Update app.py

app.py

@@ -26,7 +26,7 @@ def get_question(context, answer):
     return tokenizer.decode(outs[0], skip_special_tokens=True).replace("question:", "").strip()
 
 # Function to get similar words using Sense2Vec
-def sense2vec_get_words(word, max_similarity=0.3):
+def sense2vec_get_words(word):
     word = word.lower().replace(" ", "_")  # Prepare word for Sense2Vec
     sense = s2v.get_best_sense(word)  # Get best sense (e.g., 'apple|NOUN')
     if not sense:
@@ -36,7 +36,7 @@ def sense2vec_get_words(word, max_similarity=0.3):
     return [
         each_word[0].split("|")[0].replace("_", " ").title()
         for each_word in s2v.most_similar(sense, n=20)
-        if each_word[0].split("|")[0] != word and each_word[1] >= max_similarity
+        if each_word[0].split("|")[0] != word 
     ]
     
 # Generate multiple questions and return as DataFrame
@@ -46,7 +46,7 @@ def generate_questions(context, num_questions=5):
         distractors = sense2vec_get_words(answer.capitalize())
         if distractors:
             question = get_question(context, answer)
-            options = [answer.capitalize()] + distractors[:3]
+            options = [answer.capitalize()] + distractors[-3:]
             question_dict = {
                 "Question": question,
                 "Answer": answer.capitalize(),