Update app.py

app.py

@@ -58,17 +58,18 @@ def score_fincat(txt):
       context_text = extract_context_words(x)
       features = bert_embedding_extract(context_text, word)
       if(features[0]=='None'):
-          highlight.append((txt, '    '))
-          return highlight
+          continue
+          #highlight.append((txt, '    '))
+          #return highlight
       prediction = lr_clf.predict(features.reshape(1, 768))
       prediction_probability = '{:.4f}'.format(round(lr_clf.predict_proba(features.reshape(1, 768))[:,1][0], 4))
       highlight.append((word, '    In-claim' if prediction==1 else 'Out-of-Claim'))
      # li.append([word,'    In-claim' if prediction==1 else 'Out-of-Claim', prediction_probability])
     else:
-      highlight.append((word, '    '))
-  #headers = ['numeral', 'prediction', 'probability']
-  #dff = pd.DataFrame(li)
- # dff.columns = headers
+       continue
+     # highlight.append((word, '    '))
+  if(len(highlight)<1):
+      highlight.append((txt,'  '))   
   return highlight