Update app.py

app.py

@@ -100,26 +100,20 @@ def ensemble_prediction(audio_file, apply_noise_reduction=False, segment_duratio
     return most_common
 
 def predict_emotion(audio_file, use_ensemble=False, apply_noise_reduction=False, segment_duration=3.0, overlap=1.0):
-    """
-    Main prediction function:
-      - Uses ensemble prediction if enabled.
-      - Otherwise, processes the entire audio at once.
-    Returns the emotion label enhanced with an emoji.
-    """
     try:
         if use_ensemble:
             label = ensemble_prediction(audio_file, apply_noise_reduction, segment_duration, overlap)
         else:
             temp_file = preprocess_audio(audio_file, apply_noise_reduction)
-            result = classifier.classify_file(temp_file)  # Check if this returns a list
+            result = classifier.classify_file(temp_file)
             os.remove(temp_file)
 
-            if isinstance(result, list):  # Ensure we extract the correct label
-                label = result[-1]  # Assuming the last item is the label
+            if isinstance(result, tuple) and len(result) > 3:
+                label = result[3][0]  # Extract the predicted label (e.g., 'hap')
             else:
-                label = result
+                label = str(result)  # Convert to string if unexpected format
 
-        return add_emoji_to_label(str(label))  # Convert to string before .lower()
+        return add_emoji_to_label(label.lower())  # Ensure lowercase for consistency
     except Exception as e:
         return f"Error processing file: {str(e)}"