Merge pull request #10 from srishtimaggo/patch-2

truefalse_quiz.py

@@ -4,7 +4,7 @@ from transformers import pipeline
 from nltk.tokenize import sent_tokenize
 
 # Download required tokenizer
-nltk.download('punkt_tab', quiet=True)
+nltk.download('punkt', quiet=True)
 
 # Load NLI model
 nli = pipeline("text-classification", model="facebook/bart-large-mnli")
@@ -27,7 +27,7 @@ def apply_noise(sentence: str, level: str) -> str:
     elif level == "medium":
         if "Sun" in sentence:
             return sentence.replace("Sun", "Moon")
-        return sentence.replace("is", "is not") if "is" in sentence else sentence
+        return sentence.replace(" is ", " is not ") if " is " in sentence else sentence
     elif level == "hard":
         if "eight" in sentence:
             return sentence.replace("eight", "ten")
@@ -48,51 +48,20 @@ def generate_statements(context, n, difficulty, sentences):
             break
     return final
 
-# Get valid user answer
-def get_user_answer():
-    while True:
-        user = input("True or False? ").strip().lower()
-        if user in ["true", "false"]:
-            return user
-        print("Please enter 'true' or 'false'.")
-
-# Main logic
-try:
-    context = input(">> Enter context text: ")
-    num_questions = int(input("\n>> How many questions do you want to generate? "))
-    difficulty = input("\n>> Enter difficulty level (easy/medium/hard): ").strip().lower()
-    
+# ✅ MAIN BACKEND FUNCTION
+def generate_true_false(context, num_questions, difficulty):
+    """
+    Returns a list of (statement, label) pairs for Streamlit frontend.
+    label: 'ENTAILMENT' (True) or 'CONTRADICTION' (False)
+    """
     sentences = validate_inputs(context, num_questions, difficulty)
     questions = generate_statements(context, num_questions, difficulty, sentences)
-    
-    if len(questions) < num_questions:
-        print(f"Warning: Only {len(questions)} questions generated due to limited context.")
-    
-    print("\n--- QUIZ STARTS ---\n")
-    score = 0
-    
-    for idx, (statement, actual_label) in enumerate(questions, 1):
-        print(f"Q{idx}: {statement}")
-        user = get_user_answer()
-        
-        # Format input for facebook/bart-large-mnli
+    result = []
+
+    for statement, _ in questions:
         input_text = f"{context} [SEP] {statement}"
-        result = nli(input_text)[0]
-        if result["label"] == "neutral":
-            print("Skipping ambiguous statement.\n")
-            continue
-        model_label = "ENTAILMENT" if result["label"] == "entailment" else "CONTRADICTION"
-        
-        if model_label == "ENTAILMENT" and user == "true":
-            print("Correct!\n")
-            score += 1
-        elif model_label == "CONTRADICTION" and user == "false":
-            print("Correct!\n")
-            score += 1
-        else:
-            print(f"Incorrect! (Correct answer: {'True' if model_label == 'ENTAILMENT' else 'False'})\n")
+        nli_result = nli(input_text)[0]
+        label = "ENTAILMENT" if nli_result["label"] == "entailment" else "CONTRADICTION"
+        result.append((statement, label))
     
-    print(f"\n--- Final Score: {score}/{len(questions)} ---")
-
-except ValueError as e:
-    print(f"Error: {e}")
+    return result