Update app.py

app.py

@@ -63,8 +63,13 @@ sequence = tokenizer.texts_to_sequences([query_data['lyrics']])
 padded_sequence = pad_sequences(sequence, maxlen=50)
 emotion = emotion_model.predict(padded_sequence).flatten()
 
+# Mapping emotion predictions to encoded categories
+emotion_mapping = {0: 'happy', 1: 'sad', 2: 'calm', 3: 'anger'}
+encoded_emotion = np.argmax(emotion)  
+emotion_category = emotion_mapping[encoded_emotion]
+
 # Combine emotion and audio features for recommendation
-combined_features_hybrid = np.concatenate([emotion, query_data[audio_feature_columns].values])
+combined_features_hybrid = np.concatenate([encoded_emotion, query_data[audio_feature_columns].values])
 
 # Generate recommendations using the hybrid model
 hybrid_recs = hybrid_recommendation(song_index=0)