t tag)
• Similar image search — find visually similar media by image or a selected region
• Explore view — visual cluster map and tag cloud for browsing by theme
• Timeline view — media grouped chronologically by capture date (EXIF)
• Duplicate finder — three-phase exact-duplicate scan (size → sample hash → full hash) with live progress and bulk delete
• Explore, Timeline, and Duplicates are folder-scopable directly from their headers — no need to bounce through the sidebar

Viewing & curation

• Lightbox with keyboard navigation, zoom, inline tag editing, and rating controls
• Custom video player — immersive edge-to-edge playback with scrubbing, volume, playback speed, loop, and fullscreen; auto-hiding controls and full keyboard support
• AI tagging via WD tagger (ONNX, CPU/DirectML) with confidence threshold, batch size, and per-folder queue targeting

Maintenance

• Database compaction and orphaned-thumbnail cleanup from Settings, with live size/reclaimable stats
• Per-folder pausing of background work (thumbnails, metadata, embeddings, tagging)

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) + HNSW index
• ONNX Runtime (ort) for AI tagging
• Candle (Rust ML) for CLIP visual embeddings
• mozjpeg for fast scaled JPEG decoding
• 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

# Type-check the frontend
pnpm build:vite

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, EXIF capture date, etc.).
3. Background workers process the queue as a strict priority pipeline — thumbnails first, then video metadata, then visual embeddings, then AI tags — so each stage runs at full speed instead of competing for CPU, disk, and the database.
4. Progress events stream back to the UI while the gallery updates incrementally.
5. A filesystem watcher picks up later changes (new files, edits, deletions, renames) and keeps the index current without rescans.
6. Embeddings power semantic search and the similar-images feature via an HNSW index.