Update app.py

app.py

@@ -10,8 +10,8 @@ with col1:
     st.title("Spamd: Turkish Spam Detector")
     st.markdown("Message spam detection tool for Turkish language. Due the small size of the dataset, I decided to go with transformers         technology Google BERT. Using the Turkish pre-trained model BERTurk, I imporved the accuracy of the tool by 18 percent compared to the previous model which used fastText.")
 with col2:
-        text = placeholder.text_input("Enter the text you'd like to analyze for spam.", disabled=True, key="1")
-        aButton = placeholder2.button('Analyze', disabled=True, key="1")
+    text = placeholder.text_input("Enter the text you'd like to analyze for spam.", disabled=True, key="1")
+    aButton = placeholder2.button('Analyze', disabled=True, key="1")
 if st.button('Load Model', disabled=False):   
     with st.spinner('Wait for it...'):
         import torch
@@ -59,11 +59,10 @@ if st.button('Load Model', disabled=False):
                 pred = 'Predicted Class: '+ prediction
                 return pred
         placeholder.text_input("Enter the text you'd like to analyze for spam.", disabled=False, key="2")
-        placeholder2.button('Analyze', disabled=False, key="2") 
-if not flag:       
+        placeholder2.button('Analyze', disabled=False, key="2")       
+if text or aButton:
     with col2:
-        if text or aButton:
-            st.header(predict(text))
+        st.header(predict(text))