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app.py

@@ -271,9 +271,9 @@ def _to_tensor(spec) -> torch.Tensor:
 
 
 def _normalize_label(val):
-    """Convert labels to hashable, comparable form."""
+    """Convert labels to a simple string for metrics."""
     if isinstance(val, (list, tuple)):
-        return tuple(str(v) for v in val)
+        return " | ".join(str(v) for v in val)
     return str(val)
 
 
@@ -303,6 +303,9 @@ def compute_eval(task: str):
         y_true.append(true)
         y_pred.append(pred)
 
+    if not y_true or not y_pred:
+        raise RuntimeError("No samples were evaluated; check data or predictions.")
+
     labels = sorted(list({*y_true, *y_pred}))
     cm = confusion_matrix(y_true, y_pred, labels=labels)
     f1 = f1_score(y_true, y_pred, labels=labels, average="macro", zero_division=0)