A robust, high-performance desktop asset manager designed specifically for the AI image generation ecosystem. It unifies metadata parsing across fragmented formats, providing SQL-backed search, Smart Collections, live folder monitoring, and AI-powered interrogation in a modern, multi-themed desktop interface.
Unified grid gallery with instant SQLite search and dynamic metadata parsing.
Speed Sorter: Rapidly categorize massive generation dumps using keyboard hotkeys.
Image Comparator: Pixel-peep fine details between two generations with the draggable slider.
View More Features (Collections, Duplicate Detective & Custom Themes)
Smart Collections: Create dynamic, auto-populating folders based on complex metadata filters.
Duplicate Detective: Identify and manage identical or similar generations across your entire library.
Choose between Deep Neon, Clean Light, and Dark Premium themes to suit your workspace.
Designed for the privacy-conscious artist, this application operates on a strictly "Local-First" philosophy.
- Standalone Desktop App: Runs as a single
.exe(Windows),.AppImage(Linux), or.dmg(macOS). No installer required. - Bundled Runtime: Includes a self-contained Java 21 environment. No system-wide Java installation is required.
- Portable Data: All data (database, thumbnails, settings) is stored in a local
data/folder next to the executable (or in a standard user data location on macOS), making it easy to backup or move. - 100% Offline / No Telemetry: There are no "cloud sync" features, analytics, or background API calls. Your prompts and generation data never leave your machine.
- Privacy Scrubbing: Integrated Scrubber View allows you to sanitize images before sharing. It strips hidden generation metadata (Prompts, ComfyUI Workflows, Seed data) while preserving visual quality.
- Universal Metadata Engine: Advanced parsing strategies for the entire stable diffusion ecosystem.
- ComfyUI: Traverses complex node graphs (recursive inputs) and API formats to identify the true Sampler, Scheduler, and LoRAs used.
- Automatic1111 / Forge: Robust parsing of standard "Steps: XX, Sampler: XX" text blocks.
- Others: Native support for InvokeAI, SwarmUI, and NovelAI.
- Note: Metadata extraction requires images to contain embedded EXIF or PNG text chunks (standard for most AI generators).
- AI Auto-Tagger: Integrated WD14 ONNX model for local image interrogation. Automatically generate descriptive tags for your library without external API calls.
- Library Management:
- Smart Collections: Create dynamic collections based on metadata filters (e.g., "All images using Flux model with > 4 stars").
- Visual Previews: Collections feature a 3D-stacked image preview for immediate visual context.
- Pinned Folders: Bookmark frequently accessed directories for rapid navigation.
- Star Ratings: Rate images (1-5 stars) with instant filtering.
- Speed Sorting: A dedicated mode for processing high-volume generation batches.
- Hotkeys: Instantly move images to configurable target folders using numeric keys (1-5).
- Recycle Bin: Safely move unwanted results to the OS trash (Recycle Bin/Trash).
- Performance:
- FTS5 Search: Powered by SQLite's Full-Text Search for near-instant results across tens of thousands of images.
- Virtualization: Uses virtual scrolling to handle massive folders without UI lag.
- Project Loom: Leverages Java 21 Virtual Threads for non-blocking background indexing.
- Modern UX & Customization:
- Multi-Theme System: Choose between Deep Neon Cinematic, Minimalist Light, and Dark Gold themes.
- Image Comparator: Side-by-side comparison tool with a draggable slider.
- OS: Windows 10/11 (64-bit), Linux (AppImage), or macOS (11+).
- Memory:
- Minimum: 4GB RAM.
- Recommended: 8GB+ RAM (especially when using the AI Auto-Tagger).
- Storage: ~300MB for the application + additional space for the WD14 AI model (~300MB) and thumbnail cache.
- GPU: Not required. AI interrogation runs efficiently on the CPU via ONNX Runtime.
The application is built as a hybrid desktop application combining a Spring Boot backend with a Vue.js frontend, packaged via Electron.
-
Backend (Java 21 + Spring Boot 3.3):
- SQLite + FTS5: High-performance local indexing and relational storage.
- Virtual Threads: Optimized for heavy I/O tasks (file scanning and metadata extraction).
- ONNX Runtime: Local execution of AI models with automated native resource management and idle-eviction.
- Flyway: Automated database schema migrations.
-
Frontend (Vue 3 + PrimeVue):
- Pinia: Centralized state management for the image library and UI state.
- PrimeVue: Premium UI component library with custom glassmorphism overrides.
- Vite: Modern build pipeline for the frontend assets.
-
Desktop (Electron):
- Process Management: Automatically spawns and terminates the Spring Boot backend.
- Native Integration: Provides access to native folder selection dialogs and OS file explorer.
- Cross-Platform: Builds for Windows, Linux, and macOS using GitHub Actions.
- Download the appropriate file for your OS:
- Windows:
Latent Library Setup X.X.X.exe - Linux:
Latent Library-X.X.X.AppImage(mark as executable withchmod +x) - macOS:
Latent Library-X.X.X.dmg
- Windows:
- Run the application. No installation is required.
- Select a Folder containing your AI-generated images to start indexing.
🍎 macOS Users: Because this app is not yet signed with an Apple Developer Certificate, you may see an error saying the app is "damaged and can't be opened." This is a standard macOS security message for unsigned apps.
To fix this:
- Move the app to your Applications folder.
- Open Terminal.
- Run the following command to clear the quarantine attribute:
sudo xattr -cr "/Applications/Latent Library.app"- You can now open the app normally.
Distributed under the MIT License. Free for personal and commercial use.
If Latent Library has streamlined your workflow, consider supporting its ongoing development.
Developed by
Copyright (c) 2026 Alexander Nilsson
