fix: WebSocket race condition, data source indicators, auto-start pose detection (#96)

* feat: RVF training pipeline & UI integration (ADR-036)

Implement full model training, management, and inference pipeline:

Backend (Rust):
- recording.rs: CSI recording API (start/stop/list/download/delete)
- model_manager.rs: RVF model loading, LoRA profile switching, model library
- training_api.rs: Training API with WebSocket progress streaming, simulated
  training mode with realistic loss curves, auto-RVF export on completion
- main.rs: Wire new modules, recording hooks in all CSI paths, data dirs

UI (new components):
- ModelPanel.js: Dark-mode model library with load/unload, LoRA dropdown
- TrainingPanel.js: Recording controls, training config, live Canvas charts
- model.service.js: Model REST API client with events
- training.service.js: Training + recording API client with WebSocket progress

UI (enhancements):
- LiveDemoTab: Model selector, LoRA profile switcher, A/B split view toggle,
  training quick-panel with 60s recording shortcut
- SettingsPanel: Full dark mode conversion (issue #92), model configuration
  (device, threads, auto-load), training configuration (epochs, LR, patience)
- PoseDetectionCanvas: 10-frame pose trail with ghost keypoints and motion
  trajectory lines, cyan trail toggle button
- pose.service.js: Model-inference confidence thresholds

UI (plumbing):
- index.html: Training tab (8th tab)
- app.js: Panel initialization and tab routing
- style.css: ~250 lines of training/model panel dark-mode styles

191 Rust tests pass, 0 failures. Closes #92.

Refs: ADR-036, #93

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix: real RuVector training pipeline + UI service fixes

Training pipeline (training_api.rs):
- Replace simulated training with real signal-based training loop
- Load actual CSI data from .csi.jsonl recordings or live frame history
- Extract 180 features per frame: subcarrier amplitudes, temporal variance,
  Goertzel frequency analysis (9 bands), motion gradients, global stats
- Train calibrated linear CSI-to-pose mapping via mini-batch gradient descent
  with L2 regularization (ridge regression), Xavier init, cosine LR decay
- Self-supervised: teacher targets from derive_pose_from_sensing() heuristics
- Real validation metrics: MSE and PCK@0.2 on 80/20 train/val split
- Export trained .rvf with real weights, feature normalization stats, witness
- Add infer_pose_from_model() for live inference from trained model
- 16 new tests covering features, training, inference, serialization

UI fixes:
- Fix double-URL bug in model.service.js and training.service.js
  (buildApiUrl was called twice — once in service, once in apiService)
- Fix route paths to match Rust backend (/api/v1/train/*, /api/v1/recording/*)
- Fix request body formats (session_name, nested config object)
- Fix top-level await in LiveDemoTab.js blocking module graph
- Dynamic imports for ModelPanel/TrainingPanel in app.js
- Center nav tabs with flex-wrap for 8-tab layout

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix: WebSocket onOpen race condition, data source indicators, auto-start pose detection

- Fix WebSocket onOpen race condition in websocket.service.js where
  setupEventHandlers replaced onopen after socket was already open,
  preventing pose service from receiving connection signal
- Add 4-state data source indicator (LIVE/SIMULATED/RECONNECTING/OFFLINE)
  across Dashboard, Sensing, and Live Demo tabs via sensing.service.js
- Add hot-plug ESP32 auto-detection in sensing server (auto mode runs
  both UDP listener and simulation, switches on ESP32_TIMEOUT)
- Auto-start pose detection when backend is reachable
- Hide duplicate PoseDetectionCanvas controls when enableControls=false
- Add standalone Demo button in LiveDemoTab for offline animated demo
- Add data source banner and status styling

Co-Authored-By: claude-flow <ruv@ruv.net>

ui/services/sensing.service.js

@@ -32,8 +32,14 @@ class SensingService {
     this._simTimer = null;
     // Connection state: disconnected | connecting | connected | reconnecting | simulated
     this._state = 'disconnected';
-    // Data-source label exposed to the UI: "live" | "reconnecting" | "simulated"
+    // Data-source label exposed to the UI:
+    //   "live"              — real ESP32 hardware connected
+    //   "server-simulated"  — server is running but using synthetic data (no hardware)
+    //   "reconnecting"      — WebSocket disconnected, retrying
+    //   "simulated"         — client-side fallback simulation (server unreachable)
     this._dataSource = 'reconnecting';
+    // The raw source string from the server (e.g. "esp32", "simulated", "simulate")
+    this._serverSource = null;
     this._lastMessage = null;
 
     // Ring buffer of recent RSSI values for sparkline
@@ -113,7 +119,9 @@ class SensingService {
       this._reconnectAttempt = 0;
       this._stopSimulation();
       this._setState('connected');
-      this._setDataSource('live');
+      // Don't assume "live" yet — wait for first frame's source field.
+      // Fetch server status to determine actual data source immediately.
+      this._detectServerSource();
     };
 
     this._ws.onmessage = (evt) => {
@@ -256,11 +264,61 @@ class SensingService {
     };
   }
 
+  // ---- Server source detection -------------------------------------------
+
+  /**
+   * Fetch `/api/v1/status` to find out if the server is using real
+   * hardware or simulation. Called once on WebSocket open.
+   */
+  async _detectServerSource() {
+    try {
+      const resp = await fetch('/api/v1/status');
+      if (resp.ok) {
+        const json = await resp.json();
+        this._applyServerSource(json.source);
+      } else {
+        // Can't reach status endpoint — assume live until first frame tells us
+        this._setDataSource('live');
+      }
+    } catch {
+      this._setDataSource('live');
+    }
+  }
+
+  /**
+   * Map a raw server source string to the UI data-source label.
+   */
+  _applyServerSource(rawSource) {
+    this._serverSource = rawSource;
+    if (rawSource === 'esp32' || rawSource === 'wifi' || rawSource === 'live') {
+      this._setDataSource('live');
+    } else if (rawSource === 'simulated' || rawSource === 'simulate') {
+      this._setDataSource('server-simulated');
+    } else {
+      // Unknown source — show as server-simulated to be safe
+      this._setDataSource('server-simulated');
+    }
+  }
+
+  /** @return {string|null} Raw server source (e.g. "esp32", "simulated") */
+  get serverSource() {
+    return this._serverSource;
+  }
+
   // ---- Data handling -----------------------------------------------------
 
   _handleData(data) {
     this._lastMessage = data;
 
+    // Track the server's source field from each frame so the UI
+    // can react if the server switches between esp32 ↔ simulated at runtime.
+    if (data.source && this._state === 'connected') {
+      const raw = data.source;
+      if (raw !== this._serverSource) {
+        this._applyServerSource(raw);
+      }
+    }
+
     // Update RSSI history for sparkline
     if (data.features && data.features.mean_rssi != null) {
       this._rssiHistory.push(data.features.mean_rssi);
@@ -292,7 +350,7 @@ class SensingService {
   /**
    * Update the dataSource label and notify state listeners so the UI can
    * react without needing a separate subscription.
-   * @param {'live'|'reconnecting'|'simulated'} source
+   * @param {'live'|'server-simulated'|'reconnecting'|'simulated'} source
    */
   _setDataSource(source) {
     if (source === this._dataSource) return;