AI-Powered Bookmark Manager for Modern Browsers

Product Introduction • Usage • 中文文档 • 使用文档 • Features • Development • Contributing

HamHome is an AI-powered bookmark manager for modern browsers. It uses AI to automatically categorize saved pages, generate summaries, and suggest tags. It also supports semantic search for your bookmarks while keeping your data local and private.

👉 View Product Introduction - Learn more about features and capabilities

Side Panel	Save Panel
Semantic Search	Preset Categories
Management Page	Settings Page

• Auto-categorization based on page content
• Smart tag suggestions with configurable presets
• AI-generated summaries for quick reference
• BYOK (Bring Your Own Key) support for OpenAI, Anthropic, Claude, Ollama, and custom endpoints

• Support synchronization via WebDAV (e.g., Nextcloud, InfiniCLOUD, etc.)
• End-to-end encrypted or plain data sync options
• Real-time sync status widget in the header
• Granular control over remote data (clear remote data anytime)

• Icon Support: Add emoji icons to your categories for better visual identification.
• Preset Schemes: Two built-in category templates—"General" and "Professional Creator"—with one-click import
• AI-Generated Categories: Describe your use case and let AI create a tailored category structure
• Unlimited hierarchical category tree

• Save complete HTML snapshots locally (IndexedDB)
• Access content even when the original page goes offline
• Powered by Mozilla Readability for clean extraction

• Full-text search across titles, descriptions, and content
• Semantic search (vector-based)
• Filter by category, tags, and time range
• Create custom filter presets for complex queries

• Local-First: All data stored locally in Chrome Storage + IndexedDB
• Granular Storage Management: View and manage space used by bookmarks, snapshots, and vector data separately.
• Selective Deletion: Delete specific data types (e.g., only snapshots) while keeping your categories and configurations.
• Privacy Domains: Configure domains to exclude sensitive sites from AI analysis

• Grid (masonry) and list view modes
• Light/dark theme with system preference detection
• Full i18n support (English & Chinese)
• Keyboard shortcuts and edge-trigger panel

• Chrome Web Store
• Firefox Add-ons
• Microsoft Edge Addons
• See releases to download and install manually.

# Clone the repository
git clone https://github.com/bingoYB/ham_home.git
cd ham_home

# Install dependencies (requires pnpm)
pnpm install

# Build for Chrome/Edge
pnpm --filter extension build

# Build for Firefox
pnpm --filter extension build:firefox

• Chrome/Edge: Navigate to chrome://extensions/, enable "Developer mode", click "Load unpacked", and select apps/extension/.output/chrome-mv3
• Firefox: Go to about:debugging, click "This Firefox", click "Load Temporary Add-on", and select apps/extension/.output/firefox-mv2/manifest.json

# Start dev server (Chrome)
pnpm --filter extension dev

# Start dev server (Firefox)
pnpm --filter extension dev:firefox

# Build all browser variants
pnpm --filter extension build:all

• Framework: WXT (Vite-based extension framework)
• UI: React 19 + TypeScript + Tailwind CSS
• Components: shadcn/ui
• Content Extraction: Mozilla Readability + Turndown
• i18n: i18next + react-i18next
• Storage: Chrome Storage API + IndexedDB

ham_home/
├── apps/
│   └── extension/          # Browser extension
│       ├── components/     # React components
│       ├── hooks/          # Custom hooks
│       ├── lib/            # Core libraries (AI, storage, i18n)
│       ├── entrypoints/    # Extension entry points
│       └── locales/        # i18n resources
├── packages/
│   ├── ui/                 # Shared UI components
│   ├── types/              # Shared TypeScript types
│   └── ...                 # Other shared packages
└── docs/                   # Documentation

Contributions are welcome! Please:

1. Fork this repository
2. Create a feature branch (git checkout -b feature/your-feature)
3. Commit your changes (git commit -m 'Add your feature')
4. Push to the branch (git push origin feature/your-feature)
5. Open a Pull Request

MIT

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