🎉 Featured Project: Check out Browseragent.dev - A no-code AI Agent builder powered by BrowserAI with unlimited executions! Build your own AI agents in minutes.

• 🔒 100% Private: All processing happens locally in your browser
• 🚀 WebGPU Accelerated: Near-native performance
• 💰 Zero Server Costs: No complex infrastructure needed
• 🌐 Offline Capable: Works without internet after initial download
• 🎯 Developer Friendly: Simple sdk with multiple engine support
• 📦 Production Ready: Pre-optimized popular models

• Web developers building AI-powered applications
• Companies needing privacy-conscious AI solutions
• Researchers experimenting with browser-based AI
• Hobbyists exploring AI without infrastructure overhead
• No-code platform builders creating AI-powered tools

• 🎯 Run AI models directly in the browser - no server required!
• ⚡ WebGPU acceleration for blazing fast inference
• 🔄 Seamless switching between MLC and Transformers engines
• 📦 Pre-configured popular models ready to use
• 🛠️ Easy-to-use API for text generation and more
• 🔧 Web Worker support for non-blocking UI performance
• 📊 Structured output generation with JSON schemas
• 🎙️ Speech recognition and text-to-speech capabilities
• 💾 Built-in database support for storing conversations and embeddings

npm install @browserai/browserai

OR

yarn add @browserai/browserai

import { BrowserAI } from '@browserai/browserai';
const browserAI = new BrowserAI();
// Load model with progress tracking
await browserAI.loadModel('llama-3.2-1b-instruct', {
 quantization: 'q4f16_1',
 onProgress: (progress) => console.log('Loading:', progress.progress + '%')
});
// Generate text
const response = await browserAI.generateText('Hello, how are you?');
console.log(response.choices[0].message.content);

const response = await browserAI.generateText('Write a short poem about coding', {
 temperature: 0.8,
 max_tokens: 100,
 system_prompt: "You are a creative poet specialized in technology themes."
});

const ai = new BrowserAI();
await ai.loadModel('gemma-2b-it');
const response = await ai.generateText([
 { role: 'system', content: 'You are a helpful assistant.' },
 { role: 'user', content: 'What is WebGPU?' }
]);

const response = await browserAI.generateText('List 3 colors', {
 json_schema: {
 type: "object",
 properties: {
 colors: {
 type: "array",
 items: {
 type: "object",
 properties: {
 name: { type: "string" },
 hex: { type: "string" }
 }
 }
 }
 }
 },
 response_format: { type: "json_object" }
});

const browserAI = new BrowserAI();
await browserAI.loadModel('whisper-tiny-en');
// Using the built-in recorder
await browserAI.startRecording();
const audioBlob = await browserAI.stopRecording();
const transcription = await browserAI.transcribeAudio(audioBlob, {
 return_timestamps: true,
 language: 'en'
});

const ai = new BrowserAI();
await ai.loadModel('kokoro-tts');
const audioBuffer = await browserAI.textToSpeech('Hello, how are you today?', {
 voice: 'af_bella',
 speed: 1.0
});// Play the audio using Web Audio API
const audioContext = new AudioContext();
const source = audioContext.createBufferSource();
audioContext.decodeAudioData(audioBuffer, (buffer) => {
 source.buffer = buffer;
 source.connect(audioContext.destination);
 source.start(0);
});

More models will be added soon. Request a model by creating an issue.

• Llama-3.2-1b-Instruct
• Llama-3.2-3b-Instruct
• Hermes-Llama-3.2-3b
• SmolLM2-135M-Instruct
• SmolLM2-360M-Instruct
• SmolLM2-1.7B-Instruct
• Qwen-0.5B-Instruct
• Gemma-2B-IT
• TinyLlama-1.1B-Chat-v0.4
• Phi-3.5-mini-instruct
• Qwen3-0.6B
• Qwen3-1.7B
• Qwen3-4B
• Qwen3-8B
• Qwen2.5-1.5B-Instruct
• DeepSeek-R1-Distill-Qwen-7B
• DeepSeek-R1-Distill-Llama-8B
• Snowflake-Arctic-Embed-M-B32
• Snowflake-Arctic-Embed-S-B32
• Snowflake-Arctic-Embed-M-B4
• Snowflake-Arctic-Embed-S-B4

• Llama-3.2-1b-Instruct
• Whisper-tiny-en (Speech Recognition)
• Whisper-base-all (Speech Recognition)
• Whisper-small-all (Speech Recognition)
• Kokoro-TTS (Text-to-Speech)

• 🎯 Simplified model initialization
• 📊 Basic monitoring and metrics
• 🔍 Simple RAG implementation
• 🛠️ Developer tools integration

• 📚 Enhanced RAG capabilities
  • Hybrid search
  • Auto-chunking
  • Source tracking
• 📊 Advanced observability
  • Performance dashboards
  • Memory profiling
  • Error tracking

• 🔐 Security features
• 📈 Advanced analytics
• 🤝 Multi-model orchestration

We welcome contributions! Feel free to:

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

This project is licensed under the MIT License - see the LICENSE file for details.

• MLC AI for their incredible mode compilation library and support for webgpu runtime and xgrammar
• Hugging Face and Xenova for their Transformers.js library, licensed under Apache License 2.0. The original code has been modified to work in a browser environment and converted to TypeScript.
• All our contributors and supporters!

Made with ❤️ for the AI community

• Modern browser with WebGPU support (Chrome 113+, Edge 113+, or equivalent)
• For models with shader-f16 requirement, hardware must support 16-bit floating point operations