Update app.py

app.py

@@ -60,19 +60,22 @@ title = st.text_area(label='Title', height=50)
 abstract = st.text_area(label='Summary', height=150)
 
 if st.button('Start classifier'):
-    prediction_classes, prediction_probs, probs = predict_label(title, abstract, tokenizer, model, inv_map)
+    if title == '' and abstract == '':
+        st.markdown("Summary and title are empty")
+    else:
+        prediction_classes, prediction_probs, probs = predict_label(title, abstract, tokenizer, model, inv_map)
+        
+        data = pd.DataFrame({'Categories' : tag, 'Probs' : probs})
+        data = data.sort_values(by='Probs', ascending=False)
+        
+        fig, ax = plt.subplots()
+        ax.bar(data['Categories'], data['Probs'])
+        ax.bar(prediction_classes, prediction_probs)
+        
+      
+        data_answer = pd.DataFrame({'Categories' : prediction_classes, 'Probs, %' : prediction_probs})
     
-    data = pd.DataFrame({'Categories' : tag, 'Probs' : probs})
-    data = data.sort_values(by='Probs', ascending=False)
     
-    fig, ax = plt.subplots()
-    ax.bar(data['Categories'], data['Probs'])
-    ax.bar(prediction_classes, prediction_probs)
-    
-  
-    data_answer = pd.DataFrame({'Categories' : prediction_classes, 'Probs, %' : prediction_probs})
-
-
-    st.pyplot(fig)
-    st.write('top-95%')
-    st.write(data_answer)
+        st.pyplot(fig)
+        st.write('top-95%')
+        st.write(data_answer)