fix: /api/diversity - use JIT _predict instead of raw model() to avoid tracer error

web/app.py

@@ -217,9 +217,8 @@ def sample_diversity(req: DiversityRequest):
     # Stable sort index: most-free edges first
     sort_idx = np.argsort(-q_std_per_edge)
 
-    # Deterministic MLP prediction for the same target shape
-    flat_target = xyz_target_np
-    det_pred, (det_q, _, _) = model(flat_target, structure, aux_data=True)
+    # Deterministic MLP prediction for the same target shape (reuse JIT'd predict)
+    det_pred, det_q, _ = _predict(xyz_target)
     det_pred_np = np.array(det_pred).reshape(-1, 3)
     det_q_np = np.array(det_q).flatten()