since we don't use the alert bar to inform the user that the first choice is the correct answer anymore and instead, use it as an error alert, we have to code it to show on the first choice that it's different from the other choices and indeed is the correct one

127.0.0.1.txt

@@ -16,3 +16,36 @@ Visit https://scribehow.com/shared/How_to_use_T2E_Vocabulary_Exam_Generator__vyY
 Note: The first choice of each question is the correct answer, the rest are trick choices!
 
 
+What is the meaning of this word "computer" in this sentence "[computer] good"?
+- >> a machine for performing calculations automatically
+- an expert at calculation (or at operating calculating machines)
+
+What is the meaning of this word "good" in this sentence "computer [good]"?
+- >> moral excellence or admirableness
+- (often used as a combining form) in a good or proper or satisfactory manner or to a high standard (`good' is a nonstandard dialectal variant for `well')
+- exerting force or influence
+- of moral excellence
+- morally admirable
+- in excellent physical condition
+- generally admired
+- having desirable or positive qualities especially those suitable for a thing specified
+- resulting favorably
+- having or showing knowledge and skill and aptitude
+- promoting or enhancing well-being
+- that which is pleasing or valuable or useful
+- completely and absolutely (`good' is sometimes used informally for `thoroughly')
+- financially sound
+- tending to promote physical well-being; beneficial to health
+- deserving of esteem and respect
+- benefit
+- having the normally expected amount
+- thorough
+- most suitable or right for a particular purpose
+- articles of commerce
+- agreeable or pleasing
+- capable of pleasing
+- not forged
+- appealing to the mind
+- not left to spoil
+- with or in a close or intimate relationship
+

model.py

@@ -159,14 +159,29 @@ def model(passage, level):
     vocab, context = key4.split(" = ")
     sequence_to_classify = context
     candidate_labels = value4
-    correct_def[key4] = []
+    # correct_def[key4] = []
+    correct_def_list = []
+    temp_def = []
     hypothesis_template = 'The meaning of [' + vocab + '] is {}.'
 
     output = classifier(sequence_to_classify, candidate_labels, hypothesis_template=hypothesis_template)
 
     # Process the score of each definition and add it to the Python dictionary, correct_def
     for label, score in zip(output['labels'], output['scores']):
-        correct_def[key4].append(f"{label}")
+        temp_def.append(label)
+        # print(temp_def)
+        for first in range(len(temp_def)):
+          if first == 0:
+            val = f">> {temp_def[first]}"
+          else:
+            val = f"{temp_def[first]}"
+
+        correct_def_list.append(val)
+
+    print(type(key4), type(correct_def_list))
+    correct_def[key4] = correct_def_list
+        
+        # correct_def[key4].append(f"{label}")
 
   return correct_def