Update app.py

app.py

@@ -32,8 +32,15 @@ label_encoder.fit(target_classes)
 user_text_embedding = encoder.encode_sentences([user_text])[0]
 user_text_embedding = np.reshape(user_text_embedding, (1, -1))
 
-predicted_sentiment = np.argmax(model.predict(user_text_embedding))
-predicted_sentiment_no = label_encoder.inverse_transform([predicted_sentiment])[0]
+st.write("Debug: user_text_embedding", user_text_embedding)
+
+try:
+    predicted_sentiment = np.argmax(model.predict(user_text_embedding))
+    predicted_sentiment_no = label_encoder.inverse_transform([predicted_sentiment])[0]
+    st.write("Debug: predicted_sentiment_no", predicted_sentiment_no)
+except Exception as e:
+    st.write("Error during prediction:", str(e))
+    raise e
 
 if predicted_sentiment_no == 1:
     predicted_sentiment_label = 'neutral'
@@ -42,4 +49,4 @@ elif predicted_sentiment_no == 2:
 else:
     predicted_sentiment_label = 'negative'
 
-st.write("Predicted Sentiment:" + predicted_sentiment_label)
+st.write("Predicted Sentiment:", predicted_sentiment_label)