Delete verify_generation.py

verify_generation.py

@@ -1,124 +0,0 @@
-import logging
-from exam_question_system import ExamQuestionSystem
-from option_generator import OptionGenerator
-
-# Configure logging
-logging.basicConfig(level=logging.INFO)
-
-def verify_generation():
-    # Mock content
-    content = """
-    Data visualization is the graphical representation of information and data. 
-    By using visual elements like charts, graphs, and maps, data visualization 
-    tools provide an accessible way to see and understand trends, outliers, and 
-    patterns in data. In the world of Big Data, data visualization tools and 
-    technologies are essential to analyze massive amounts of information and 
-    make data-driven decisions.
-    
-    Design principles in data visualization include understanding the audience, 
-    choosing the right chart type, and using color effectively. Good design 
-    makes complex data more accessible, understandable, and usable.
-    
-    Exploratory Data Analysis (EDA) is an approach to analyzing data sets to 
-    summarize their main characteristics, often with visual methods. A statistical 
-    model can be used or not, but primarily EDA is for seeing what the data can 
-    tell us beyond the formal modeling or hypothesis testing task.
-    """
-    
-    print("Initializing ExamQuestionSystem...")
-    system = ExamQuestionSystem(use_transformers=False) # Use rule-based for speed in test
-    
-    print("\nGenerating questions (Target: 2 MCQ, 1 Short, 1 Long)...")
-    # We simulate the logic in app.py
-    num_mcq = 2
-    num_short = 1
-    num_long = 1
-    total_needed = num_mcq + num_short + num_long
-    
-    results = system.generate_exam_questions(
-        input_text=content,
-        max_questions=total_needed,
-        include_mcq=False,
-        syllabus_text=content
-    )
-    
-    all_questions = results.get('questions', [])
-    print(f"\nTotal questions generated: {len(all_questions)}")
-    
-    # Simulate app.py distribution logic
-    generated_questions = {
-        'mcq_questions': [],
-        'short_questions': [],
-        'long_questions': []
-    }
-    
-    # Filter out questions that are too simple for Long answers
-    long_candidates = [q for q in all_questions if len(q.get('context', '').split()) > 10]
-    short_candidates = [q for q in all_questions if q not in long_candidates]
-    
-    # If we don't have enough long candidates, take from short
-    if len(long_candidates) < num_long:
-        needed = num_long - len(long_candidates)
-        long_candidates.extend(short_candidates[:needed])
-        short_candidates = short_candidates[needed:]
-    
-    # 3. Process Long Questions
-    for _ in range(num_long):
-        if long_candidates:
-            q = long_candidates.pop(0)
-            q['type'] = 'long_answer'
-            generated_questions['long_questions'].append(q)
-            if q in all_questions:
-                all_questions.remove(q)
-    
-    # 2. Process Short Questions
-    for _ in range(num_short):
-        if short_candidates:
-            q = short_candidates.pop(0)
-            q['type'] = 'short_answer'
-            generated_questions['short_questions'].append(q)
-            if q in all_questions:
-                all_questions.remove(q)
-        elif all_questions:
-            q = all_questions.pop(0)
-            q['type'] = 'short_answer'
-            generated_questions['short_questions'].append(q)
-
-    # 1. Process MCQs
-    global_keywords = [k[1] for k in results.get('keywords', [])]
-    print(f"\nGlobal Keywords (Cleaned): {global_keywords}")
-    
-    for _ in range(num_mcq):
-        if all_questions:
-            q = all_questions.pop(0)
-            try:
-                mcq_data = system.option_generator.create_mcq_options(
-                    q['question'],
-                    q['context'],
-                    correct_answer=q.get('correct_answer'),
-                    global_keywords=global_keywords
-                )
-                if mcq_data and 'options' in mcq_data:
-                    q.update(mcq_data)
-                    q['type'] = 'mcq'
-                    generated_questions['mcq_questions'].append(q)
-            except Exception as e:
-                print(f"Error generating options: {e}")
-
-    # Print Results
-    print("\n--- Generation Results ---")
-    print(f"MCQs: {len(generated_questions['mcq_questions'])}")
-    for q in generated_questions['mcq_questions']:
-        print(f"  Q: {q['question']}")
-        print(f"  Options: {q.get('options')}")
-        
-    print(f"\nShort Questions: {len(generated_questions['short_questions'])}")
-    for q in generated_questions['short_questions']:
-        print(f"  Q: {q['question']}")
-        
-    print(f"\nLong Questions: {len(generated_questions['long_questions'])}")
-    for q in generated_questions['long_questions']:
-        print(f"  Q: {q['question']}")
-
-if __name__ == "__main__":
-    verify_generation()