Update app.py

app.py

@@ -1,7 +1,8 @@
+# Filename: app.py
 import streamlit as st
 from transformers import pipeline
 
-# Load the text classification model for spam detection
+# Load a different text classification model for spam detection
 classifier = pipeline("text-classification", model="mrm8488/bert-tiny-finetuned-sms-spam-detection")
 
 def main():
@@ -18,5 +19,13 @@ def main():
             # Display the result
             st.write(f"**Result:** {result['label']} (Confidence: {result['score']:.2%})")
 
+            # Show a message based on the classification
+            if result['label'] == 'spam':
+                st.error("This message is classified as spam.")
+            else:
+                st.success("This message is not spam.")
+        else:
+            st.warning("Please enter a message before checking for spam.")
+
 if __name__ == "__main__":
     main()