BrowserAI enables running production-ready Large Language Models (LLMs) directly within the user's web browser, offering a private, fast, and zero-server-cost solution. It targets web developers building AI applications, companies requiring privacy-conscious AI, researchers, and hobbyists. The primary benefit is leveraging powerful AI models locally without complex infrastructure or data privacy concerns.

How It Works

BrowserAI utilizes WebGPU for hardware-accelerated inference, achieving near-native performance for LLMs. It supports both the MLC and Transformers.js engines, allowing seamless switching between them and offering pre-optimized popular models. This approach democratizes AI deployment by eliminating server costs and enabling offline capabilities after initial model download.

Quick Start & Requirements

• Install via npm: npm install @browserai/browserai or yarn: yarn add @browserai/browserai.
• Requires a modern browser with WebGPU support (Chrome 113+, Edge 113+, or equivalents).
• Hardware must support 16-bit floating-point operations for models with f16 requirements.
• Documentation
• Live Demo

Highlighted Details

• 100% private processing occurs locally in the browser.
• WebGPU acceleration provides high inference speeds.
• Supports seamless switching between MLC and Transformers engines.
• Includes speech recognition (Whisper) and text-to-speech (Kokoro-TTS) capabilities.
• Offers structured output generation with JSON schemas.

Maintenance & Community

• Active development with a roadmap outlining future enhancements.
• Discord Community available for support and discussion.
• Project is open source and welcomes contributions.

Licensing & Compatibility

• Licensed under the MIT License.
• Compatible with commercial use and closed-source linking due to permissive licensing.

Limitations & Caveats

BrowserAI's performance and model availability are dependent on the user's browser and hardware capabilities, particularly WebGPU support. Some models may have specific hardware requirements, such as f16 support.