Update app.py

app.py

@@ -73,7 +73,6 @@ parser.add_argument("--model_dir", default="/home/user/app/Customized_IDSF/Joint
 parser.add_argument("--batch_size", default=32, type=int, help="Batch size for prediction")
 parser.add_argument("--no_cuda", action="store_true", help="Avoid using CUDA when available")
 
-globals()['var'] = "an object"
 pred_config = parser.parse_args()    
 
 # load model and args
@@ -124,17 +123,22 @@ def ner(text):
 
   slot_tokens = []    
 
-  words[0].capitalize()
+  words[0] = words[0].upper() + words[1:]
   for word, pred in zip(words, slot_preds):
       word = word.replace("_", " ")
       if pred == 'O':
           slot_tokens.extend([(word, None), (" ", None)])
-      elif pred[0] == 'I':
+          
+      elif pred[0] == 'I': # token with label's prefix' "I-XXX": will be combined their corresponded "B-XXX"
           added_tokens = list(slot_tokens[-2]) 
           added_tokens[0] += f' {word}'
           slot_tokens[-2] = tuple(added_tokens)
-      else:
+          
+      elif pred[0] == 'B': # token with label's prefix "B-XXX" : remove "B-" 
           slot_tokens.extend([(word, pred[2:]), (" ", None)])
+          
+      else: # PAD or UNK tags
+          slot_tokens.extend([(word, pred), (" ", None)])
   
   intent_label = intent_label_lst[intent_pred]