Update app.py

app.py

@@ -60,6 +60,23 @@ def get_bert_prediction(input_text,top_k):
     return res
   except Exception as error:
     pass
+    
+ 
+def run_test(sent,top_k):
+  start = None
+  with st.spinner("Computing"):
+          start = time.time()
+          try:
+            res = get_bert_prediction(sent,top_k)
+            st.caption("Results in JSON")
+            st.json(res)
+            
+          except Exception as e:
+            st.error("Some error occurred during prediction" + str(e))
+            st.stop()
+  if start is not None:
+    st.text(f"prediction took {time.time() - start:.2f}s")
+  
 
 st.markdown("<h3 style='text-align: center;'>Qualitative evaluation of Pretrained BERT models</h3>", unsafe_allow_html=True)
 st.markdown("""
@@ -73,7 +90,7 @@ top_k = st.sidebar.slider("Select how many predictions do you need", 1 , 50, 20)
 print(top_k)
 
   
-start = None
+
   #if st.button("Submit"):
     
   #  with st.spinner("Computing"):
@@ -81,7 +98,7 @@ 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'], index=0,  key = "model_name")
       option = st.selectbox(
-     'Choose any of these sentences to test models',
+     '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]'"))
       bert_tokenizer, bert_model  = load_bert_model(model_name)
       default_text = "Imatinib is used to [MASK] nsclc"
@@ -89,22 +106,13 @@ try:
                   label="Enter text below",
                   value=default_text,
                 )
-      if st.button("Submit") or len(option) > 0:
-        with st.spinner("Computing"):
-          start = time.time()
-          try:
-            res = get_bert_prediction(input_text,top_k)
-            st.caption("Results in JSON")
-            st.json(res)
-            
-          except Exception as e:
-            st.error("Some error occurred during prediction" + str(e))
-            st.stop()
- 
+      if st.button("Submit"):
+        run_test(input_text,top_k)
+      else:
+        if len(option) > 0:
+          run_test(option,top_k)
 
-	
-      if start is not None:
-          st.text(f"prediction took {time.time() - start:.2f}s")
+      
 
 except Exception as e:
   st.error("Some error occurred during loading" + str(e))