Update app.py

app.py

@@ -6,6 +6,10 @@ from txtai.pipeline import TextToSpeech
 # Load the text classification model pipeline, filter out the spam and leave the ham
 classifier = pipeline("text-classification", model='JustHuggingFaces/OptimalSpamDetect')
 to_speech = TextToSpeech("NeuML/ljspeech-jets-onnx")
+# Set the images for better user experience
+ham_pic = 
+spam_pic = "https://inst.eecs.berkeley.edu/~cs10/labs/cur/programming/data/spam-ham/1-introduction.html?topic=berkeley_bjc%2Fareas%2Fdata.topic"
+
 # Streamlit application title
 st.title("Reading Ham")
 st.write("Classification for Spam Email: Spam or  Ham?")
@@ -22,6 +26,7 @@ if st.button("Classify"):
         #st.write("Text:", text)
         st.write("Spam!")
         #st.write("Label: ", result['label'])
+        st.image(spam_pic, caption="It's a spam!")
     else:
         st.write("Ham!")
         #st.write("Label: ", result['label'])