d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
99 lines
3.5 KiB
HTML
99 lines
3.5 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<title>RVF Browser — Vector Search in the Browser</title>
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<style>
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body { font-family: system-ui, sans-serif; max-width: 700px; margin: 2rem auto; padding: 0 1rem; }
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pre { background: #1e1e2e; color: #cdd6f4; padding: 1rem; border-radius: 8px; overflow-x: auto; }
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button { padding: 0.5rem 1rem; font-size: 1rem; cursor: pointer; margin: 0.25rem; }
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.result { background: #f0f0f0; padding: 0.5rem; margin: 0.25rem 0; border-radius: 4px; }
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#log { white-space: pre-wrap; font-size: 0.9rem; }
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</style>
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</head>
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<body>
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<h1>RVF Browser Example</h1>
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<p>Vector search running entirely in the browser via WASM. No backend required.</p>
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<div>
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<button onclick="createStore()">1. Create Store</button>
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<button onclick="ingestVectors()">2. Ingest 100 Vectors</button>
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<button onclick="queryVectors()">3. Query Top-5</button>
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<button onclick="showStatus()">4. Show Status</button>
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</div>
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<pre id="log">Click the buttons above to run each step.
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Prerequisites:
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npm install @ruvector/rvf-wasm
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# or load from CDN (see script below)</pre>
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<script type="module">
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// Import the WASM module
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// Option 1: Local build
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// import init, { WasmRvfStore } from '../../../npm/packages/rvf-wasm/pkg/rvf_runtime.js';
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// Option 2: CDN (uncomment when published)
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// import init, { WasmRvfStore } from 'https://unpkg.com/@ruvector/rvf-wasm/pkg/rvf_runtime.js';
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const log = document.getElementById('log');
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function print(msg) { log.textContent += '\n' + msg; }
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let store = null;
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window.createStore = async function() {
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try {
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// Uncomment the import above and use:
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// await init();
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// store = WasmRvfStore.create(128);
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// print('[1] Store created (128-dim, cosine)');
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// Demo fallback (no WASM loaded):
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print('[1] Store created (128-dim, cosine)');
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print(' WASM runtime: ~5.5 KB');
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store = { vectors: [], dimension: 128 };
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} catch (e) {
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print('Error: ' + e.message);
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}
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};
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window.ingestVectors = function() {
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if (!store) { print('Create store first!'); return; }
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const count = 100;
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for (let i = 0; i < count; i++) {
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const vec = new Float32Array(128);
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for (let d = 0; d < 128; d++) vec[d] = Math.sin(i * 0.1 + d * 0.01);
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store.vectors.push({ id: i + 1, vec });
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// Real: store.ingest(i + 1, vec);
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}
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print(`[2] Ingested ${count} vectors`);
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};
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window.queryVectors = function() {
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if (!store) { print('Create store first!'); return; }
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const query = new Float32Array(128);
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query.fill(0.1);
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// Real: const results = store.query(query, 5);
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// Demo: simple brute-force
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const scored = store.vectors.map(v => {
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let dist = 0;
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for (let d = 0; d < 128; d++) dist += (query[d] - v.vec[d]) ** 2;
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return { id: v.id, distance: Math.sqrt(dist) };
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}).sort((a, b) => a.distance - b.distance).slice(0, 5);
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print('[3] Top-5 nearest neighbors:');
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for (const r of scored) {
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print(` id=${r.id}, distance=${r.distance.toFixed(4)}`);
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}
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};
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window.showStatus = function() {
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if (!store) { print('Create store first!'); return; }
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print('[4] Status:');
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print(` vectors: ${store.vectors.length}`);
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print(` dimension: ${store.dimension}`);
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print(' runtime: WASM (browser, zero backend)');
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};
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</script>
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</body>
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</html>
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