Update app.py

app.py

@@ -5,6 +5,7 @@ import string
 
 bert_tokenizer = None
 bert_model = None
+top_k = 20
 
 from transformers import BertTokenizer, BertForMaskedLM
 
@@ -99,6 +100,8 @@ def on_option_change():
   text = st.session_state.my_choice
   run_test(text,top_k,model_name)
   
+ def on_results_count_change():
+   top_k = int(st.session_state.my_slider)
 
 def on_model_change1():
   model_name = st.session_state.my_model1
@@ -115,24 +118,28 @@ def init_selectbox():
      'Choose any of these sentences or type any text below',
      ('', "[MASK] who lives in New York and works for XCorp suffers from Parkinson's", "Lou Gehrig who lives in [MASK] and works for XCorp suffers from Parkinson's","Lou Gehrig who lives in New York and works       for [MASK] suffers from Parkinson's","Lou Gehrig who lives in New York and works for XCorp suffers from [MASK]","[MASK] who lives in New York and works for XCorp suffers from Lou Gehrig's", "Parkinson who      lives in [MASK] and works for XCorp suffers from Lou Gehrig's","Parkinson who lives in New York and works for [MASK] suffers from Lou Gehrig's","Parkinson who lives in New York and works for XCorp suffers      from [MASK]","Lou Gehrig","Parkinson","Lou Gehrigh's is a [MASK]","Parkinson is a [MASK]","New York is a [MASK]","New York","XCorp","XCorp is a [MASK]","acute lymphoblastic leukemia","acute lymphoblastic       leukemia is a [MASK]"),on_change=on_option_change,key='my_choice') 
   return option
+  
+
 
-st.markdown("<h3 style='text-align: center;'>Qualitative evaluation of  any pretrained BERT model</h3>", unsafe_allow_html=True)
-st.markdown("""
+def main():
+
+  st.markdown("<h3 style='text-align: center;'>Qualitative evaluation of  any pretrained BERT model</h3>", unsafe_allow_html=True)
+  st.markdown("""
         <small style="font-size:18px; color: #7f7f7f">Pretrained BERT models can be used as is, <a href="https://ajitrajasekharan.github.io/2021/01/02/my-first-post.html"><b>with no fine tuning to perform tasks like NER</b></a> <i>ideally if both fill-mask and CLS predictions are good, or minimally if fill-mask predictions are adequate</i></small>
         """, unsafe_allow_html=True)
   #st.write("https://ajitrajasekharan.github.io/2021/01/02/my-first-post.html")
-st.write("This app can be used to examine both model prediction for a masked  position as well as the neighborhood of CLS vector")
-st.write("   - To examine model prediction for a position, enter the token [MASK] or <mask>")
-st.write("   - To examine just the [CLS] vector, enter a word/phrase or sentence. Example: eGFR or EGFR or non small cell lung cancer")
-top_k = st.sidebar.slider("Select how many predictions do you need", 1 , 50, 20) #some times it is possible to have less words
-print(top_k)
+  st.write("This app can be used to examine both model prediction for a masked  position as well as the neighborhood of CLS vector")
+  st.write("   - To examine model prediction for a position, enter the token [MASK] or <mask>")
+  st.write("   - To examine just the [CLS] vector, enter a word/phrase or sentence. Example: eGFR or EGFR or non small cell lung cancer")
+  top_k = st.sidebar.slider("Select how many predictions do you need", 1 , 50, top_k,key='my_slider',on_change=on_results_count_change) #some times it is possible to have less words
+  print(top_k)
 
 
 
   #if st.button("Submit"):
     
   #  with st.spinner("Computing"):
-try:
+  try:
             
       model_name = st.sidebar.selectbox(label='Select Model to Apply',  options=['ajitrajasekharan/biomedical', 'bert-base-cased','bert-large-cased','microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext','allenai/scibert_scivocab_cased','dmis-lab/biobert-v1.1'], index=0,  key = "my_model1",on_change=on_model_change1)
       option = init_selectbox()
@@ -153,9 +160,14 @@ try:
       
       
 
-except Exception as e:
-  st.error("Some error occurred during loading" + str(e))
-  st.stop()  
+  except Exception as e:
+    st.error("Some error occurred during loading" + str(e))
+    st.stop()  
 	
-st.write("---")
+  st.write("---")
+  
+ 
+ 
+ if __name__ == "__main__":
+   main()