SONA WASM Example

Interactive browser demo of the Self-Optimizing Neural Architecture (SONA).

Quick Start

Build the WASM module (if not already built):

cd ..
wasm-pack build --target web --features wasm
cp -r pkg wasm-example/

Serve the example:

cd wasm-example
python3 -m http.server 8080

Open in browser:

http://localhost:8080

Features

Real-time Learning: Record trajectories and see instant updates
LoRA Visualization: Watch transformation in real-time
Statistics Dashboard: Monitor patterns, quality, and performance
Interactive Controls: Adjust configuration and run experiments

Files

index.html - Demo page with UI
index.js - JavaScript logic using WASM bindings
package.json - NPM configuration
pkg/ - Generated WASM package
- sona.js - JavaScript bindings
- sona_bg.wasm - WebAssembly binary
- sona.d.ts - TypeScript definitions

Usage Example

import init, { WasmSonaEngine } from './pkg/sona.js';

async function main() {
  await init();
  
  const engine = new WasmSonaEngine(256);
  const trajectoryId = engine.start_trajectory(new Float32Array(256).fill(0.1));
  engine.record_step(trajectoryId, 42, 0.8, 1000);
  engine.end_trajectory(trajectoryId, 0.85);
  
  const output = engine.apply_lora(new Float32Array(256).fill(1.0));
  console.log('Transformed output:', output);
}

main();

Performance

WASM file size: ~1.5MB (release build)
Initialization: < 100ms
Per-trajectory overhead: < 1ms
LoRA application: < 0.1ms (256-dim)

Browser Support

Chrome/Edge 91+
Firefox 89+
Safari 14.1+

License

MIT OR Apache-2.0