Update app.py

app.py

@@ -9,8 +9,8 @@ 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 = st.text_input("Enter the text you'd like to analyze for spam.", disabled=flag)
-        aButton = st.button('Analyze', disabled=flag)
+        text = st.text_input("Enter the text you'd like to analyze for spam.", disabled=flag, key="1")
+        aButton = st.button('Analyze', disabled=flag, key="1")
 if st.button('Load Model', disabled=False):   
     with st.spinner('Wait for it...'):
         import torch
@@ -58,8 +58,8 @@ if st.button('Load Model', disabled=False):
                 pred = 'Predicted Class: '+ prediction
                 return pred
         flag = False
-        text = st.text_input("Enter the text you'd like to analyze for spam.", disabled=flag)
-        aButton = st.button('Analyze', disabled=flag)     
+        text = st.text_input("Enter the text you'd like to analyze for spam.", disabled=flag, key="2")
+        aButton = st.button('Analyze', disabled=flag, key="2")     
 if not flag:       
     with col2:
         if text or aButton: