Browser FZF Search

Version: 1.1.0 | License: MIT

Browser FZF Search is an AI-powered Chrome extension that enhances web and PDF search capabilities directly in your browser. Leveraging local machine learning with TensorFlow.js and pre-trained GloVe embeddings, it provides fast, privacy-preserving semantic, exact, and fuzzy search functionality without relying on external servers.

✨ Features

• Multi-Mode Search: Choose between semantic (meaning-based), exact (literal), or fuzzy (approximate) search modes
• Web & PDF Support: Seamlessly search across HTML pages and PDFs with a custom viewer
• Local Processing: All computation runs client-side using TensorFlow.js with WebGL acceleration
• Efficient Highlighting: Matches are visually highlighted with navigation controls for next/previous results
• Keyboard Shortcuts: Trigger the popup with Ctrl+Shift+S (or Cmd+Shift+S on Mac) and navigate matches with Enter/Shift+Enter
• Rate Limiting: Built-in token bucket rate limiter ensures performance stability

🚀 Installation

1. Clone the Repository

   git clone https://github.com/zachkepe/browser-fzf.git

2. Install Dependencies

   cd browser-fzf && npm install

3. Build the Extension

   npm run build

4. Load into Chrome

   • Open Chrome and navigate to chrome://extensions/
   • Enable "Developer mode" in the top right
   • Click "Load unpacked" and select the dist/ folder from the project root

📝 Usage

• Open the Popup: Use Ctrl+Shift+S (or Cmd+Shift+S on Mac) to launch the search interface
• Search Modes: Select from "Semantic," "Exact," or "Fuzzy" via the dropdown
• Navigate Results: Use the up/down arrow buttons or Enter/Shift+Enter to cycle through matches
• PDF Viewing: Automatically intercepts .pdf URLs and renders them in a searchable viewer

🎮 Demonstration

Below are visual examples of the extension in action.

Search Popup Interface

The search popup with mode selection and match navigation.

Highlighting Matches on a Web Page/PDF

Highlighting matches on a webpage/PDF with real-time updates.

🔧 Technical Overview

• Architecture: Built as a Chrome Manifest V3 extension with a service worker background script, content scripts, and a popup UI
• Machine Learning: Utilizes TensorFlow.js with pre-trained GloVe 6B 50D embeddings (15,000-word vocabulary) for semantic search
• Dependencies:
  • @tensorflow/tfjs: Core ML framework with WebGL backend
  • fuse.js: Fuzzy search implementation
  • pdfjs-dist: PDF rendering and text extraction
• Build Tooling: Webpack with Babel for module bundling and ES6+ compatibility

💻 Development

• Dev Mode: npm run dev (watches for changes and rebuilds)
• Clean Build: npm run clean && npm run build
• Embedding Generation: Run node scripts/generate-embeddings.js to regenerate embeddings.json from glove.6B.50d.txt (optional, pre-built file included)

🤝 Contributing

Contributions are welcome! Please:

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

📄 License

This project is licensed under the MIT License. See LICENSE for details.

📞 Contact

For issues or inquiries, please file a ticket on the GitHub Issues page or contact Zach Kepe directly.