Update app.py

app.py

@@ -6,12 +6,13 @@ st.set_page_config(layout='wide', initial_sidebar_state='expanded')
 col1, col2= st.columns(2)
 placeholder = st.empty()
 placeholder2 = st.empty()
-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")
+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.")
+
 if st.button('Load Model', disabled=False):   
     with st.spinner('Wait for it...'):
         import torch
@@ -61,6 +62,8 @@ if st.button('Load Model', disabled=False):
         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 text or aButton:
+    placeholder.text_input("Enter the text you'd like to analyze for spam.", disabled=False, key="3")
+    placeholder2.button('Analyze', disabled=False, key="3") 
     with col2:
         st.header(predict(text))