# Enhanced QuizAgent in ai/agents.py
class QuizAgent(Agent):
    def __init__(self, hf_service):
        super().__init__("Quiz", "Generates questions")
        self.hf = hf_service
    
    def process(self, content, context=None):
        # Generate 3-5 questions based on content
        questions = []
        
        # Extract key concepts using summarization
        summary = self.hf.summarize_content(content)[0]['summary_text']
        
        # Generate questions using question-answering in reverse
        # We'll extract potential answers and create questions for them
        sentences = summary.split('. ')
        for sentence in sentences[:5]:  # Limit to 5 questions
            # Use the sentence as context and try to generate a question
            potential_answer = sentence.strip()
            
            # We'll need to integrate with a better question generation model here
            # For now, create a simple question by masking parts of the sentence
            words = potential_answer.split()
            if len(words) > 5:
                # Find a key noun or entity to ask about
                # This is simplified - would need NER or POS tagging in production
                question_word = words[len(words)//2]
                question = potential_answer.replace(question_word, "___")
                questions.append({
                    "question": f"Complete the following: {question}", 
                    "answer": question_word,
                    "context": potential_answer
                })
        
        return questions
      
      # New PersonalizationAgent in ai/agents.py
class PersonalizationAgent(Agent):
    def __init__(self, hf_service):
        super().__init__("Personalizer", "Adapts content for users")
        self.hf = hf_service
    
    def process(self, content, context=None):
        # Context should contain user profile/level
        if not context or 'level' not in context:
            return content
        
        user_level = context['level']
        
        if user_level == 'beginner':
            # Simplify content, add more explanations
            simplified = self.hf.summarize_content(
                content, 
                max_length=len(content.split()) // 2  # Half the original length
            )[0]['summary_text']
            return f"{simplified}\n\nLet's break this down further: {content}"
            
        elif user_level == 'advanced':
            # Provide more detailed content
            return f"{content}\n\nFor advanced learners: [Additional depth would be added here]"
            
        # Default - intermediate
        return content