diff --git a/backend/src/core/essentia_classifier.py b/backend/src/core/essentia_classifier.py
index 173b846..919c54d 100644
--- a/backend/src/core/essentia_classifier.py
+++ b/backend/src/core/essentia_classifier.py
@@ -168,12 +168,25 @@ class EssentiaClassifier:
             predictions = predictions[0]  # Remove batch dimension
 
             # Get top predictions
-            top_indices = np.argsort(predictions)[::-1][:5]
             labels = self.class_labels.get("genre", [])
+            logger.info(f"Genre predictions shape: {predictions.shape}, num_labels: {len(labels)}")
 
-            primary = labels[top_indices[0]] if labels else "unknown"
-            secondary = [labels[i] for i in top_indices[1:4]] if labels else []
-            confidence = float(predictions[top_indices[0]])
+            # Ensure we don't go out of bounds
+            if len(predictions) == 0:
+                logger.warning("No predictions returned from genre model")
+                return self._fallback_genre()
+
+            top_indices = np.argsort(predictions)[::-1][:5]
+            # Only use indices that are within the labels range
+            valid_top_indices = [i for i in top_indices if i < len(labels)]
+
+            if not valid_top_indices:
+                logger.warning(f"No valid indices found. Predictions: {len(predictions)}, Labels: {len(labels)}")
+                return self._fallback_genre()
+
+            primary = labels[valid_top_indices[0]]
+            secondary = [labels[i] for i in valid_top_indices[1:4]]
+            confidence = float(predictions[valid_top_indices[0]])
 
             return {
                 "primary": primary,
@@ -218,11 +231,19 @@ class EssentiaClassifier:
             predictions = predictions[0]
 
             # Get top predictions
-            top_indices = np.argsort(predictions)[::-1][:5]
             labels = self.class_labels.get("mood", [])
 
-            primary = labels[top_indices[0]] if labels else "unknown"
-            secondary = [labels[i] for i in top_indices[1:3]] if labels else []
+            if len(predictions) == 0:
+                return self._fallback_mood()
+
+            top_indices = np.argsort(predictions)[::-1][:5]
+            valid_top_indices = [i for i in top_indices if i < len(labels)]
+
+            if not valid_top_indices:
+                return self._fallback_mood()
+
+            primary = labels[valid_top_indices[0]] if valid_top_indices else "unknown"
+            secondary = [labels[i] for i in valid_top_indices[1:3]] if len(valid_top_indices) > 1 else []
 
             # Estimate arousal and valence from mood labels (simplified)
             arousal, valence = self._estimate_arousal_valence(primary)
diff --git a/frontend/app/page.tsx b/frontend/app/page.tsx
index f2e25f4..872734e 100644
--- a/frontend/app/page.tsx
+++ b/frontend/app/page.tsx
@@ -76,6 +76,8 @@ export default function Home() {
                   <div className="flex justify-between items-start">
                     <div className="flex-1">
                       <h3 className="font-medium text-gray-900">{track.filename}</h3>
+
+                      {/* Primary metadata */}
                       <div className="mt-1 flex flex-wrap gap-2">
                         <span className="inline-flex items-center px-2 py-1 rounded text-xs bg-blue-100 text-blue-800">
                           {track.classification.genre.primary}
@@ -86,10 +88,40 @@ export default function Home() {
                         <span className="text-xs text-gray-500">
                           {Math.round(track.features.tempo_bpm)} BPM
                         </span>
+                        <span className="text-xs text-gray-500">
+                          {track.features.key}
+                        </span>
                         <span className="text-xs text-gray-500">
                           {Math.floor(track.duration_seconds / 60)}:{String(Math.floor(track.duration_seconds % 60)).padStart(2, '0')}
                         </span>
                       </div>
+
+                      {/* Secondary moods */}
+                      {track.classification.mood.secondary && track.classification.mood.secondary.length > 0 && (
+                        <div className="mt-2 flex flex-wrap gap-1">
+                          <span className="text-xs text-gray-400">Also:</span>
+                          {track.classification.mood.secondary.map((mood, i) => (
+                            <span key={i} className="inline-flex items-center px-2 py-0.5 rounded text-xs bg-purple-50 text-purple-600">
+                              {mood}
+                            </span>
+                          ))}
+                        </div>
+                      )}
+
+                      {/* Instruments */}
+                      {track.classification.instruments && track.classification.instruments.length > 0 && (
+                        <div className="mt-2 flex flex-wrap gap-1">
+                          <span className="text-xs text-gray-400">Instruments:</span>
+                          {track.classification.instruments.slice(0, 6).map((instrument, i) => (
+                            <span key={i} className="inline-flex items-center px-2 py-0.5 rounded text-xs bg-green-50 text-green-700">
+                              {instrument}
+                            </span>
+                          ))}
+                          {track.classification.instruments.length > 6 && (
+                            <span className="text-xs text-gray-400">+{track.classification.instruments.length - 6} more</span>
+                          )}
+                        </div>
+                      )}
                     </div>
                     <div className="ml-4 flex gap-2">
                       <a