Verba

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Verba is a fully offline, local-first AI-powered text-polishing utility built with Tauri v2, React, TypeScript, and Rust—with the flexible option to also connect to online LLM providers. It runs silently in your system tray, listens to a global hotkey, instantly captures selected text, polishes it locally or online, and pastes the refined text back to your focused application.

Important

100% Offline & Private: Verba runs completely offline using a built-in llama-completion sidecar powered by the Llama-3.2-1B-Instruct model—so your text never leaves your device. If you prefer, you can easily configure it to use online cloud providers (like OpenAI, Anthropic, Gemini, or Groq) in the Settings.

✨ Features

• Global Hotkey Activation: Quickly select any text, press the hotkey (default: Ctrl+Alt+P), and watch it load in the Verba popup.
• AI Text Polishing: Integrate with top-tier AI LLM providers to clean up grammar, tone, style, or translate text.
• Local Offline Inference: Run text polishing completely offline using the lightweight Llama-3.2-1B-Instruct model powered by a built-in llama-completion sidecar. No API keys or internet connection required!
• Local Model Downloader: In-app panel to trigger, track, and cancel model downloads from HuggingFace with live download speeds and progress indicators.
• Auto-Paste Back: Seamlessly writes polished text back to your clipboard and injects it back into your active window.
• Clipboard Preservation: Backs up and restores your pre-existing clipboard contents automatically, preventing pollution of your copy/paste queue.
• Keyboard Safety Validation: Dynamically detects physical keystrokes and waits for hotkey releases before executing Ctrl+C, preventing selection replacement bugs (e.g. typing a literal 'c' instead of copying).
• Anti-Clipping Window Layout: Custom container layouts with fine-tuned paddings and margins to prevent CSS box-shadow clipping issues on transparent overlays.
• System Tray Menu: Run the app in the background with a system tray menu allowing easy access to settings and application exit.
• Polishing History: Keep track of previously edited texts for easy reference and reuse.
• Secure Storage: Safe handling of API keys using system-native keyring storage via Rust.

🤖 Local Offline Inference Setup

Verba supports 100% local, offline text polishing. To use this feature:

1. Get the Executables: Download the llama-completion executables and dynamic libraries (.dll/.so/.dylib) from the llama.cpp releases.
2. Place Executables & DLLs:
   • For compilation and bundling, place a renamed binary llama-completion-<target-triple>.exe in the src-tauri/binaries directory.
   • For active development/runtime, place the dynamic libraries (llama.dll, ggml.dll, ggml-cpu-*.dll, etc.) and llama-completion.exe in the active build folder (e.g., src-tauri/target/debug or the production installation folder).
3. Download the Model: Launch Verba, go to Settings, select the Local provider, and click Download Model to fetch the 800MB Llama-3.2-1B-Instruct-Q4_K_M.gguf model file directly.
4. Trigger Polishing: Highlight any text, press your hotkey, select Generative (or any local prompt), and watch it polish instantly offline without calling any external APIs.

🍏 macOS Compatibility & Setup

Verba is fully compatible with macOS (both Apple Silicon/M1/M2/M3 and Intel chips). Follow these setup requirements:

1. Global Hotkey: The default global trigger hotkey on macOS is Cmd+Alt+P (compared to Ctrl+Alt+P on Windows).
2. Accessibility Permissions:
   • Because Verba simulates key presses (Cmd+C and Cmd+V) via AppleScript to capture and paste text automatically, macOS requires Accessibility Permissions.
   • Upon first trigger, macOS will prompt you. Go to System Settings -> Privacy & Security -> Accessibility and ensure Verba is checked/enabled.
   • If keystroke emulation fails to paste, toggle the permission off and back on.
3. Local Offline Inference Setup (macOS):
   • For compilation and bundling, copy the relevant llama-completion executable from the target macOS directory (llama-macos-arm64 or llama-macos-x64) into src-tauri/binaries/ with the corresponding target triple:
     • Apple Silicon (M1/M2/M3/M4): llama-completion-aarch64-apple-darwin
     • Intel Macs: llama-completion-x86_64-apple-darwin
   • Make sure you also copy the required dynamic libraries (e.g. libllama-*.dylib, libggml-*.dylib, etc.) to the same directory or system library paths as needed if running from compiled source.

🛠️ Tech Stack

• Desktop Framework: Tauri v2 (Rust backend)
• Local LLM Engine: llama.cpp via llama-completion sidecar
• Frontend library: React with Vite
• Programming Languages: Rust (Core Logic), TypeScript (UI & Application orchestration)
• Security: System Keychain (keyring-rs) for API key protection

🚀 Quick Start

Prerequisites

Ensure you have the following installed on your local machine:

1. Rust & Cargo: Follow instructions at rustup.rs.
2. Node.js & npm: Install via nodejs.org.
3. Tauri Prerequisites: Depending on your OS, install necessary dependencies listed in the Tauri Getting Started Guide.

Development Setup

1. Clone the repository:

   git clone https://github.com/RhythmicDias/Verba.git
   cd Verba

2. Install node dependencies:

   npm install

3. Run in development mode:

   npm run tauri dev

Production Build

To build a standalone production-ready package:

npm run tauri build

📜 License

Distributed under the MIT License. See LICENSE for more information.