Update app.py

app.py

@@ -50,6 +50,7 @@ INDEX_TO_CATEGORY = {v: f"[{k}] {CATEGORY_NAMES[k]}" for k, v in LABEL_MAPPING.i
 # Set Streamlit app title
 st.title("Google Taxonomy Classifier by DEJAN")
 st.write("Enter text in the input box, and the model will classify it into one of the 21 top level categories. This demo showcases early model capability while the full 5000+ label model is undergoing extensive training.")
+st.write("Works for product descriptions, search queries, articles, social media posts and broadly web text of any style. Suitable for classification pipelines of millions of queries.")
 
 # Input text box
 input_text = st.text_area("Enter text for classification:")
@@ -91,6 +92,14 @@ if st.button("Classify"):
             ax.invert_yaxis()  # Ensure highest probability is at the top
             ax.set_xlim(0, 1)  # Set the x-axis range to 0-1 for probabilities
             st.pyplot(fig)
+
+            # Additional information at the end
+            st.divider()
+            st.markdown("""
+            Interested in using this in an automated pipeline for bulk link prediction?
+            Please [book an appointment](https://dejanmarketing.com/conference/) to discuss your needs.
+            """)
+            
         else:
             st.error("Could not classify the text. Please try again.")
     else: