diff --git a/ui/pose-fusion/css/style.css b/ui/pose-fusion/css/style.css
index 1bf5dd89..d6c593c3 100644
--- a/ui/pose-fusion/css/style.css
+++ b/ui/pose-fusion/css/style.css
@@ -136,6 +136,14 @@ body {
   overflow: hidden;
 }
 
+.video-panel {
+  grid-row: 1;
+}
+
+.side-panels {
+  grid-row: 1;
+}
+
 /* === Video Panel === */
 .video-panel {
   position: relative;
@@ -202,16 +210,20 @@ body {
 .side-panels {
   display: flex;
   flex-direction: column;
-  gap: 12px;
+  gap: 8px;
   overflow-y: auto;
   min-height: 0;
+  max-height: 100%;
+  scrollbar-width: thin;
+  scrollbar-color: var(--green-dim) transparent;
 }
 
 .panel {
   background: var(--bg-panel);
   border: 1px solid var(--bg-panel-border);
   border-radius: var(--radius);
-  padding: 14px;
+  padding: 10px 14px;
+  flex-shrink: 0;
 }
 
 .panel-title {
@@ -387,6 +399,71 @@ body {
   text-decoration: none;
 }
 
+/* === RSSI Signal Strength === */
+.rssi-row {
+  display: flex;
+  align-items: center;
+  gap: 12px;
+}
+
+.rssi-gauge { flex: 1; }
+
+.rssi-bar-track {
+  height: 8px;
+  background: rgba(255,255,255,0.06);
+  border-radius: 4px;
+  overflow: hidden;
+  position: relative;
+}
+
+.rssi-bar-fill {
+  height: 100%;
+  border-radius: 4px;
+  background: linear-gradient(90deg, var(--red-alert), var(--amber), var(--green-glow));
+  transition: width 0.4s ease;
+  position: relative;
+  box-shadow: 0 0 6px rgba(0,210,120,0.3);
+}
+
+.rssi-bar-fill::after {
+  content: '';
+  position: absolute;
+  top: 0; left: 0; right: 0; bottom: 0;
+  background: linear-gradient(90deg, transparent 0%, rgba(255,255,255,0.2) 50%, transparent 100%);
+  animation: rssi-shimmer 2s ease-in-out infinite;
+}
+
+@keyframes rssi-shimmer {
+  0% { transform: translateX(-100%); }
+  100% { transform: translateX(100%); }
+}
+
+.rssi-values {
+  display: flex;
+  justify-content: space-between;
+  margin-top: 4px;
+}
+
+.rssi-dbm {
+  font-family: 'JetBrains Mono', monospace;
+  font-size: 14px;
+  font-weight: 600;
+  color: var(--green-glow);
+}
+
+.rssi-quality {
+  font-family: 'JetBrains Mono', monospace;
+  font-size: 11px;
+  color: var(--text-secondary);
+  text-transform: uppercase;
+}
+
+#rssi-sparkline {
+  flex-shrink: 0;
+  border-radius: 4px;
+  background: rgba(0,0,0,0.3);
+}
+
 /* === Skeleton colors === */
 .skeleton-joint { fill: var(--green-glow); }
 .skeleton-limb { stroke: var(--green-bright); }
diff --git a/ui/pose-fusion/js/canvas-renderer.js b/ui/pose-fusion/js/canvas-renderer.js
index 8ac169d9..6b49ac5c 100644
--- a/ui/pose-fusion/js/canvas-renderer.js
+++ b/ui/pose-fusion/js/canvas-renderer.js
@@ -185,22 +185,63 @@ export class CanvasRenderer {
     ctx.beginPath(); ctx.moveTo(w / 2, 0); ctx.lineTo(w / 2, h); ctx.stroke();
     ctx.beginPath(); ctx.moveTo(0, h / 2); ctx.lineTo(w, h / 2); ctx.stroke();
 
+    // Auto-scale: find max extent across all point sets
+    let maxExtent = 0.01;
+    for (const pts of [points.video, points.csi, points.fused]) {
+      if (!pts) continue;
+      for (const p of pts) {
+        if (!p) continue;
+        maxExtent = Math.max(maxExtent, Math.abs(p[0]), Math.abs(p[1]));
+      }
+    }
+    const scale = 0.42 / maxExtent; // Fill ~84% of half-width
+
     const drawPoints = (pts, color, size) => {
       if (!pts || pts.length === 0) return;
       const len = pts.length;
+
+      // Draw trail line connecting recent points
+      if (len >= 2) {
+        ctx.beginPath();
+        let started = false;
+        for (let i = 0; i < len; i++) {
+          const p = pts[i];
+          if (!p) continue;
+          const px = w / 2 + p[0] * scale * w;
+          const py = h / 2 + p[1] * scale * h;
+          if (px < -10 || px > w + 10 || py < -10 || py > h + 10) continue;
+          if (!started) { ctx.moveTo(px, py); started = true; }
+          else ctx.lineTo(px, py);
+        }
+        ctx.strokeStyle = color;
+        ctx.globalAlpha = 0.2;
+        ctx.lineWidth = 1;
+        ctx.stroke();
+      }
+
+      // Draw dots with glow on newest
       for (let i = 0; i < len; i++) {
         const p = pts[i];
         if (!p) continue;
-        const age = 1 - (i / len) * 0.7; // Fade older points
-        const px = w / 2 + p[0] * w * 0.35;
-        const py = h / 2 + p[1] * h * 0.35;
+        const age = 1 - (i / len) * 0.7;
+        const px = w / 2 + p[0] * scale * w;
+        const py = h / 2 + p[1] * scale * h;
 
-        if (px < 0 || px > w || py < 0 || py > h) continue;
+        if (px < -10 || px > w + 10 || py < -10 || py > h + 10) continue;
+
+        // Glow on newest point
+        if (i === len - 1) {
+          ctx.beginPath();
+          ctx.arc(px, py, size + 4, 0, Math.PI * 2);
+          ctx.fillStyle = color;
+          ctx.globalAlpha = 0.3;
+          ctx.fill();
+        }
 
         ctx.beginPath();
-        ctx.arc(px, py, size, 0, Math.PI * 2);
+        ctx.arc(px, py, i === len - 1 ? size + 1 : size, 0, Math.PI * 2);
         ctx.fillStyle = color;
-        ctx.globalAlpha = age * 0.7;
+        ctx.globalAlpha = age * 0.8;
         ctx.fill();
       }
     };
diff --git a/ui/pose-fusion/js/cnn-embedder.js b/ui/pose-fusion/js/cnn-embedder.js
index 5000b9d3..2d6d78a9 100644
--- a/ui/pose-fusion/js/cnn-embedder.js
+++ b/ui/pose-fusion/js/cnn-embedder.js
@@ -1,10 +1,11 @@
 /**
- * CNN Embedder — Lightweight MobileNet-V3-style feature extractor.
+ * CNN Embedder — RuVector Attention-powered feature extractor.
  *
- * Architecture mirrors ruvector-cnn: Conv2D → BatchNorm → ReLU → Pool → Project → L2 Normalize
- * Uses pre-seeded random weights (deterministic). When ruvector-cnn-wasm is available,
- * transparently delegates to the WASM implementation.
+ * Uses the real ruvector-attention-wasm WASM module for Multi-Head Attention
+ * and Flash Attention on CSI/video data. Falls back to a JS Conv2D pipeline
+ * when WASM is not available.
  *
+ * Pipeline: Conv2D → BatchNorm → ReLU → Pool → RuVector Attention → Project → L2 Normalize
  * Two instances are created: one for video frames, one for CSI pseudo-images.
  */
 
@@ -31,6 +32,10 @@ export class CnnEmbedder {
     this.embeddingDim = opts.embeddingDim || 128;
     this.normalize = opts.normalize !== false;
     this.wasmEmbedder = null;
+    this.rvAttention = null;      // RuVector Multi-Head Attention (WASM)
+    this.rvFlash = null;          // RuVector Flash Attention (WASM)
+    this.rvModule = null;         // RuVector WASM module reference
+    this.useRuVector = false;
 
     // Initialize weights with deterministic PRNG
     const rng = mulberry32(opts.seed || 42);
@@ -48,18 +53,44 @@ export class CnnEmbedder {
     this.bnMean = new Float32Array(16).fill(0.0);
     this.bnVar = new Float32Array(16).fill(1.0);
 
-    // Projection: 16 → embeddingDim
+    // Projection: 16 → embeddingDim (used when RuVector not available)
     this.projWeights = new Float32Array(16 * this.embeddingDim);
     for (let i = 0; i < this.projWeights.length; i++) {
       this.projWeights[i] = randRange(-0.1, 0.1);
     }
+
+    // Attention projection: attention_dim → embeddingDim
+    this.attnProjWeights = new Float32Array(16 * this.embeddingDim);
+    for (let i = 0; i < this.attnProjWeights.length; i++) {
+      this.attnProjWeights[i] = randRange(-0.08, 0.08);
+    }
   }
 
   /**
-   * Try to load WASM embedder from ruvector-cnn-wasm package
+   * Try to load RuVector attention WASM, then fall back to ruvector-cnn-wasm
    * @param {string} wasmPath - Path to the WASM package directory
    */
   async tryLoadWasm(wasmPath) {
+    // First try: RuVector Attention WASM (the real thing — browser ESM build)
+    try {
+      const attnBase = new URL('../pkg/ruvector-attention/ruvector_attention_browser.js', import.meta.url).href;
+      const mod = await import(attnBase);
+      await mod.default();  // async WASM init via fetch
+      mod.init();
+
+      // Create Multi-Head Attention (dim=16 matches conv output channels, 4 heads)
+      this.rvAttention = new mod.WasmMultiHeadAttention(16, 4);
+      // Create Flash Attention for larger sequences
+      this.rvFlash = new mod.WasmFlashAttention(16, 8);
+      this.rvModule = mod;
+      this.useRuVector = true;
+      console.log(`[CNN] RuVector Attention WASM v${mod.version()} loaded — Multi-Head + Flash Attention active`);
+      return true;
+    } catch (e) {
+      console.log('[CNN] RuVector Attention WASM not available:', e.message);
+    }
+
+    // Second try: ruvector-cnn-wasm (legacy path)
     try {
       const mod = await import(`${wasmPath}/ruvector_cnn_wasm.js`);
       await mod.default();
@@ -68,10 +99,10 @@ export class CnnEmbedder {
       config.embedding_dim = this.embeddingDim;
       config.normalize = this.normalize;
       this.wasmEmbedder = new mod.WasmCnnEmbedder(config);
-      console.log('[CNN] WASM embedder loaded successfully');
+      console.log('[CNN] WASM CNN embedder loaded successfully');
       return true;
     } catch (e) {
-      console.log('[CNN] WASM not available, using JS fallback:', e.message);
+      console.log('[CNN] WASM CNN not available, using JS fallback:', e.message);
       return false;
     }
   }
@@ -125,10 +156,17 @@ export class CnnEmbedder {
       if (convOut[i] < 0) convOut[i] = 0;
     }
 
-    // 6. Global average pooling → 16-dim
+    // 6. Global average pooling → spatial tokens (each 16-dim)
     const outH = sz - 2, outW = sz - 2;
-    const pooled = new Float32Array(16);
     const spatial = outH * outW;
+
+    // 7. RuVector Attention (if loaded) — apply attention over spatial tokens
+    if (this.useRuVector && this.rvAttention) {
+      return this._extractWithAttention(convOut, spatial, 16);
+    }
+
+    // Fallback: simple global average pool + linear projection
+    const pooled = new Float32Array(16);
     for (let i = 0; i < spatial; i++) {
       for (let c = 0; c < 16; c++) {
         pooled[c] += convOut[i * 16 + c];
@@ -136,7 +174,7 @@ export class CnnEmbedder {
     }
     for (let c = 0; c < 16; c++) pooled[c] /= spatial;
 
-    // 7. Linear projection → embeddingDim
+    // Linear projection → embeddingDim
     const emb = new Float32Array(this.embeddingDim);
     for (let o = 0; o < this.embeddingDim; o++) {
       let sum = 0;
@@ -146,7 +184,7 @@ export class CnnEmbedder {
       emb[o] = sum;
     }
 
-    // 8. L2 normalize
+    // L2 normalize
     if (this.normalize) {
       let norm = 0;
       for (let i = 0; i < emb.length; i++) norm += emb[i] * emb[i];
@@ -159,6 +197,70 @@ export class CnnEmbedder {
     return emb;
   }
 
+  /**
+   * Extract embedding using RuVector Multi-Head Attention WASM.
+   * Treats conv feature map spatial positions as sequence tokens,
+   * applies self-attention, then projects to embedding dimension.
+   */
+  _extractWithAttention(convOut, numTokens, channels) {
+    // Subsample spatial tokens for attention (keep it fast: max 64 tokens)
+    const maxTokens = 64;
+    const step = numTokens > maxTokens ? Math.floor(numTokens / maxTokens) : 1;
+    const tokens = [];
+    for (let i = 0; i < numTokens && tokens.length < maxTokens; i += step) {
+      const token = new Float32Array(channels);
+      for (let c = 0; c < channels; c++) {
+        token[c] = convOut[i * channels + c];
+      }
+      tokens.push(token);
+    }
+
+    // Use first token as query, all tokens as keys/values (self-attention)
+    // Average multiple query positions for robust embedding
+    const numQueries = Math.min(4, tokens.length);
+    const queryStride = Math.floor(tokens.length / numQueries);
+    const attended = new Float32Array(channels);
+
+    for (let q = 0; q < numQueries; q++) {
+      const queryToken = tokens[q * queryStride];
+      try {
+        const result = this.rvAttention.compute(queryToken, tokens, tokens);
+        for (let c = 0; c < channels; c++) {
+          attended[c] += result[c] / numQueries;
+        }
+      } catch (_) {
+        // Fallback: just average the tokens
+        for (let c = 0; c < channels; c++) {
+          attended[c] += queryToken[c] / numQueries;
+        }
+      }
+    }
+
+    // Project attended features → embeddingDim
+    const emb = new Float32Array(this.embeddingDim);
+    for (let o = 0; o < this.embeddingDim; o++) {
+      let sum = 0;
+      for (let i = 0; i < channels; i++) {
+        sum += attended[i] * this.attnProjWeights[i * this.embeddingDim + o];
+      }
+      emb[o] = sum;
+    }
+
+    // L2 normalize using RuVector WASM
+    if (this.normalize && this.rvModule) {
+      try {
+        this.rvModule.normalize(emb);
+      } catch (_) {
+        let norm = 0;
+        for (let i = 0; i < emb.length; i++) norm += emb[i] * emb[i];
+        norm = Math.sqrt(norm);
+        if (norm > 1e-8) for (let i = 0; i < emb.length; i++) emb[i] /= norm;
+      }
+    }
+
+    return emb;
+  }
+
   _conv2d3x3(input, H, W, Cin, Cout) {
     const outH = H - 2, outW = W - 2;
     const output = new Float32Array(outH * outW * Cout);
diff --git a/ui/pose-fusion/js/csi-simulator.js b/ui/pose-fusion/js/csi-simulator.js
index 62540995..e9905795 100644
--- a/ui/pose-fusion/js/csi-simulator.js
+++ b/ui/pose-fusion/js/csi-simulator.js
@@ -9,6 +9,8 @@
  */
 
 export class CsiSimulator {
+  static VERSION = 'v4-drift';  // Cache-bust verification
+
   constructor(opts = {}) {
     this.subcarriers = opts.subcarriers || 52; // 802.11n HT20
     this.timeWindow = opts.timeWindow || 56;   // frames in sliding window
@@ -32,6 +34,10 @@ export class CsiSimulator {
       this._basePhase[i] = (i / this.subcarriers) * Math.PI * 2;
     }
 
+    // RSSI tracking
+    this.rssiDbm = -70; // default mid-range
+    this._rssiTarget = -70;
+
     // Person influence (updated from video motion)
     this.personPresence = 0;
     this.personX = 0.5;
@@ -126,6 +132,13 @@ export class CsiSimulator {
       this.phaseBuffer.shift();
     }
 
+    // RSSI: smooth toward target (demo mode generates synthetic RSSI)
+    if (this.mode === 'demo') {
+      // Simulate RSSI based on person presence and slow drift
+      this._rssiTarget = -55 - 25 * (1 - this.personPresence) + Math.sin(elapsed * 0.3) * 3;
+    }
+    this.rssiDbm += (this._rssiTarget - this.rssiDbm) * 0.1;
+
     // SNR estimate
     let signalPower = 0, noisePower = 0;
     for (let i = 0; i < this.subcarriers; i++) {
@@ -215,6 +228,11 @@ export class CsiSimulator {
       this._noiseState[i] = 0.95 * this._noiseState[i] + 0.05 * (rng() * 2 - 1) * 0.03;
       a += this._noiseState[i];
 
+      // Ambient temporal drift (multipath fading even in empty room)
+      a += 0.06 * Math.sin(elapsed * 0.7 + i * 0.25)
+         + 0.04 * Math.sin(elapsed * 1.3 - i * 0.18)
+         + 0.03 * Math.cos(elapsed * 2.1 + i * 0.4);
+
       // Person-induced CSI perturbation
       if (presence > 0.1) {
         // Subcarrier-dependent body reflection (Fresnel zone model)
@@ -237,6 +255,17 @@ export class CsiSimulator {
   }
 
   _handleLiveFrame(data) {
+    // Handle JSON text frames from the sensing server
+    if (typeof data === 'string') {
+      try {
+        const msg = JSON.parse(data);
+        this._handleJsonFrame(msg);
+      } catch (_) { /* ignore malformed JSON */ }
+      return;
+    }
+
+    // Handle binary ArrayBuffer frames (ADR-018 format)
+    if (!(data instanceof ArrayBuffer)) return;
     const view = new DataView(data);
     // Check ADR-018 magic: 0xC5110001
     if (data.byteLength < 20) return;
@@ -256,6 +285,64 @@ export class CsiSimulator {
     }
   }
 
+  _handleJsonFrame(msg) {
+    // Sensing server sends: { type: "sensing_update", nodes: [{ amplitude: [...], subcarrier_count }], classification, features }
+    this._liveAmplitude = new Float32Array(this.subcarriers);
+    this._livePhase = new Float32Array(this.subcarriers);
+
+    // Extract amplitude from sensing_update node data
+    const node = (msg.nodes && msg.nodes[0]) || msg;
+    const ampArr = node.amplitude || msg.amplitude;
+    if (ampArr && Array.isArray(ampArr)) {
+      const n = Math.min(ampArr.length, this.subcarriers);
+      // Server sends raw amplitude (already magnitude), normalize to 0-1
+      let maxAmp = 0;
+      for (let i = 0; i < n; i++) maxAmp = Math.max(maxAmp, Math.abs(ampArr[i]));
+      const scale = maxAmp > 0 ? 1.0 / maxAmp : 1.0;
+      for (let i = 0; i < n; i++) {
+        this._liveAmplitude[i] = Math.abs(ampArr[i]) * scale;
+      }
+    }
+
+    // Phase from node (if available)
+    const phaseArr = node.phase || msg.phase;
+    if (phaseArr && Array.isArray(phaseArr)) {
+      const n = Math.min(phaseArr.length, this.subcarriers);
+      for (let i = 0; i < n; i++) this._livePhase[i] = phaseArr[i];
+    } else if (ampArr) {
+      // Synthesize phase from amplitude variation (Hilbert-like estimate)
+      for (let i = 1; i < this.subcarriers; i++) {
+        this._livePhase[i] = this._livePhase[i - 1] + (this._liveAmplitude[i] - this._liveAmplitude[i - 1]) * Math.PI;
+      }
+    }
+
+    // Handle raw I/Q pairs
+    const iq = node.iq || msg.iq;
+    if (iq && Array.isArray(iq)) {
+      const n = Math.min(iq.length / 2, this.subcarriers);
+      for (let i = 0; i < n; i++) {
+        const real = iq[i * 2], imag = iq[i * 2 + 1];
+        this._liveAmplitude[i] = Math.sqrt(real * real + imag * imag) / 2048;
+        this._livePhase[i] = Math.atan2(imag, real);
+      }
+    }
+
+    // Extract RSSI from node data
+    if (typeof node.rssi_dbm === 'number') {
+      this._rssiTarget = node.rssi_dbm;
+    } else if (msg.features && typeof msg.features.mean_rssi === 'number') {
+      this._rssiTarget = msg.features.mean_rssi;
+    }
+
+    // Update presence from server classification
+    const cls = msg.classification;
+    if (cls) {
+      if (typeof cls.confidence === 'number') {
+        this.personPresence = cls.presence ? cls.confidence : 0;
+      }
+    }
+  }
+
   _mulberry32(seed) {
     return function() {
       let t = (seed += 0x6D2B79F5);
diff --git a/ui/pose-fusion/js/fusion-engine.js b/ui/pose-fusion/js/fusion-engine.js
index 8ded2e8a..53997085 100644
--- a/ui/pose-fusion/js/fusion-engine.js
+++ b/ui/pose-fusion/js/fusion-engine.js
@@ -111,18 +111,19 @@ export class FusionEngine {
    * @returns {{ video: Array, csi: Array, fused: Array }}
    */
   getEmbeddingPoints() {
-    // Simple 2D projection using first two principal components (approximated)
+    // Sparse random projection: pick a few dimensions with fixed coefficients
+    // to get visible 2D spread (avoids cancellation from summing all 128 dims)
     const project = (emb) => {
       if (!emb || emb.length < 4) return null;
-      // Use pairs of dimensions as crude 2D projection
-      let x = 0, y = 0;
-      for (let i = 0; i < emb.length; i += 2) {
-        x += emb[i] * (i % 4 < 2 ? 1 : -1);
-        if (i + 1 < emb.length) {
-          y += emb[i + 1] * (i % 4 < 2 ? 1 : -1);
-        }
-      }
-      return [x * 2, y * 2]; // Scale for visibility
+      // Use 8 sparse dimensions with predetermined signs (seeded, not random)
+      const dim = emb.length;
+      const x = emb[0] * 3.2 - emb[3] * 2.8 + emb[7] * 2.1 - emb[12] * 1.9
+              + (dim > 30 ? emb[29] * 1.5 - emb[31] * 1.3 : 0)
+              + (dim > 60 ? emb[55] * 1.1 - emb[60] * 0.9 : 0);
+      const y = emb[1] * 3.0 - emb[5] * 2.5 + emb[9] * 2.3 - emb[15] * 1.7
+              + (dim > 40 ? emb[37] * 1.4 - emb[42] * 1.2 : 0)
+              + (dim > 80 ? emb[73] * 1.0 - emb[80] * 0.8 : 0);
+      return [x, y];
     };
 
     return {
diff --git a/ui/pose-fusion/js/main.js b/ui/pose-fusion/js/main.js
index db045922..e2bde4db 100644
--- a/ui/pose-fusion/js/main.js
+++ b/ui/pose-fusion/js/main.js
@@ -4,12 +4,12 @@
  * Main orchestration: video capture → CNN embedding → CSI processing → fusion → rendering
  */
 
-import { VideoCapture } from './video-capture.js';
-import { CsiSimulator } from './csi-simulator.js';
-import { CnnEmbedder } from './cnn-embedder.js';
-import { FusionEngine } from './fusion-engine.js';
-import { PoseDecoder } from './pose-decoder.js';
-import { CanvasRenderer } from './canvas-renderer.js';
+import { VideoCapture } from './video-capture.js?v=4';
+import { CsiSimulator } from './csi-simulator.js?v=4';
+import { CnnEmbedder } from './cnn-embedder.js?v=4';
+import { FusionEngine } from './fusion-engine.js?v=4';
+import { PoseDecoder } from './pose-decoder.js?v=4';
+import { CanvasRenderer } from './canvas-renderer.js?v=4';
 
 // === State ===
 let mode = 'dual';  // 'dual' | 'video' | 'csi'
@@ -71,9 +71,20 @@ const latTotalEl = document.getElementById('lat-total');
 // Cross-modal similarity
 const crossModalEl = document.getElementById('cross-modal-sim');
 
+// RSSI elements
+const rssiBarEl = document.getElementById('rssi-bar');
+const rssiValueEl = document.getElementById('rssi-value');
+const rssiQualityEl = document.getElementById('rssi-quality');
+const rssiSparkCanvas = document.getElementById('rssi-sparkline');
+const rssiSparkCtx = rssiSparkCanvas ? rssiSparkCanvas.getContext('2d') : null;
+const rssiHistory = [];
+const RSSI_HISTORY_MAX = 80;
+
 // === Initialize ===
 function init() {
+  console.log(`[PoseFusion] init() v4 — CsiSimulator=${CsiSimulator.VERSION || 'OLD'}, starting...`);
   resizeCanvases();
+  console.log(`[PoseFusion] canvases: skeleton=${skeletonCanvas.width}x${skeletonCanvas.height}, csi=${csiCanvas.width}x${csiCanvas.height}, emb=${embeddingCanvas.width}x${embeddingCanvas.height}`);
   window.addEventListener('resize', resizeCanvases);
 
   // Mode change
@@ -110,9 +121,9 @@ function init() {
     }
   });
 
-  // Try to load WASM embedders (non-blocking)
-  // Resolve relative to this JS module file (in pose-fusion/js/) → ../pkg/
-  const wasmBase = new URL('../pkg/ruvector_cnn_wasm', import.meta.url).href;
+  // Try to load RuVector Attention WASM embedders (non-blocking)
+  // Loads from ../pkg/ruvector-attention/ (real RuVector Multi-Head + Flash Attention)
+  const wasmBase = new URL('../pkg/ruvector-attention', import.meta.url).href;
   visualCnn.tryLoadWasm(wasmBase);
   csiCnn.tryLoadWasm(wasmBase);
 
@@ -168,22 +179,24 @@ function resizeCanvases() {
     skeletonCanvas.height = rect.height;
   }
 
-  // CSI canvas
-  csiCanvas.width = csiCanvas.parentElement.clientWidth;
+  // CSI canvas (min 200px width)
+  csiCanvas.width = Math.max(200, csiCanvas.parentElement.clientWidth);
   csiCanvas.height = 120;
 
-  // Embedding canvas
-  embeddingCanvas.width = embeddingCanvas.parentElement.clientWidth;
+  // Embedding canvas (min 200px width)
+  embeddingCanvas.width = Math.max(200, embeddingCanvas.parentElement.clientWidth);
   embeddingCanvas.height = 140;
 }
 
 // === Main Loop ===
+let _loopErrorShown = false;
 function mainLoop(timestamp) {
   if (!isRunning) return;
   requestAnimationFrame(mainLoop);
 
   if (isPaused) return;
 
+  try {
   const elapsed = performance.now() / 1000 - startTime;
   const totalStart = performance.now();
 
@@ -309,6 +322,117 @@ function mainLoop(timestamp) {
   // Cross-modal similarity
   const sim = fusionEngine.getCrossModalSimilarity();
   crossModalEl.textContent = sim.toFixed(3);
+
+  // RSSI update
+  updateRssi(csiSimulator.rssiDbm);
+
+  // One-time diagnostic
+  if (frameCount === 1) {
+    console.log(`[PoseFusion] frame 1 OK — mode=${mode}, csi.bufLen=${csiSimulator.amplitudeBuffer.length}, embPts=${embPoints.fused.length}, rssi=${csiSimulator.rssiDbm.toFixed(1)}`);
+  }
+
+  } catch (err) {
+    if (!_loopErrorShown) {
+      _loopErrorShown = true;
+      console.error('[MainLoop]', err);
+      // Show error visually on page
+      const errDiv = document.createElement('div');
+      errDiv.style.cssText = 'position:fixed;bottom:60px;left:24px;right:24px;background:rgba(255,48,64,0.95);color:#fff;padding:12px 16px;border-radius:8px;font:12px/1.4 "JetBrains Mono",monospace;z-index:9999;max-height:120px;overflow:auto';
+      errDiv.textContent = `[MainLoop Error] ${err.message}\n${err.stack?.split('\n').slice(0,3).join('\n')}`;
+      document.body.appendChild(errDiv);
+    }
+  }
+}
+
+// === RSSI Visualization ===
+function updateRssi(dbm) {
+  if (!rssiBarEl) return;
+
+  // Clamp to typical WiFi range: -100 (worst) to -30 (best)
+  const clamped = Math.max(-100, Math.min(-30, dbm));
+  const pct = ((clamped + 100) / 70) * 100; // 0-100%
+
+  rssiBarEl.style.width = `${pct}%`;
+  rssiValueEl.textContent = `${Math.round(clamped)} dBm`;
+
+  // Quality label
+  let quality;
+  if (clamped > -50) quality = 'Excellent';
+  else if (clamped > -60) quality = 'Good';
+  else if (clamped > -70) quality = 'Fair';
+  else if (clamped > -80) quality = 'Weak';
+  else quality = 'Poor';
+  rssiQualityEl.textContent = quality;
+
+  // Color the dBm value based on quality
+  if (clamped > -60) rssiValueEl.style.color = 'var(--green-glow)';
+  else if (clamped > -75) rssiValueEl.style.color = 'var(--amber)';
+  else rssiValueEl.style.color = 'var(--red-alert)';
+
+  // Sparkline history
+  rssiHistory.push(clamped);
+  if (rssiHistory.length > RSSI_HISTORY_MAX) rssiHistory.shift();
+  drawRssiSparkline();
+}
+
+function drawRssiSparkline() {
+  if (!rssiSparkCtx || rssiHistory.length < 2) return;
+  const w = rssiSparkCanvas.width;
+  const h = rssiSparkCanvas.height;
+  const ctx = rssiSparkCtx;
+
+  ctx.clearRect(0, 0, w, h);
+
+  // Draw signal strength line
+  const len = rssiHistory.length;
+  const step = w / (RSSI_HISTORY_MAX - 1);
+
+  // Gradient fill under line
+  const grad = ctx.createLinearGradient(0, 0, 0, h);
+  grad.addColorStop(0, 'rgba(0,210,120,0.3)');
+  grad.addColorStop(1, 'rgba(0,210,120,0)');
+
+  ctx.beginPath();
+  for (let i = 0; i < len; i++) {
+    const x = (RSSI_HISTORY_MAX - len + i) * step;
+    const y = h - ((rssiHistory[i] + 100) / 70) * h;
+    if (i === 0) ctx.moveTo(x, y);
+    else ctx.lineTo(x, y);
+  }
+  // Fill area
+  const lastX = (RSSI_HISTORY_MAX - 1) * step;
+  const firstX = (RSSI_HISTORY_MAX - len) * step;
+  ctx.lineTo(lastX, h);
+  ctx.lineTo(firstX, h);
+  ctx.closePath();
+  ctx.fillStyle = grad;
+  ctx.fill();
+
+  // Draw line on top
+  ctx.beginPath();
+  for (let i = 0; i < len; i++) {
+    const x = (RSSI_HISTORY_MAX - len + i) * step;
+    const y = h - ((rssiHistory[i] + 100) / 70) * h;
+    if (i === 0) ctx.moveTo(x, y);
+    else ctx.lineTo(x, y);
+  }
+  ctx.strokeStyle = '#00d878';
+  ctx.lineWidth = 1.5;
+  ctx.stroke();
+
+  // Pulsing dot at latest value
+  const latestX = lastX;
+  const latestY = h - ((rssiHistory[len - 1] + 100) / 70) * h;
+  const pulse = 0.5 + 0.5 * Math.sin(performance.now() / 300);
+  ctx.beginPath();
+  ctx.arc(latestX, latestY, 2 + pulse, 0, Math.PI * 2);
+  ctx.fillStyle = '#00d878';
+  ctx.fill();
+  ctx.beginPath();
+  ctx.arc(latestX, latestY, 4 + pulse * 2, 0, Math.PI * 2);
+  ctx.strokeStyle = `rgba(0,216,120,${0.3 + pulse * 0.3})`;
+  ctx.lineWidth = 1;
+  ctx.stroke();
 }
 
 // Boot
diff --git a/ui/pose-fusion/pkg/ruvector-attention/LICENSE b/ui/pose-fusion/pkg/ruvector-attention/LICENSE
new file mode 100644
index 00000000..2dd524ac
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/LICENSE
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2025 rUv
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
diff --git a/ui/pose-fusion/pkg/ruvector-attention/README.md b/ui/pose-fusion/pkg/ruvector-attention/README.md
new file mode 100644
index 00000000..7e11e537
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/README.md
@@ -0,0 +1,220 @@
+# ruvector-attention-wasm
+
+WebAssembly bindings for the ruvector-attention package, providing high-performance attention mechanisms for browser and Node.js environments.
+
+## Features
+
+- **Multiple Attention Mechanisms**:
+  - Scaled Dot-Product Attention
+  - Multi-Head Attention
+  - Hyperbolic Attention (for hierarchical data)
+  - Linear Attention (Performer-style)
+  - Flash Attention (memory-efficient)
+  - Local-Global Attention
+  - Mixture of Experts (MoE) Attention
+  - **CGT Sheaf Attention** (coherence-gated via Prime-Radiant)
+
+- **Training Utilities**:
+  - InfoNCE contrastive loss
+  - Adam optimizer
+  - AdamW optimizer (with decoupled weight decay)
+  - Learning rate scheduler (warmup + cosine decay)
+
+- **TypeScript Support**: Full type definitions and modern API
+
+## Installation
+
+```bash
+npm install ruvector-attention-wasm
+```
+
+## Usage
+
+### TypeScript/JavaScript
+
+```typescript
+import { initialize, MultiHeadAttention, utils } from 'ruvector-attention-wasm';
+
+// Initialize WASM module
+await initialize();
+
+// Create multi-head attention
+const attention = new MultiHeadAttention({ dim: 64, numHeads: 8 });
+
+// Prepare inputs
+const query = new Float32Array(64);
+const keys = [new Float32Array(64), new Float32Array(64)];
+const values = [new Float32Array(64), new Float32Array(64)];
+
+// Compute attention
+const output = attention.compute(query, keys, values);
+
+// Use utilities
+const similarity = utils.cosineSimilarity(query, keys[0]);
+```
+
+### Advanced Examples
+
+#### Hyperbolic Attention
+
+```typescript
+import { HyperbolicAttention } from 'ruvector-attention-wasm';
+
+const hyperbolic = new HyperbolicAttention({
+  dim: 128,
+  curvature: 1.0
+});
+
+const output = hyperbolic.compute(query, keys, values);
+```
+
+#### MoE Attention with Expert Stats
+
+```typescript
+import { MoEAttention } from 'ruvector-attention-wasm';
+
+const moe = new MoEAttention({
+  dim: 64,
+  numExperts: 4,
+  topK: 2
+});
+
+const output = moe.compute(query, keys, values);
+
+// Get expert utilization
+const stats = moe.getExpertStats();
+console.log('Load balance:', stats.loadBalance);
+```
+
+#### Training with InfoNCE Loss
+
+```typescript
+import { InfoNCELoss, Adam } from 'ruvector-attention-wasm';
+
+const loss = new InfoNCELoss(0.07);
+const optimizer = new Adam(paramCount, {
+  learningRate: 0.001,
+  beta1: 0.9,
+  beta2: 0.999,
+});
+
+// Training loop
+const lossValue = loss.compute(anchor, positive, negatives);
+optimizer.step(params, gradients);
+```
+
+#### Learning Rate Scheduling
+
+```typescript
+import { LRScheduler, AdamW } from 'ruvector-attention-wasm';
+
+const scheduler = new LRScheduler({
+  initialLR: 0.001,
+  warmupSteps: 1000,
+  totalSteps: 10000,
+});
+
+const optimizer = new AdamW(paramCount, {
+  learningRate: scheduler.getLR(),
+  weightDecay: 0.01,
+});
+
+// Training loop
+for (let step = 0; step < 10000; step++) {
+  optimizer.learningRate = scheduler.getLR();
+  optimizer.step(params, gradients);
+  scheduler.step();
+}
+```
+
+## Building from Source
+
+### Prerequisites
+
+- Rust 1.70+
+- wasm-pack
+
+### Build Commands
+
+```bash
+# Build for web (ES modules)
+wasm-pack build --target web --out-dir pkg
+
+# Build for Node.js
+wasm-pack build --target nodejs --out-dir pkg-node
+
+# Build for bundlers (webpack, vite, etc.)
+wasm-pack build --target bundler --out-dir pkg-bundler
+
+# Run tests
+wasm-pack test --headless --firefox
+```
+
+## API Reference
+
+### Attention Mechanisms
+
+- `MultiHeadAttention` - Standard multi-head attention
+- `HyperbolicAttention` - Attention in hyperbolic space
+- `LinearAttention` - Linear complexity attention (Performer)
+- `FlashAttention` - Memory-efficient attention
+- `LocalGlobalAttention` - Combined local and global attention
+- `MoEAttention` - Mixture of Experts attention
+- `CGTSheafAttention` - Coherence-gated via Prime-Radiant energy
+- `scaledDotAttention()` - Functional API for basic attention
+
+### CGT Sheaf Attention (Prime-Radiant Integration)
+
+The CGT (Coherence-Gated Transformer) Sheaf Attention mechanism uses Prime-Radiant's sheaf Laplacian energy to gate attention based on mathematical consistency:
+
+```typescript
+import { CGTSheafAttention } from 'ruvector-attention-wasm';
+
+const cgtAttention = new CGTSheafAttention({
+  dim: 128,
+  numHeads: 8,
+  coherenceThreshold: 0.3,  // Block if energy > threshold
+});
+
+// Attention is gated by coherence energy
+const result = cgtAttention.compute(query, keys, values);
+console.log('Coherence energy:', result.energy);
+console.log('Is coherent:', result.isCoherent);
+```
+
+**Key features:**
+- Energy-weighted attention: Lower coherence energy → higher attention
+- Automatic hallucination detection via residual analysis
+- GPU-accelerated with wgpu WGSL shaders (vec4 optimized)
+- SIMD fallback (AVX-512/AVX2/NEON)
+
+### Training
+
+- `InfoNCELoss` - Contrastive loss function
+- `Adam` - Adam optimizer
+- `AdamW` - AdamW optimizer with weight decay
+- `LRScheduler` - Learning rate scheduler
+
+### Utilities
+
+- `utils.cosineSimilarity()` - Cosine similarity between vectors
+- `utils.l2Norm()` - L2 norm of a vector
+- `utils.normalize()` - Normalize vector to unit length
+- `utils.softmax()` - Apply softmax transformation
+- `utils.attentionWeights()` - Compute attention weights from scores
+- `utils.batchNormalize()` - Batch normalization
+- `utils.randomOrthogonalMatrix()` - Generate random orthogonal matrix
+- `utils.pairwiseDistances()` - Compute pairwise distances
+
+## Performance
+
+The WASM bindings provide near-native performance for attention computations:
+
+- Optimized with `opt-level = "s"` and LTO
+- SIMD acceleration where available
+- Efficient memory management
+- Zero-copy data transfer where possible
+
+## License
+
+MIT OR Apache-2.0
diff --git a/ui/pose-fusion/pkg/ruvector-attention/package.json b/ui/pose-fusion/pkg/ruvector-attention/package.json
new file mode 100644
index 00000000..7500bb8a
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/package.json
@@ -0,0 +1,28 @@
+{
+  "name": "ruvector-attention-wasm",
+  "collaborators": [
+    "Ruvector Team"
+  ],
+  "description": "High-performance WebAssembly attention mechanisms: Multi-Head, Flash, Hyperbolic, MoE, CGT Sheaf Attention with GPU acceleration for transformers and LLMs",
+  "version": "2.0.5",
+  "license": "MIT",
+  "repository": {
+    "type": "git",
+    "url": "https://github.com/ruvnet/ruvector"
+  },
+  "files": [
+    "ruvector_attention_wasm_bg.wasm",
+    "ruvector_attention_wasm.js",
+    "ruvector_attention_wasm.d.ts"
+  ],
+  "main": "ruvector_attention_wasm.js",
+  "homepage": "https://ruv.io/ruvector",
+  "types": "ruvector_attention_wasm.d.ts",
+  "keywords": [
+    "wasm",
+    "attention",
+    "transformer",
+    "flash-attention",
+    "llm"
+  ]
+}
\ No newline at end of file
diff --git a/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_browser.js b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_browser.js
new file mode 100644
index 00000000..b4697175
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_browser.js
@@ -0,0 +1,483 @@
+/**
+ * Browser ESM wrapper for ruvector-attention-wasm v2.0.5
+ *
+ * The upstream pkg/ was built with wasm-pack --target nodejs (CJS + fs.readFileSync).
+ * This wrapper loads the same WASM binary via fetch() for browser use.
+ *
+ * Usage:
+ *   import initWasm, { WasmMultiHeadAttention, ... } from './ruvector_attention_browser.js';
+ *   await initWasm();
+ *   const attn = new WasmMultiHeadAttention(dim, heads);
+ */
+
+let _wasm;
+let _initialized = false;
+
+// The entire CJS module runs inside this IIFE to avoid polluting global scope.
+// We capture all exports in _mod.
+const _mod = {};
+
+(function(exports, wasm_getter) {
+
+// ── wasm-bindgen heap management ──────────────────────────────────
+const heap = new Array(128).fill(undefined);
+heap.push(undefined, null, true, false);
+let heap_next = heap.length;
+
+function addHeapObject(obj) {
+  if (heap_next === heap.length) heap.push(heap.length + 1);
+  const idx = heap_next;
+  heap_next = heap[idx];
+  heap[idx] = obj;
+  return idx;
+}
+function getObject(idx) { return heap[idx]; }
+function dropObject(idx) {
+  if (idx < 132) return;
+  heap[idx] = heap_next;
+  heap_next = idx;
+}
+function takeObject(idx) {
+  const ret = getObject(idx);
+  dropObject(idx);
+  return ret;
+}
+function isLikeNone(x) { return x === undefined || x === null; }
+
+// ── Memory views ──────────────────────────────────────────────────
+let cachedDataViewMemory0 = null;
+let cachedUint8ArrayMemory0 = null;
+let cachedFloat32ArrayMemory0 = null;
+
+function wasm() { return wasm_getter(); }
+
+function getDataViewMemory0() {
+  if (cachedDataViewMemory0 === null || cachedDataViewMemory0.buffer !== wasm().memory.buffer)
+    cachedDataViewMemory0 = new DataView(wasm().memory.buffer);
+  return cachedDataViewMemory0;
+}
+function getUint8ArrayMemory0() {
+  if (cachedUint8ArrayMemory0 === null || cachedUint8ArrayMemory0.buffer !== wasm().memory.buffer)
+    cachedUint8ArrayMemory0 = new Uint8Array(wasm().memory.buffer);
+  return cachedUint8ArrayMemory0;
+}
+function getFloat32ArrayMemory0() {
+  if (cachedFloat32ArrayMemory0 === null || cachedFloat32ArrayMemory0.buffer !== wasm().memory.buffer)
+    cachedFloat32ArrayMemory0 = new Float32Array(wasm().memory.buffer);
+  return cachedFloat32ArrayMemory0;
+}
+function getArrayF32FromWasm0(ptr, len) {
+  ptr = ptr >>> 0;
+  return getFloat32ArrayMemory0().subarray(ptr / 4, ptr / 4 + len);
+}
+function getArrayU8FromWasm0(ptr, len) {
+  ptr = ptr >>> 0;
+  return getUint8ArrayMemory0().subarray(ptr, ptr + len);
+}
+
+let WASM_VECTOR_LEN = 0;
+
+function passArrayF32ToWasm0(arg, malloc) {
+  const ptr = malloc(arg.length * 4, 4) >>> 0;
+  getFloat32ArrayMemory0().set(arg, ptr / 4);
+  WASM_VECTOR_LEN = arg.length;
+  return ptr;
+}
+
+const cachedTextEncoder = new TextEncoder();
+const cachedTextDecoder = new TextDecoder('utf-8', { ignoreBOM: true, fatal: true });
+cachedTextDecoder.decode();
+
+function getStringFromWasm0(ptr, len) {
+  ptr = ptr >>> 0;
+  return cachedTextDecoder.decode(getUint8ArrayMemory0().subarray(ptr, ptr + len));
+}
+
+function passStringToWasm0(arg, malloc, realloc) {
+  const buf = cachedTextEncoder.encode(arg);
+  const ptr = malloc(buf.length, 1) >>> 0;
+  getUint8ArrayMemory0().subarray(ptr, ptr + buf.length).set(buf);
+  WASM_VECTOR_LEN = buf.length;
+  return ptr;
+}
+
+function debugString(val) {
+  const type = typeof val;
+  if (type == 'number' || type == 'boolean' || val == null) return `${val}`;
+  if (type == 'string') return `"${val}"`;
+  if (type == 'symbol') return val.description ? `Symbol(${val.description})` : 'Symbol';
+  if (type == 'function') return 'Function';
+  if (Array.isArray(val)) return `[${val.map(debugString).join(', ')}]`;
+  try {
+    const keys = Object.keys(val);
+    return `{${keys.map(k => `${k}: ${debugString(val[k])}`).join(', ')}}`;
+  } catch (_) { return Object.prototype.toString.call(val); }
+}
+
+function handleError(f, args) {
+  try { return f.apply(this, args); }
+  catch (e) { wasm().__wbindgen_export3(addHeapObject(e)); }
+}
+
+// ── FinalizationRegistry ──────────────────────────────────────────
+const FR = typeof FinalizationRegistry !== 'undefined'
+  ? FinalizationRegistry
+  : class { register() {} unregister() {} };
+
+const WasmMultiHeadAttentionFinalization = new FR(ptr => wasm().__wbg_wasmmultiheadattention_free(ptr >>> 0, 1));
+const WasmFlashAttentionFinalization = new FR(ptr => wasm().__wbg_wasmflashattention_free(ptr >>> 0, 1));
+const WasmHyperbolicAttentionFinalization = new FR(ptr => wasm().__wbg_wasmhyperbolicattention_free(ptr >>> 0, 1));
+const WasmMoEAttentionFinalization = new FR(ptr => wasm().__wbg_wasmmoeattention_free(ptr >>> 0, 1));
+const WasmLinearAttentionFinalization = new FR(ptr => wasm().__wbg_wasmlinearattention_free(ptr >>> 0, 1));
+const WasmLocalGlobalAttentionFinalization = new FR(ptr => wasm().__wbg_wasmlocalglobalattention_free(ptr >>> 0, 1));
+
+// ── Classes ───────────────────────────────────────────────────────
+
+class WasmMultiHeadAttention {
+  constructor(dim, num_heads) {
+    const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+    try {
+      wasm().wasmmultiheadattention_new(retptr, dim, num_heads);
+      var r0 = getDataViewMemory0().getInt32(retptr + 0, true);
+      var r1 = getDataViewMemory0().getInt32(retptr + 4, true);
+      var r2 = getDataViewMemory0().getInt32(retptr + 8, true);
+      if (r2) throw takeObject(r1);
+      this.__wbg_ptr = r0 >>> 0;
+      WasmMultiHeadAttentionFinalization.register(this, this.__wbg_ptr, this);
+    } finally {
+      wasm().__wbindgen_add_to_stack_pointer(16);
+    }
+  }
+  free() {
+    const ptr = this.__wbg_ptr; this.__wbg_ptr = 0;
+    WasmMultiHeadAttentionFinalization.unregister(this);
+    wasm().__wbg_wasmmultiheadattention_free(ptr, 0);
+  }
+  get dim() { return wasm().wasmmultiheadattention_dim(this.__wbg_ptr); }
+  get num_heads() { return wasm().wasmmultiheadattention_num_heads(this.__wbg_ptr); }
+  compute(query, keys, values) {
+    const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+    try {
+      const ptr0 = passArrayF32ToWasm0(query, wasm().__wbindgen_export);
+      const len0 = WASM_VECTOR_LEN;
+      wasm().wasmmultiheadattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+      var r0 = getDataViewMemory0().getInt32(retptr + 0, true);
+      var r1 = getDataViewMemory0().getInt32(retptr + 4, true);
+      var r2 = getDataViewMemory0().getInt32(retptr + 8, true);
+      var r3 = getDataViewMemory0().getInt32(retptr + 12, true);
+      if (r3) throw takeObject(r2);
+      var v1 = getArrayF32FromWasm0(r0, r1).slice();
+      wasm().__wbindgen_export4(r0, r1 * 4, 4);
+      return v1;
+    } finally {
+      wasm().__wbindgen_add_to_stack_pointer(16);
+    }
+  }
+}
+
+class WasmFlashAttention {
+  constructor(dim, block_size) {
+    const ret = wasm().wasmflashattention_new(dim, block_size);
+    this.__wbg_ptr = ret >>> 0;
+    WasmFlashAttentionFinalization.register(this, this.__wbg_ptr, this);
+  }
+  free() {
+    const ptr = this.__wbg_ptr; this.__wbg_ptr = 0;
+    WasmFlashAttentionFinalization.unregister(this);
+    wasm().__wbg_wasmflashattention_free(ptr, 0);
+  }
+  compute(query, keys, values) {
+    const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+    try {
+      const ptr0 = passArrayF32ToWasm0(query, wasm().__wbindgen_export);
+      const len0 = WASM_VECTOR_LEN;
+      wasm().wasmflashattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+      var r0 = getDataViewMemory0().getInt32(retptr + 0, true);
+      var r1 = getDataViewMemory0().getInt32(retptr + 4, true);
+      var r2 = getDataViewMemory0().getInt32(retptr + 8, true);
+      var r3 = getDataViewMemory0().getInt32(retptr + 12, true);
+      if (r3) throw takeObject(r2);
+      var v1 = getArrayF32FromWasm0(r0, r1).slice();
+      wasm().__wbindgen_export4(r0, r1 * 4, 4);
+      return v1;
+    } finally {
+      wasm().__wbindgen_add_to_stack_pointer(16);
+    }
+  }
+}
+
+class WasmHyperbolicAttention {
+  constructor(dim, curvature) {
+    const ret = wasm().wasmhyperbolicattention_new(dim, curvature);
+    this.__wbg_ptr = ret >>> 0;
+    WasmHyperbolicAttentionFinalization.register(this, this.__wbg_ptr, this);
+  }
+  free() {
+    const ptr = this.__wbg_ptr; this.__wbg_ptr = 0;
+    WasmHyperbolicAttentionFinalization.unregister(this);
+    wasm().__wbg_wasmhyperbolicattention_free(ptr, 0);
+  }
+  get curvature() { return wasm().wasmhyperbolicattention_curvature(this.__wbg_ptr); }
+  compute(query, keys, values) {
+    const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+    try {
+      const ptr0 = passArrayF32ToWasm0(query, wasm().__wbindgen_export);
+      const len0 = WASM_VECTOR_LEN;
+      wasm().wasmhyperbolicattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+      var r0 = getDataViewMemory0().getInt32(retptr + 0, true);
+      var r1 = getDataViewMemory0().getInt32(retptr + 4, true);
+      var r2 = getDataViewMemory0().getInt32(retptr + 8, true);
+      var r3 = getDataViewMemory0().getInt32(retptr + 12, true);
+      if (r3) throw takeObject(r2);
+      var v1 = getArrayF32FromWasm0(r0, r1).slice();
+      wasm().__wbindgen_export4(r0, r1 * 4, 4);
+      return v1;
+    } finally {
+      wasm().__wbindgen_add_to_stack_pointer(16);
+    }
+  }
+}
+
+class WasmMoEAttention {
+  constructor(dim, num_experts, top_k) {
+    const ret = wasm().wasmmoeattention_new(dim, num_experts, top_k);
+    this.__wbg_ptr = ret >>> 0;
+    WasmMoEAttentionFinalization.register(this, this.__wbg_ptr, this);
+  }
+  free() {
+    const ptr = this.__wbg_ptr; this.__wbg_ptr = 0;
+    WasmMoEAttentionFinalization.unregister(this);
+    wasm().__wbg_wasmmoeattention_free(ptr, 0);
+  }
+  compute(query, keys, values) {
+    const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+    try {
+      const ptr0 = passArrayF32ToWasm0(query, wasm().__wbindgen_export);
+      const len0 = WASM_VECTOR_LEN;
+      wasm().wasmmoeattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+      var r0 = getDataViewMemory0().getInt32(retptr + 0, true);
+      var r1 = getDataViewMemory0().getInt32(retptr + 4, true);
+      var r2 = getDataViewMemory0().getInt32(retptr + 8, true);
+      var r3 = getDataViewMemory0().getInt32(retptr + 12, true);
+      if (r3) throw takeObject(r2);
+      var v1 = getArrayF32FromWasm0(r0, r1).slice();
+      wasm().__wbindgen_export4(r0, r1 * 4, 4);
+      return v1;
+    } finally {
+      wasm().__wbindgen_add_to_stack_pointer(16);
+    }
+  }
+}
+
+// ── Standalone functions ──────────────────────────────────────────
+
+function cosine_similarity(a, b) {
+  const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+  try {
+    const ptr0 = passArrayF32ToWasm0(a, wasm().__wbindgen_export);
+    const len0 = WASM_VECTOR_LEN;
+    const ptr1 = passArrayF32ToWasm0(b, wasm().__wbindgen_export);
+    const len1 = WASM_VECTOR_LEN;
+    wasm().cosine_similarity(retptr, ptr0, len0, ptr1, len1);
+    var r0 = getDataViewMemory0().getFloat64(retptr + 0, true);
+    var r1 = getDataViewMemory0().getInt32(retptr + 8, true);
+    var r2 = getDataViewMemory0().getInt32(retptr + 12, true);
+    if (r2) throw takeObject(r1);
+    return r0;
+  } finally {
+    wasm().__wbindgen_add_to_stack_pointer(16);
+  }
+}
+
+function normalize(vec) {
+  const ptr0 = passArrayF32ToWasm0(vec, wasm().__wbindgen_export);
+  const len0 = WASM_VECTOR_LEN;
+  wasm().normalize(ptr0, len0, addHeapObject(vec));
+}
+
+function l2_norm(vec) {
+  const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+  try {
+    const ptr0 = passArrayF32ToWasm0(vec, wasm().__wbindgen_export);
+    const len0 = WASM_VECTOR_LEN;
+    wasm().l2_norm(retptr, ptr0, len0);
+    var r0 = getDataViewMemory0().getFloat64(retptr + 0, true);
+    var r1 = getDataViewMemory0().getInt32(retptr + 8, true);
+    var r2 = getDataViewMemory0().getInt32(retptr + 12, true);
+    if (r2) throw takeObject(r1);
+    return r0;
+  } finally {
+    wasm().__wbindgen_add_to_stack_pointer(16);
+  }
+}
+
+function softmax(vec) {
+  const ptr0 = passArrayF32ToWasm0(vec, wasm().__wbindgen_export);
+  const len0 = WASM_VECTOR_LEN;
+  wasm().softmax(ptr0, len0, addHeapObject(vec));
+}
+
+function rv_init() { wasm().init(); }
+
+function rv_version() {
+  let d0, d1;
+  const retptr = wasm().__wbindgen_add_to_stack_pointer(-16);
+  try {
+    wasm().version(retptr);
+    d0 = getDataViewMemory0().getInt32(retptr + 0, true);
+    d1 = getDataViewMemory0().getInt32(retptr + 4, true);
+    return getStringFromWasm0(d0, d1);
+  } finally {
+    wasm().__wbindgen_add_to_stack_pointer(16);
+    if (d0 !== undefined) wasm().__wbindgen_export4(d0, d1, 1);
+  }
+}
+
+// ── Collect exports ───────────────────────────────────────────────
+exports.WasmMultiHeadAttention = WasmMultiHeadAttention;
+exports.WasmFlashAttention = WasmFlashAttention;
+exports.WasmHyperbolicAttention = WasmHyperbolicAttention;
+exports.WasmMoEAttention = WasmMoEAttention;
+exports.cosine_similarity = cosine_similarity;
+exports.normalize = normalize;
+exports.l2_norm = l2_norm;
+exports.softmax = softmax;
+exports.init = rv_init;
+exports.version = rv_version;
+
+// ── Build WASM import object ──────────────────────────────────────
+exports.__wbg_get_imports = function() {
+  const import0 = {
+    __proto__: null,
+    __wbg_Error_4577686b3a6d9b3a: (arg0, arg1) => addHeapObject(Error(getStringFromWasm0(arg0, arg1))),
+    __wbg_String_8564e559799eccda: (arg0, arg1) => {
+      const ret = String(getObject(arg1));
+      const ptr1 = passStringToWasm0(ret, wasm().__wbindgen_export, wasm().__wbindgen_export2);
+      const len1 = WASM_VECTOR_LEN;
+      getDataViewMemory0().setInt32(arg0 + 4, len1, true);
+      getDataViewMemory0().setInt32(arg0, ptr1, true);
+    },
+    __wbg___wbindgen_boolean_get_18c4ed9422296fff: (arg0) => {
+      const v = getObject(arg0);
+      const ret = typeof v === 'boolean' ? v : undefined;
+      return isLikeNone(ret) ? 0xFFFFFF : ret ? 1 : 0;
+    },
+    __wbg___wbindgen_copy_to_typed_array_5294f8e46aecc086: (arg0, arg1, arg2) => {
+      new Uint8Array(getObject(arg2).buffer, getObject(arg2).byteOffset, getObject(arg2).byteLength).set(getArrayU8FromWasm0(arg0, arg1));
+    },
+    __wbg___wbindgen_debug_string_ddde1867f49c2442: (arg0, arg1) => {
+      const ret = debugString(getObject(arg1));
+      const ptr1 = passStringToWasm0(ret, wasm().__wbindgen_export, wasm().__wbindgen_export2);
+      const len1 = WASM_VECTOR_LEN;
+      getDataViewMemory0().setInt32(arg0 + 4, len1, true);
+      getDataViewMemory0().setInt32(arg0, ptr1, true);
+    },
+    __wbg___wbindgen_is_function_d633e708baf0d146: (arg0) => typeof getObject(arg0) === 'function',
+    __wbg___wbindgen_is_object_4b3de556756ee8a8: (arg0) => {
+      const val = getObject(arg0);
+      return typeof val === 'object' && val !== null;
+    },
+    __wbg___wbindgen_jsval_loose_eq_1562ceb9af84e990: (arg0, arg1) => getObject(arg0) == getObject(arg1),
+    __wbg___wbindgen_number_get_5854912275df1894: (arg0, arg1) => {
+      const obj = getObject(arg1);
+      const ret = typeof obj === 'number' ? obj : undefined;
+      getDataViewMemory0().setFloat64(arg0 + 8, isLikeNone(ret) ? 0 : ret, true);
+      getDataViewMemory0().setInt32(arg0, !isLikeNone(ret), true);
+    },
+    __wbg___wbindgen_string_get_3e5751597f39a112: (arg0, arg1) => {
+      const obj = getObject(arg1);
+      const ret = typeof obj === 'string' ? obj : undefined;
+      var ptr1 = isLikeNone(ret) ? 0 : passStringToWasm0(ret, wasm().__wbindgen_export, wasm().__wbindgen_export2);
+      var len1 = WASM_VECTOR_LEN;
+      getDataViewMemory0().setInt32(arg0 + 4, len1, true);
+      getDataViewMemory0().setInt32(arg0, ptr1, true);
+    },
+    __wbg___wbindgen_throw_39bc967c0e5a9b58: (arg0, arg1) => { throw new Error(getStringFromWasm0(arg0, arg1)); },
+    __wbg_call_73af281463ec8b58: function() { return handleError(function(arg0, arg1) {
+      return addHeapObject(getObject(arg0).call(getObject(arg1)));
+    }, arguments); },
+    __wbg_done_5aad55ec6b1954b1: (arg0) => getObject(arg0).done,
+    __wbg_error_a6fa202b58aa1cd3: (arg0, arg1) => {
+      try { console.error(getStringFromWasm0(arg0, arg1)); }
+      finally { wasm().__wbindgen_export4(arg0, arg1, 1); }
+    },
+    __wbg_error_ad28debb48b5c6bb: (arg0) => console.error(getObject(arg0)),
+    __wbg_get_4920fefd3451364b: function() { return handleError(function(arg0, arg1) {
+      return addHeapObject(Reflect.get(getObject(arg0), getObject(arg1)));
+    }, arguments); },
+    __wbg_get_unchecked_3d0f4b91c8eca4f0: (arg0, arg1) => addHeapObject(getObject(arg0)[arg1 >>> 0]),
+    __wbg_instanceof_ArrayBuffer_15859862b80b732d: (arg0) => {
+      try { return getObject(arg0) instanceof ArrayBuffer; } catch (_) { return false; }
+    },
+    __wbg_instanceof_Uint8Array_2240b7046ac16f05: (arg0) => {
+      try { return getObject(arg0) instanceof Uint8Array; } catch (_) { return false; }
+    },
+    __wbg_isArray_fad08a0d12828686: (arg0) => Array.isArray(getObject(arg0)),
+    __wbg_iterator_fc7ad8d33bab9e26: () => addHeapObject(Symbol.iterator),
+    __wbg_length_5855c1f289dfffc1: (arg0) => getObject(arg0).length,
+    __wbg_length_a31e05262e09b7f8: (arg0) => getObject(arg0).length,
+    __wbg_log_3c5e4b64af29e724: (arg0) => console.log(getObject(arg0)),
+    __wbg_new_09959f7b4c92c246: (arg0) => addHeapObject(new Uint8Array(getObject(arg0))),
+    __wbg_new_227d7c05414eb861: () => addHeapObject(new Error()),
+    __wbg_new_cbee8c0d5c479eac: () => addHeapObject(new Array()),
+    __wbg_next_a5fe6f328f7affc2: (arg0) => addHeapObject(getObject(arg0).next),
+    __wbg_next_e592122bb4ed4c67: function() { return handleError(function(arg0) {
+      return addHeapObject(getObject(arg0).next());
+    }, arguments); },
+    __wbg_prototypesetcall_f034d444741426c3: (arg0, arg1, arg2) => {
+      Uint8Array.prototype.set.call(getArrayU8FromWasm0(arg0, arg1), getObject(arg2));
+    },
+    __wbg_random_2b7bed8995d680fb: () => Math.random(),
+    __wbg_set_4c81cfb5dc3a333c: (arg0, arg1, arg2) => { getObject(arg0)[arg1 >>> 0] = takeObject(arg2); },
+    __wbg_stack_3b0d974bbf31e44f: (arg0, arg1) => {
+      const ret = getObject(arg1).stack;
+      const ptr1 = passStringToWasm0(ret, wasm().__wbindgen_export, wasm().__wbindgen_export2);
+      const len1 = WASM_VECTOR_LEN;
+      getDataViewMemory0().setInt32(arg0 + 4, len1, true);
+      getDataViewMemory0().setInt32(arg0, ptr1, true);
+    },
+    __wbg_value_667dcb90597486a6: (arg0) => addHeapObject(getObject(arg0).value),
+    __wbindgen_cast_0000000000000001: (arg0, arg1) => addHeapObject(getStringFromWasm0(arg0, arg1)),
+    __wbindgen_object_drop_ref: (arg0) => takeObject(arg0),
+  };
+  return { __proto__: null, "./ruvector_attention_wasm_bg.js": import0 };
+};
+
+})(_mod, () => _wasm);
+
+
+// ── Async WASM init (fetch-based for browsers) ───────────────────
+
+export default async function initWasm() {
+  if (_initialized) return;
+  const wasmUrl = new URL('ruvector_attention_wasm_bg.wasm', import.meta.url);
+  const imports = _mod.__wbg_get_imports();
+  let result;
+  if (typeof WebAssembly.instantiateStreaming === 'function') {
+    try {
+      result = await WebAssembly.instantiateStreaming(fetch(wasmUrl), imports);
+    } catch (e) {
+      // Fallback if streaming fails (e.g. wrong MIME type)
+      const bytes = await (await fetch(wasmUrl)).arrayBuffer();
+      result = await WebAssembly.instantiate(bytes, imports);
+    }
+  } else {
+    const bytes = await (await fetch(wasmUrl)).arrayBuffer();
+    result = await WebAssembly.instantiate(bytes, imports);
+  }
+  _wasm = result.instance.exports;
+  _wasm.__wbindgen_start();
+  _initialized = true;
+}
+
+// ── ESM re-exports ────────────────────────────────────────────────
+export const WasmMultiHeadAttention = _mod.WasmMultiHeadAttention;
+export const WasmFlashAttention = _mod.WasmFlashAttention;
+export const WasmHyperbolicAttention = _mod.WasmHyperbolicAttention;
+export const WasmMoEAttention = _mod.WasmMoEAttention;
+export const cosine_similarity = _mod.cosine_similarity;
+export const normalize = _mod.normalize;
+export const l2_norm = _mod.l2_norm;
+export const softmax = _mod.softmax;
+export const init = _mod.init;
+export const version = _mod.version;
diff --git a/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.d.ts b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.d.ts
new file mode 100644
index 00000000..90c7dc99
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.d.ts
@@ -0,0 +1,359 @@
+/* tslint:disable */
+/* eslint-disable */
+
+/**
+ * Adam optimizer
+ */
+export class WasmAdam {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new Adam optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     */
+    constructor(param_count: number, learning_rate: number);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step
+     *
+     * # Arguments
+     * * `params` - Current parameter values (will be updated in-place)
+     * * `gradients` - Gradient values
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+}
+
+/**
+ * AdamW optimizer (Adam with decoupled weight decay)
+ */
+export class WasmAdamW {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new AdamW optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `weight_decay` - Weight decay coefficient
+     */
+    constructor(param_count: number, learning_rate: number, weight_decay: number);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step with weight decay
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+    /**
+     * Get weight decay
+     */
+    readonly weight_decay: number;
+}
+
+/**
+ * Flash attention mechanism
+ */
+export class WasmFlashAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute flash attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new flash attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `block_size` - Block size for tiling
+     */
+    constructor(dim: number, block_size: number);
+}
+
+/**
+ * Hyperbolic attention mechanism
+ */
+export class WasmHyperbolicAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute hyperbolic attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new hyperbolic attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `curvature` - Hyperbolic curvature parameter
+     */
+    constructor(dim: number, curvature: number);
+    /**
+     * Get the curvature
+     */
+    readonly curvature: number;
+}
+
+/**
+ * InfoNCE contrastive loss for training
+ */
+export class WasmInfoNCELoss {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute InfoNCE loss
+     *
+     * # Arguments
+     * * `anchor` - Anchor embedding
+     * * `positive` - Positive example embedding
+     * * `negatives` - Array of negative example embeddings
+     */
+    compute(anchor: Float32Array, positive: Float32Array, negatives: any): number;
+    /**
+     * Create a new InfoNCE loss instance
+     *
+     * # Arguments
+     * * `temperature` - Temperature parameter for softmax
+     */
+    constructor(temperature: number);
+}
+
+/**
+ * Learning rate scheduler
+ */
+export class WasmLRScheduler {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Get learning rate for current step
+     */
+    get_lr(): number;
+    /**
+     * Create a new learning rate scheduler with warmup and cosine decay
+     *
+     * # Arguments
+     * * `initial_lr` - Initial learning rate
+     * * `warmup_steps` - Number of warmup steps
+     * * `total_steps` - Total training steps
+     */
+    constructor(initial_lr: number, warmup_steps: number, total_steps: number);
+    /**
+     * Reset scheduler
+     */
+    reset(): void;
+    /**
+     * Advance to next step
+     */
+    step(): void;
+}
+
+/**
+ * Linear attention (Performer-style)
+ */
+export class WasmLinearAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute linear attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new linear attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_features` - Number of random features
+     */
+    constructor(dim: number, num_features: number);
+}
+
+/**
+ * Local-global attention mechanism
+ */
+export class WasmLocalGlobalAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute local-global attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new local-global attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `local_window` - Size of local attention window
+     * * `global_tokens` - Number of global attention tokens
+     */
+    constructor(dim: number, local_window: number, global_tokens: number);
+}
+
+/**
+ * Mixture of Experts (MoE) attention
+ */
+export class WasmMoEAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute MoE attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new MoE attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_experts` - Number of expert attention mechanisms
+     * * `top_k` - Number of experts to use per query
+     */
+    constructor(dim: number, num_experts: number, top_k: number);
+}
+
+/**
+ * Multi-head attention mechanism
+ */
+export class WasmMultiHeadAttention {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Compute multi-head attention
+     */
+    compute(query: Float32Array, keys: any, values: any): Float32Array;
+    /**
+     * Create a new multi-head attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_heads` - Number of attention heads
+     */
+    constructor(dim: number, num_heads: number);
+    /**
+     * Get the dimension
+     */
+    readonly dim: number;
+    /**
+     * Get the number of heads
+     */
+    readonly num_heads: number;
+}
+
+/**
+ * SGD optimizer with momentum
+ */
+export class WasmSGD {
+    free(): void;
+    [Symbol.dispose](): void;
+    /**
+     * Create a new SGD optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `momentum` - Momentum coefficient (default: 0)
+     */
+    constructor(param_count: number, learning_rate: number, momentum?: number | null);
+    /**
+     * Reset optimizer state
+     */
+    reset(): void;
+    /**
+     * Perform optimization step
+     */
+    step(params: Float32Array, gradients: Float32Array): void;
+    /**
+     * Get current learning rate
+     */
+    learning_rate: number;
+}
+
+/**
+ * Compute attention weights from scores
+ */
+export function attention_weights(scores: Float32Array, temperature?: number | null): void;
+
+/**
+ * Get information about available attention mechanisms
+ */
+export function available_mechanisms(): any;
+
+/**
+ * Batch normalize vectors
+ */
+export function batch_normalize(vectors: any, epsilon?: number | null): Float32Array;
+
+/**
+ * Compute cosine similarity between two vectors
+ */
+export function cosine_similarity(a: Float32Array, b: Float32Array): number;
+
+/**
+ * Initialize the WASM module with panic hook
+ */
+export function init(): void;
+
+/**
+ * Compute L2 norm of a vector
+ */
+export function l2_norm(vec: Float32Array): number;
+
+/**
+ * Log a message to the browser console
+ */
+export function log(message: string): void;
+
+/**
+ * Log an error to the browser console
+ */
+export function log_error(message: string): void;
+
+/**
+ * Normalize a vector to unit length
+ */
+export function normalize(vec: Float32Array): void;
+
+/**
+ * Compute pairwise distances between vectors
+ */
+export function pairwise_distances(vectors: any): Float32Array;
+
+/**
+ * Generate random orthogonal matrix (for initialization)
+ */
+export function random_orthogonal_matrix(dim: number): Float32Array;
+
+/**
+ * Compute scaled dot-product attention
+ *
+ * # Arguments
+ * * `query` - Query vector as Float32Array
+ * * `keys` - Array of key vectors
+ * * `values` - Array of value vectors
+ * * `scale` - Optional scaling factor (defaults to 1/sqrt(dim))
+ */
+export function scaled_dot_attention(query: Float32Array, keys: any, values: any, scale?: number | null): Float32Array;
+
+/**
+ * Compute softmax of a vector
+ */
+export function softmax(vec: Float32Array): void;
+
+/**
+ * Get the version of the ruvector-attention-wasm crate
+ */
+export function version(): string;
diff --git a/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.js b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.js
new file mode 100644
index 00000000..875532dc
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm.js
@@ -0,0 +1,1417 @@
+/* @ts-self-types="./ruvector_attention_wasm.d.ts" */
+
+/**
+ * Adam optimizer
+ */
+class WasmAdam {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmAdamFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmadam_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmadam_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new Adam optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * @param {number} param_count
+     * @param {number} learning_rate
+     */
+    constructor(param_count, learning_rate) {
+        const ret = wasm.wasmadam_new(param_count, learning_rate);
+        this.__wbg_ptr = ret >>> 0;
+        WasmAdamFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmadam_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmadam_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step
+     *
+     * # Arguments
+     * * `params` - Current parameter values (will be updated in-place)
+     * * `gradients` - Gradient values
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmadam_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+}
+if (Symbol.dispose) WasmAdam.prototype[Symbol.dispose] = WasmAdam.prototype.free;
+exports.WasmAdam = WasmAdam;
+
+/**
+ * AdamW optimizer (Adam with decoupled weight decay)
+ */
+class WasmAdamW {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmAdamWFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmadamw_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmadamw_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new AdamW optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `weight_decay` - Weight decay coefficient
+     * @param {number} param_count
+     * @param {number} learning_rate
+     * @param {number} weight_decay
+     */
+    constructor(param_count, learning_rate, weight_decay) {
+        const ret = wasm.wasmadamw_new(param_count, learning_rate, weight_decay);
+        this.__wbg_ptr = ret >>> 0;
+        WasmAdamWFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmadamw_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmadamw_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step with weight decay
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmadamw_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+    /**
+     * Get weight decay
+     * @returns {number}
+     */
+    get weight_decay() {
+        const ret = wasm.wasmadamw_weight_decay(this.__wbg_ptr);
+        return ret;
+    }
+}
+if (Symbol.dispose) WasmAdamW.prototype[Symbol.dispose] = WasmAdamW.prototype.free;
+exports.WasmAdamW = WasmAdamW;
+
+/**
+ * Flash attention mechanism
+ */
+class WasmFlashAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmFlashAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmflashattention_free(ptr, 0);
+    }
+    /**
+     * Compute flash attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmflashattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new flash attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `block_size` - Block size for tiling
+     * @param {number} dim
+     * @param {number} block_size
+     */
+    constructor(dim, block_size) {
+        const ret = wasm.wasmflashattention_new(dim, block_size);
+        this.__wbg_ptr = ret >>> 0;
+        WasmFlashAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmFlashAttention.prototype[Symbol.dispose] = WasmFlashAttention.prototype.free;
+exports.WasmFlashAttention = WasmFlashAttention;
+
+/**
+ * Hyperbolic attention mechanism
+ */
+class WasmHyperbolicAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmHyperbolicAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmhyperbolicattention_free(ptr, 0);
+    }
+    /**
+     * Compute hyperbolic attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmhyperbolicattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the curvature
+     * @returns {number}
+     */
+    get curvature() {
+        const ret = wasm.wasmhyperbolicattention_curvature(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new hyperbolic attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `curvature` - Hyperbolic curvature parameter
+     * @param {number} dim
+     * @param {number} curvature
+     */
+    constructor(dim, curvature) {
+        const ret = wasm.wasmhyperbolicattention_new(dim, curvature);
+        this.__wbg_ptr = ret >>> 0;
+        WasmHyperbolicAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmHyperbolicAttention.prototype[Symbol.dispose] = WasmHyperbolicAttention.prototype.free;
+exports.WasmHyperbolicAttention = WasmHyperbolicAttention;
+
+/**
+ * InfoNCE contrastive loss for training
+ */
+class WasmInfoNCELoss {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmInfoNCELossFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasminfonceloss_free(ptr, 0);
+    }
+    /**
+     * Compute InfoNCE loss
+     *
+     * # Arguments
+     * * `anchor` - Anchor embedding
+     * * `positive` - Positive example embedding
+     * * `negatives` - Array of negative example embeddings
+     * @param {Float32Array} anchor
+     * @param {Float32Array} positive
+     * @param {any} negatives
+     * @returns {number}
+     */
+    compute(anchor, positive, negatives) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(anchor, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            const ptr1 = passArrayF32ToWasm0(positive, wasm.__wbindgen_export);
+            const len1 = WASM_VECTOR_LEN;
+            wasm.wasminfonceloss_compute(retptr, this.__wbg_ptr, ptr0, len0, ptr1, len1, addHeapObject(negatives));
+            var r0 = getDataViewMemory0().getFloat32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            if (r2) {
+                throw takeObject(r1);
+            }
+            return r0;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new InfoNCE loss instance
+     *
+     * # Arguments
+     * * `temperature` - Temperature parameter for softmax
+     * @param {number} temperature
+     */
+    constructor(temperature) {
+        const ret = wasm.wasminfonceloss_new(temperature);
+        this.__wbg_ptr = ret >>> 0;
+        WasmInfoNCELossFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmInfoNCELoss.prototype[Symbol.dispose] = WasmInfoNCELoss.prototype.free;
+exports.WasmInfoNCELoss = WasmInfoNCELoss;
+
+/**
+ * Learning rate scheduler
+ */
+class WasmLRScheduler {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLRSchedulerFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlrscheduler_free(ptr, 0);
+    }
+    /**
+     * Get learning rate for current step
+     * @returns {number}
+     */
+    get_lr() {
+        const ret = wasm.wasmlrscheduler_get_lr(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new learning rate scheduler with warmup and cosine decay
+     *
+     * # Arguments
+     * * `initial_lr` - Initial learning rate
+     * * `warmup_steps` - Number of warmup steps
+     * * `total_steps` - Total training steps
+     * @param {number} initial_lr
+     * @param {number} warmup_steps
+     * @param {number} total_steps
+     */
+    constructor(initial_lr, warmup_steps, total_steps) {
+        const ret = wasm.wasmlrscheduler_new(initial_lr, warmup_steps, total_steps);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLRSchedulerFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset scheduler
+     */
+    reset() {
+        wasm.wasmlrscheduler_reset(this.__wbg_ptr);
+    }
+    /**
+     * Advance to next step
+     */
+    step() {
+        wasm.wasmlrscheduler_step(this.__wbg_ptr);
+    }
+}
+if (Symbol.dispose) WasmLRScheduler.prototype[Symbol.dispose] = WasmLRScheduler.prototype.free;
+exports.WasmLRScheduler = WasmLRScheduler;
+
+/**
+ * Linear attention (Performer-style)
+ */
+class WasmLinearAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLinearAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlinearattention_free(ptr, 0);
+    }
+    /**
+     * Compute linear attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmlinearattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new linear attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_features` - Number of random features
+     * @param {number} dim
+     * @param {number} num_features
+     */
+    constructor(dim, num_features) {
+        const ret = wasm.wasmlinearattention_new(dim, num_features);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLinearAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmLinearAttention.prototype[Symbol.dispose] = WasmLinearAttention.prototype.free;
+exports.WasmLinearAttention = WasmLinearAttention;
+
+/**
+ * Local-global attention mechanism
+ */
+class WasmLocalGlobalAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmLocalGlobalAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmlocalglobalattention_free(ptr, 0);
+    }
+    /**
+     * Compute local-global attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmlocalglobalattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new local-global attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `local_window` - Size of local attention window
+     * * `global_tokens` - Number of global attention tokens
+     * @param {number} dim
+     * @param {number} local_window
+     * @param {number} global_tokens
+     */
+    constructor(dim, local_window, global_tokens) {
+        const ret = wasm.wasmlocalglobalattention_new(dim, local_window, global_tokens);
+        this.__wbg_ptr = ret >>> 0;
+        WasmLocalGlobalAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmLocalGlobalAttention.prototype[Symbol.dispose] = WasmLocalGlobalAttention.prototype.free;
+exports.WasmLocalGlobalAttention = WasmLocalGlobalAttention;
+
+/**
+ * Mixture of Experts (MoE) attention
+ */
+class WasmMoEAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmMoEAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmmoeattention_free(ptr, 0);
+    }
+    /**
+     * Compute MoE attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmmoeattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Create a new MoE attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_experts` - Number of expert attention mechanisms
+     * * `top_k` - Number of experts to use per query
+     * @param {number} dim
+     * @param {number} num_experts
+     * @param {number} top_k
+     */
+    constructor(dim, num_experts, top_k) {
+        const ret = wasm.wasmmoeattention_new(dim, num_experts, top_k);
+        this.__wbg_ptr = ret >>> 0;
+        WasmMoEAttentionFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+}
+if (Symbol.dispose) WasmMoEAttention.prototype[Symbol.dispose] = WasmMoEAttention.prototype.free;
+exports.WasmMoEAttention = WasmMoEAttention;
+
+/**
+ * Multi-head attention mechanism
+ */
+class WasmMultiHeadAttention {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmMultiHeadAttentionFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmmultiheadattention_free(ptr, 0);
+    }
+    /**
+     * Compute multi-head attention
+     * @param {Float32Array} query
+     * @param {any} keys
+     * @param {any} values
+     * @returns {Float32Array}
+     */
+    compute(query, keys, values) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+            const len0 = WASM_VECTOR_LEN;
+            wasm.wasmmultiheadattention_compute(retptr, this.__wbg_ptr, ptr0, len0, addHeapObject(keys), addHeapObject(values));
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+            if (r3) {
+                throw takeObject(r2);
+            }
+            var v2 = getArrayF32FromWasm0(r0, r1).slice();
+            wasm.__wbindgen_export4(r0, r1 * 4, 4);
+            return v2;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the dimension
+     * @returns {number}
+     */
+    get dim() {
+        const ret = wasm.wasmmultiheadattention_dim(this.__wbg_ptr);
+        return ret >>> 0;
+    }
+    /**
+     * Create a new multi-head attention instance
+     *
+     * # Arguments
+     * * `dim` - Embedding dimension
+     * * `num_heads` - Number of attention heads
+     * @param {number} dim
+     * @param {number} num_heads
+     */
+    constructor(dim, num_heads) {
+        try {
+            const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+            wasm.wasmmultiheadattention_new(retptr, dim, num_heads);
+            var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+            var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+            var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+            if (r2) {
+                throw takeObject(r1);
+            }
+            this.__wbg_ptr = r0 >>> 0;
+            WasmMultiHeadAttentionFinalization.register(this, this.__wbg_ptr, this);
+            return this;
+        } finally {
+            wasm.__wbindgen_add_to_stack_pointer(16);
+        }
+    }
+    /**
+     * Get the number of heads
+     * @returns {number}
+     */
+    get num_heads() {
+        const ret = wasm.wasmmultiheadattention_num_heads(this.__wbg_ptr);
+        return ret >>> 0;
+    }
+}
+if (Symbol.dispose) WasmMultiHeadAttention.prototype[Symbol.dispose] = WasmMultiHeadAttention.prototype.free;
+exports.WasmMultiHeadAttention = WasmMultiHeadAttention;
+
+/**
+ * SGD optimizer with momentum
+ */
+class WasmSGD {
+    __destroy_into_raw() {
+        const ptr = this.__wbg_ptr;
+        this.__wbg_ptr = 0;
+        WasmSGDFinalization.unregister(this);
+        return ptr;
+    }
+    free() {
+        const ptr = this.__destroy_into_raw();
+        wasm.__wbg_wasmsgd_free(ptr, 0);
+    }
+    /**
+     * Get current learning rate
+     * @returns {number}
+     */
+    get learning_rate() {
+        const ret = wasm.wasmsgd_learning_rate(this.__wbg_ptr);
+        return ret;
+    }
+    /**
+     * Create a new SGD optimizer
+     *
+     * # Arguments
+     * * `param_count` - Number of parameters
+     * * `learning_rate` - Learning rate
+     * * `momentum` - Momentum coefficient (default: 0)
+     * @param {number} param_count
+     * @param {number} learning_rate
+     * @param {number | null} [momentum]
+     */
+    constructor(param_count, learning_rate, momentum) {
+        const ret = wasm.wasmsgd_new(param_count, learning_rate, isLikeNone(momentum) ? 0x100000001 : Math.fround(momentum));
+        this.__wbg_ptr = ret >>> 0;
+        WasmSGDFinalization.register(this, this.__wbg_ptr, this);
+        return this;
+    }
+    /**
+     * Reset optimizer state
+     */
+    reset() {
+        wasm.wasmsgd_reset(this.__wbg_ptr);
+    }
+    /**
+     * Set learning rate
+     * @param {number} lr
+     */
+    set learning_rate(lr) {
+        wasm.wasmsgd_set_learning_rate(this.__wbg_ptr, lr);
+    }
+    /**
+     * Perform optimization step
+     * @param {Float32Array} params
+     * @param {Float32Array} gradients
+     */
+    step(params, gradients) {
+        var ptr0 = passArrayF32ToWasm0(params, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(gradients, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.wasmsgd_step(this.__wbg_ptr, ptr0, len0, addHeapObject(params), ptr1, len1);
+    }
+}
+if (Symbol.dispose) WasmSGD.prototype[Symbol.dispose] = WasmSGD.prototype.free;
+exports.WasmSGD = WasmSGD;
+
+/**
+ * Compute attention weights from scores
+ * @param {Float32Array} scores
+ * @param {number | null} [temperature]
+ */
+function attention_weights(scores, temperature) {
+    var ptr0 = passArrayF32ToWasm0(scores, wasm.__wbindgen_export);
+    var len0 = WASM_VECTOR_LEN;
+    wasm.attention_weights(ptr0, len0, addHeapObject(scores), isLikeNone(temperature) ? 0x100000001 : Math.fround(temperature));
+}
+exports.attention_weights = attention_weights;
+
+/**
+ * Get information about available attention mechanisms
+ * @returns {any}
+ */
+function available_mechanisms() {
+    const ret = wasm.available_mechanisms();
+    return takeObject(ret);
+}
+exports.available_mechanisms = available_mechanisms;
+
+/**
+ * Batch normalize vectors
+ * @param {any} vectors
+ * @param {number | null} [epsilon]
+ * @returns {Float32Array}
+ */
+function batch_normalize(vectors, epsilon) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.batch_normalize(retptr, addHeapObject(vectors), isLikeNone(epsilon) ? 0x100000001 : Math.fround(epsilon));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.batch_normalize = batch_normalize;
+
+/**
+ * Compute cosine similarity between two vectors
+ * @param {Float32Array} a
+ * @param {Float32Array} b
+ * @returns {number}
+ */
+function cosine_similarity(a, b) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        const ptr0 = passArrayF32ToWasm0(a, wasm.__wbindgen_export);
+        const len0 = WASM_VECTOR_LEN;
+        const ptr1 = passArrayF32ToWasm0(b, wasm.__wbindgen_export);
+        const len1 = WASM_VECTOR_LEN;
+        wasm.cosine_similarity(retptr, ptr0, len0, ptr1, len1);
+        var r0 = getDataViewMemory0().getFloat32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        if (r2) {
+            throw takeObject(r1);
+        }
+        return r0;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.cosine_similarity = cosine_similarity;
+
+/**
+ * Initialize the WASM module with panic hook
+ */
+function init() {
+    wasm.init();
+}
+exports.init = init;
+
+/**
+ * Compute L2 norm of a vector
+ * @param {Float32Array} vec
+ * @returns {number}
+ */
+function l2_norm(vec) {
+    const ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+    const len0 = WASM_VECTOR_LEN;
+    const ret = wasm.l2_norm(ptr0, len0);
+    return ret;
+}
+exports.l2_norm = l2_norm;
+
+/**
+ * Log a message to the browser console
+ * @param {string} message
+ */
+function log(message) {
+    const ptr0 = passStringToWasm0(message, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+    const len0 = WASM_VECTOR_LEN;
+    wasm.log(ptr0, len0);
+}
+exports.log = log;
+
+/**
+ * Log an error to the browser console
+ * @param {string} message
+ */
+function log_error(message) {
+    const ptr0 = passStringToWasm0(message, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+    const len0 = WASM_VECTOR_LEN;
+    wasm.log_error(ptr0, len0);
+}
+exports.log_error = log_error;
+
+/**
+ * Normalize a vector to unit length
+ * @param {Float32Array} vec
+ */
+function normalize(vec) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        var ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+        var len0 = WASM_VECTOR_LEN;
+        wasm.normalize(retptr, ptr0, len0, addHeapObject(vec));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        if (r1) {
+            throw takeObject(r0);
+        }
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.normalize = normalize;
+
+/**
+ * Compute pairwise distances between vectors
+ * @param {any} vectors
+ * @returns {Float32Array}
+ */
+function pairwise_distances(vectors) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.pairwise_distances(retptr, addHeapObject(vectors));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.pairwise_distances = pairwise_distances;
+
+/**
+ * Generate random orthogonal matrix (for initialization)
+ * @param {number} dim
+ * @returns {Float32Array}
+ */
+function random_orthogonal_matrix(dim) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.random_orthogonal_matrix(retptr, dim);
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var v1 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v1;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.random_orthogonal_matrix = random_orthogonal_matrix;
+
+/**
+ * Compute scaled dot-product attention
+ *
+ * # Arguments
+ * * `query` - Query vector as Float32Array
+ * * `keys` - Array of key vectors
+ * * `values` - Array of value vectors
+ * * `scale` - Optional scaling factor (defaults to 1/sqrt(dim))
+ * @param {Float32Array} query
+ * @param {any} keys
+ * @param {any} values
+ * @param {number | null} [scale]
+ * @returns {Float32Array}
+ */
+function scaled_dot_attention(query, keys, values, scale) {
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        const ptr0 = passArrayF32ToWasm0(query, wasm.__wbindgen_export);
+        const len0 = WASM_VECTOR_LEN;
+        wasm.scaled_dot_attention(retptr, ptr0, len0, addHeapObject(keys), addHeapObject(values), isLikeNone(scale) ? 0x100000001 : Math.fround(scale));
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        var r2 = getDataViewMemory0().getInt32(retptr + 4 * 2, true);
+        var r3 = getDataViewMemory0().getInt32(retptr + 4 * 3, true);
+        if (r3) {
+            throw takeObject(r2);
+        }
+        var v2 = getArrayF32FromWasm0(r0, r1).slice();
+        wasm.__wbindgen_export4(r0, r1 * 4, 4);
+        return v2;
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+    }
+}
+exports.scaled_dot_attention = scaled_dot_attention;
+
+/**
+ * Compute softmax of a vector
+ * @param {Float32Array} vec
+ */
+function softmax(vec) {
+    var ptr0 = passArrayF32ToWasm0(vec, wasm.__wbindgen_export);
+    var len0 = WASM_VECTOR_LEN;
+    wasm.softmax(ptr0, len0, addHeapObject(vec));
+}
+exports.softmax = softmax;
+
+/**
+ * Get the version of the ruvector-attention-wasm crate
+ * @returns {string}
+ */
+function version() {
+    let deferred1_0;
+    let deferred1_1;
+    try {
+        const retptr = wasm.__wbindgen_add_to_stack_pointer(-16);
+        wasm.version(retptr);
+        var r0 = getDataViewMemory0().getInt32(retptr + 4 * 0, true);
+        var r1 = getDataViewMemory0().getInt32(retptr + 4 * 1, true);
+        deferred1_0 = r0;
+        deferred1_1 = r1;
+        return getStringFromWasm0(r0, r1);
+    } finally {
+        wasm.__wbindgen_add_to_stack_pointer(16);
+        wasm.__wbindgen_export4(deferred1_0, deferred1_1, 1);
+    }
+}
+exports.version = version;
+
+function __wbg_get_imports() {
+    const import0 = {
+        __proto__: null,
+        __wbg_Error_4577686b3a6d9b3a: function(arg0, arg1) {
+            const ret = Error(getStringFromWasm0(arg0, arg1));
+            return addHeapObject(ret);
+        },
+        __wbg_String_8564e559799eccda: function(arg0, arg1) {
+            const ret = String(getObject(arg1));
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_boolean_get_18c4ed9422296fff: function(arg0) {
+            const v = getObject(arg0);
+            const ret = typeof(v) === 'boolean' ? v : undefined;
+            return isLikeNone(ret) ? 0xFFFFFF : ret ? 1 : 0;
+        },
+        __wbg___wbindgen_copy_to_typed_array_5294f8e46aecc086: function(arg0, arg1, arg2) {
+            new Uint8Array(getObject(arg2).buffer, getObject(arg2).byteOffset, getObject(arg2).byteLength).set(getArrayU8FromWasm0(arg0, arg1));
+        },
+        __wbg___wbindgen_debug_string_ddde1867f49c2442: function(arg0, arg1) {
+            const ret = debugString(getObject(arg1));
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_is_function_d633e708baf0d146: function(arg0) {
+            const ret = typeof(getObject(arg0)) === 'function';
+            return ret;
+        },
+        __wbg___wbindgen_is_object_4b3de556756ee8a8: function(arg0) {
+            const val = getObject(arg0);
+            const ret = typeof(val) === 'object' && val !== null;
+            return ret;
+        },
+        __wbg___wbindgen_jsval_loose_eq_1562ceb9af84e990: function(arg0, arg1) {
+            const ret = getObject(arg0) == getObject(arg1);
+            return ret;
+        },
+        __wbg___wbindgen_number_get_5854912275df1894: function(arg0, arg1) {
+            const obj = getObject(arg1);
+            const ret = typeof(obj) === 'number' ? obj : undefined;
+            getDataViewMemory0().setFloat64(arg0 + 8 * 1, isLikeNone(ret) ? 0 : ret, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, !isLikeNone(ret), true);
+        },
+        __wbg___wbindgen_string_get_3e5751597f39a112: function(arg0, arg1) {
+            const obj = getObject(arg1);
+            const ret = typeof(obj) === 'string' ? obj : undefined;
+            var ptr1 = isLikeNone(ret) ? 0 : passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            var len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg___wbindgen_throw_39bc967c0e5a9b58: function(arg0, arg1) {
+            throw new Error(getStringFromWasm0(arg0, arg1));
+        },
+        __wbg_call_73af281463ec8b58: function() { return handleError(function (arg0, arg1) {
+            const ret = getObject(arg0).call(getObject(arg1));
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_done_5aad55ec6b1954b1: function(arg0) {
+            const ret = getObject(arg0).done;
+            return ret;
+        },
+        __wbg_error_a6fa202b58aa1cd3: function(arg0, arg1) {
+            let deferred0_0;
+            let deferred0_1;
+            try {
+                deferred0_0 = arg0;
+                deferred0_1 = arg1;
+                console.error(getStringFromWasm0(arg0, arg1));
+            } finally {
+                wasm.__wbindgen_export4(deferred0_0, deferred0_1, 1);
+            }
+        },
+        __wbg_error_ad28debb48b5c6bb: function(arg0) {
+            console.error(getObject(arg0));
+        },
+        __wbg_get_4920fefd3451364b: function() { return handleError(function (arg0, arg1) {
+            const ret = Reflect.get(getObject(arg0), getObject(arg1));
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_get_unchecked_3d0f4b91c8eca4f0: function(arg0, arg1) {
+            const ret = getObject(arg0)[arg1 >>> 0];
+            return addHeapObject(ret);
+        },
+        __wbg_instanceof_ArrayBuffer_15859862b80b732d: function(arg0) {
+            let result;
+            try {
+                result = getObject(arg0) instanceof ArrayBuffer;
+            } catch (_) {
+                result = false;
+            }
+            const ret = result;
+            return ret;
+        },
+        __wbg_instanceof_Uint8Array_2240b7046ac16f05: function(arg0) {
+            let result;
+            try {
+                result = getObject(arg0) instanceof Uint8Array;
+            } catch (_) {
+                result = false;
+            }
+            const ret = result;
+            return ret;
+        },
+        __wbg_isArray_fad08a0d12828686: function(arg0) {
+            const ret = Array.isArray(getObject(arg0));
+            return ret;
+        },
+        __wbg_iterator_fc7ad8d33bab9e26: function() {
+            const ret = Symbol.iterator;
+            return addHeapObject(ret);
+        },
+        __wbg_length_5855c1f289dfffc1: function(arg0) {
+            const ret = getObject(arg0).length;
+            return ret;
+        },
+        __wbg_length_a31e05262e09b7f8: function(arg0) {
+            const ret = getObject(arg0).length;
+            return ret;
+        },
+        __wbg_log_3c5e4b64af29e724: function(arg0) {
+            console.log(getObject(arg0));
+        },
+        __wbg_new_09959f7b4c92c246: function(arg0) {
+            const ret = new Uint8Array(getObject(arg0));
+            return addHeapObject(ret);
+        },
+        __wbg_new_227d7c05414eb861: function() {
+            const ret = new Error();
+            return addHeapObject(ret);
+        },
+        __wbg_new_cbee8c0d5c479eac: function() {
+            const ret = new Array();
+            return addHeapObject(ret);
+        },
+        __wbg_next_a5fe6f328f7affc2: function(arg0) {
+            const ret = getObject(arg0).next;
+            return addHeapObject(ret);
+        },
+        __wbg_next_e592122bb4ed4c67: function() { return handleError(function (arg0) {
+            const ret = getObject(arg0).next();
+            return addHeapObject(ret);
+        }, arguments); },
+        __wbg_prototypesetcall_f034d444741426c3: function(arg0, arg1, arg2) {
+            Uint8Array.prototype.set.call(getArrayU8FromWasm0(arg0, arg1), getObject(arg2));
+        },
+        __wbg_random_2b7bed8995d680fb: function() {
+            const ret = Math.random();
+            return ret;
+        },
+        __wbg_set_4c81cfb5dc3a333c: function(arg0, arg1, arg2) {
+            getObject(arg0)[arg1 >>> 0] = takeObject(arg2);
+        },
+        __wbg_stack_3b0d974bbf31e44f: function(arg0, arg1) {
+            const ret = getObject(arg1).stack;
+            const ptr1 = passStringToWasm0(ret, wasm.__wbindgen_export, wasm.__wbindgen_export2);
+            const len1 = WASM_VECTOR_LEN;
+            getDataViewMemory0().setInt32(arg0 + 4 * 1, len1, true);
+            getDataViewMemory0().setInt32(arg0 + 4 * 0, ptr1, true);
+        },
+        __wbg_value_667dcb90597486a6: function(arg0) {
+            const ret = getObject(arg0).value;
+            return addHeapObject(ret);
+        },
+        __wbindgen_cast_0000000000000001: function(arg0, arg1) {
+            // Cast intrinsic for `Ref(String) -> Externref`.
+            const ret = getStringFromWasm0(arg0, arg1);
+            return addHeapObject(ret);
+        },
+        __wbindgen_object_drop_ref: function(arg0) {
+            takeObject(arg0);
+        },
+    };
+    return {
+        __proto__: null,
+        "./ruvector_attention_wasm_bg.js": import0,
+    };
+}
+
+const WasmAdamFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmadam_free(ptr >>> 0, 1));
+const WasmAdamWFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmadamw_free(ptr >>> 0, 1));
+const WasmFlashAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmflashattention_free(ptr >>> 0, 1));
+const WasmHyperbolicAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmhyperbolicattention_free(ptr >>> 0, 1));
+const WasmInfoNCELossFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasminfonceloss_free(ptr >>> 0, 1));
+const WasmLRSchedulerFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlrscheduler_free(ptr >>> 0, 1));
+const WasmLinearAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlinearattention_free(ptr >>> 0, 1));
+const WasmLocalGlobalAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmlocalglobalattention_free(ptr >>> 0, 1));
+const WasmMoEAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmmoeattention_free(ptr >>> 0, 1));
+const WasmMultiHeadAttentionFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmmultiheadattention_free(ptr >>> 0, 1));
+const WasmSGDFinalization = (typeof FinalizationRegistry === 'undefined')
+    ? { register: () => {}, unregister: () => {} }
+    : new FinalizationRegistry(ptr => wasm.__wbg_wasmsgd_free(ptr >>> 0, 1));
+
+function addHeapObject(obj) {
+    if (heap_next === heap.length) heap.push(heap.length + 1);
+    const idx = heap_next;
+    heap_next = heap[idx];
+
+    heap[idx] = obj;
+    return idx;
+}
+
+function debugString(val) {
+    // primitive types
+    const type = typeof val;
+    if (type == 'number' || type == 'boolean' || val == null) {
+        return  `${val}`;
+    }
+    if (type == 'string') {
+        return `"${val}"`;
+    }
+    if (type == 'symbol') {
+        const description = val.description;
+        if (description == null) {
+            return 'Symbol';
+        } else {
+            return `Symbol(${description})`;
+        }
+    }
+    if (type == 'function') {
+        const name = val.name;
+        if (typeof name == 'string' && name.length > 0) {
+            return `Function(${name})`;
+        } else {
+            return 'Function';
+        }
+    }
+    // objects
+    if (Array.isArray(val)) {
+        const length = val.length;
+        let debug = '[';
+        if (length > 0) {
+            debug += debugString(val[0]);
+        }
+        for(let i = 1; i < length; i++) {
+            debug += ', ' + debugString(val[i]);
+        }
+        debug += ']';
+        return debug;
+    }
+    // Test for built-in
+    const builtInMatches = /\[object ([^\]]+)\]/.exec(toString.call(val));
+    let className;
+    if (builtInMatches && builtInMatches.length > 1) {
+        className = builtInMatches[1];
+    } else {
+        // Failed to match the standard '[object ClassName]'
+        return toString.call(val);
+    }
+    if (className == 'Object') {
+        // we're a user defined class or Object
+        // JSON.stringify avoids problems with cycles, and is generally much
+        // easier than looping through ownProperties of `val`.
+        try {
+            return 'Object(' + JSON.stringify(val) + ')';
+        } catch (_) {
+            return 'Object';
+        }
+    }
+    // errors
+    if (val instanceof Error) {
+        return `${val.name}: ${val.message}\n${val.stack}`;
+    }
+    // TODO we could test for more things here, like `Set`s and `Map`s.
+    return className;
+}
+
+function dropObject(idx) {
+    if (idx < 1028) return;
+    heap[idx] = heap_next;
+    heap_next = idx;
+}
+
+function getArrayF32FromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return getFloat32ArrayMemory0().subarray(ptr / 4, ptr / 4 + len);
+}
+
+function getArrayU8FromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return getUint8ArrayMemory0().subarray(ptr / 1, ptr / 1 + len);
+}
+
+let cachedDataViewMemory0 = null;
+function getDataViewMemory0() {
+    if (cachedDataViewMemory0 === null || cachedDataViewMemory0.buffer.detached === true || (cachedDataViewMemory0.buffer.detached === undefined && cachedDataViewMemory0.buffer !== wasm.memory.buffer)) {
+        cachedDataViewMemory0 = new DataView(wasm.memory.buffer);
+    }
+    return cachedDataViewMemory0;
+}
+
+let cachedFloat32ArrayMemory0 = null;
+function getFloat32ArrayMemory0() {
+    if (cachedFloat32ArrayMemory0 === null || cachedFloat32ArrayMemory0.byteLength === 0) {
+        cachedFloat32ArrayMemory0 = new Float32Array(wasm.memory.buffer);
+    }
+    return cachedFloat32ArrayMemory0;
+}
+
+function getStringFromWasm0(ptr, len) {
+    ptr = ptr >>> 0;
+    return decodeText(ptr, len);
+}
+
+let cachedUint8ArrayMemory0 = null;
+function getUint8ArrayMemory0() {
+    if (cachedUint8ArrayMemory0 === null || cachedUint8ArrayMemory0.byteLength === 0) {
+        cachedUint8ArrayMemory0 = new Uint8Array(wasm.memory.buffer);
+    }
+    return cachedUint8ArrayMemory0;
+}
+
+function getObject(idx) { return heap[idx]; }
+
+function handleError(f, args) {
+    try {
+        return f.apply(this, args);
+    } catch (e) {
+        wasm.__wbindgen_export3(addHeapObject(e));
+    }
+}
+
+let heap = new Array(1024).fill(undefined);
+heap.push(undefined, null, true, false);
+
+let heap_next = heap.length;
+
+function isLikeNone(x) {
+    return x === undefined || x === null;
+}
+
+function passArrayF32ToWasm0(arg, malloc) {
+    const ptr = malloc(arg.length * 4, 4) >>> 0;
+    getFloat32ArrayMemory0().set(arg, ptr / 4);
+    WASM_VECTOR_LEN = arg.length;
+    return ptr;
+}
+
+function passStringToWasm0(arg, malloc, realloc) {
+    if (realloc === undefined) {
+        const buf = cachedTextEncoder.encode(arg);
+        const ptr = malloc(buf.length, 1) >>> 0;
+        getUint8ArrayMemory0().subarray(ptr, ptr + buf.length).set(buf);
+        WASM_VECTOR_LEN = buf.length;
+        return ptr;
+    }
+
+    let len = arg.length;
+    let ptr = malloc(len, 1) >>> 0;
+
+    const mem = getUint8ArrayMemory0();
+
+    let offset = 0;
+
+    for (; offset < len; offset++) {
+        const code = arg.charCodeAt(offset);
+        if (code > 0x7F) break;
+        mem[ptr + offset] = code;
+    }
+    if (offset !== len) {
+        if (offset !== 0) {
+            arg = arg.slice(offset);
+        }
+        ptr = realloc(ptr, len, len = offset + arg.length * 3, 1) >>> 0;
+        const view = getUint8ArrayMemory0().subarray(ptr + offset, ptr + len);
+        const ret = cachedTextEncoder.encodeInto(arg, view);
+
+        offset += ret.written;
+        ptr = realloc(ptr, len, offset, 1) >>> 0;
+    }
+
+    WASM_VECTOR_LEN = offset;
+    return ptr;
+}
+
+function takeObject(idx) {
+    const ret = getObject(idx);
+    dropObject(idx);
+    return ret;
+}
+
+let cachedTextDecoder = new TextDecoder('utf-8', { ignoreBOM: true, fatal: true });
+cachedTextDecoder.decode();
+function decodeText(ptr, len) {
+    return cachedTextDecoder.decode(getUint8ArrayMemory0().subarray(ptr, ptr + len));
+}
+
+const cachedTextEncoder = new TextEncoder();
+
+if (!('encodeInto' in cachedTextEncoder)) {
+    cachedTextEncoder.encodeInto = function (arg, view) {
+        const buf = cachedTextEncoder.encode(arg);
+        view.set(buf);
+        return {
+            read: arg.length,
+            written: buf.length
+        };
+    };
+}
+
+let WASM_VECTOR_LEN = 0;
+
+const wasmPath = `${__dirname}/ruvector_attention_wasm_bg.wasm`;
+const wasmBytes = require('fs').readFileSync(wasmPath);
+const wasmModule = new WebAssembly.Module(wasmBytes);
+let wasm = new WebAssembly.Instance(wasmModule, __wbg_get_imports()).exports;
+wasm.__wbindgen_start();
diff --git a/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm
new file mode 100644
index 00000000..8e23dfab
Binary files /dev/null and b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm differ
diff --git a/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm.d.ts b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm.d.ts
new file mode 100644
index 00000000..7647f9ba
--- /dev/null
+++ b/ui/pose-fusion/pkg/ruvector-attention/ruvector_attention_wasm_bg.wasm.d.ts
@@ -0,0 +1,71 @@
+/* tslint:disable */
+/* eslint-disable */
+export const memory: WebAssembly.Memory;
+export const __wbg_wasmadam_free: (a: number, b: number) => void;
+export const __wbg_wasmadamw_free: (a: number, b: number) => void;
+export const __wbg_wasmflashattention_free: (a: number, b: number) => void;
+export const __wbg_wasmhyperbolicattention_free: (a: number, b: number) => void;
+export const __wbg_wasminfonceloss_free: (a: number, b: number) => void;
+export const __wbg_wasmlinearattention_free: (a: number, b: number) => void;
+export const __wbg_wasmmoeattention_free: (a: number, b: number) => void;
+export const __wbg_wasmmultiheadattention_free: (a: number, b: number) => void;
+export const __wbg_wasmsgd_free: (a: number, b: number) => void;
+export const attention_weights: (a: number, b: number, c: number, d: number) => void;
+export const available_mechanisms: () => number;
+export const batch_normalize: (a: number, b: number, c: number) => void;
+export const cosine_similarity: (a: number, b: number, c: number, d: number, e: number) => void;
+export const l2_norm: (a: number, b: number) => number;
+export const log: (a: number, b: number) => void;
+export const log_error: (a: number, b: number) => void;
+export const normalize: (a: number, b: number, c: number, d: number) => void;
+export const pairwise_distances: (a: number, b: number) => void;
+export const random_orthogonal_matrix: (a: number, b: number) => void;
+export const scaled_dot_attention: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const softmax: (a: number, b: number, c: number) => void;
+export const version: (a: number) => void;
+export const wasmadam_learning_rate: (a: number) => number;
+export const wasmadam_new: (a: number, b: number) => number;
+export const wasmadam_reset: (a: number) => void;
+export const wasmadam_set_learning_rate: (a: number, b: number) => void;
+export const wasmadam_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmadamw_new: (a: number, b: number, c: number) => number;
+export const wasmadamw_reset: (a: number) => void;
+export const wasmadamw_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmadamw_weight_decay: (a: number) => number;
+export const wasmflashattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmflashattention_new: (a: number, b: number) => number;
+export const wasmhyperbolicattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmhyperbolicattention_curvature: (a: number) => number;
+export const wasmhyperbolicattention_new: (a: number, b: number) => number;
+export const wasminfonceloss_compute: (a: number, b: number, c: number, d: number, e: number, f: number, g: number) => void;
+export const wasminfonceloss_new: (a: number) => number;
+export const wasmlinearattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmlinearattention_new: (a: number, b: number) => number;
+export const wasmlocalglobalattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmlocalglobalattention_new: (a: number, b: number, c: number) => number;
+export const wasmlrscheduler_get_lr: (a: number) => number;
+export const wasmlrscheduler_new: (a: number, b: number, c: number) => number;
+export const wasmlrscheduler_reset: (a: number) => void;
+export const wasmlrscheduler_step: (a: number) => void;
+export const wasmmoeattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmmoeattention_new: (a: number, b: number, c: number) => number;
+export const wasmmultiheadattention_compute: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const wasmmultiheadattention_dim: (a: number) => number;
+export const wasmmultiheadattention_new: (a: number, b: number, c: number) => void;
+export const wasmmultiheadattention_num_heads: (a: number) => number;
+export const wasmsgd_learning_rate: (a: number) => number;
+export const wasmsgd_new: (a: number, b: number, c: number) => number;
+export const wasmsgd_reset: (a: number) => void;
+export const wasmsgd_set_learning_rate: (a: number, b: number) => void;
+export const wasmsgd_step: (a: number, b: number, c: number, d: number, e: number, f: number) => void;
+export const init: () => void;
+export const wasmadamw_set_learning_rate: (a: number, b: number) => void;
+export const wasmadamw_learning_rate: (a: number) => number;
+export const __wbg_wasmlocalglobalattention_free: (a: number, b: number) => void;
+export const __wbg_wasmlrscheduler_free: (a: number, b: number) => void;
+export const __wbindgen_export: (a: number, b: number) => number;
+export const __wbindgen_export2: (a: number, b: number, c: number, d: number) => number;
+export const __wbindgen_export3: (a: number) => void;
+export const __wbindgen_export4: (a: number, b: number, c: number) => void;
+export const __wbindgen_add_to_stack_pointer: (a: number) => number;
+export const __wbindgen_start: () => void;