# modules/flashcard_generator.py
"""Enhanced Flashcard Generator Module"""

from typing import Dict, List, Optional
from modules.api_utils import (
    fetch_wikipedia_summary,
    fetch_wikibooks_content,
    fetch_wikipedia_categories,
    fetch_related_topics,
)
import random
import hashlib # For generating unique IDs


def _generate_item_id(content: str) -> str:
    """Generates a unique ID for a flashcard based on its content."""
    return hashlib.sha256(content.encode()).hexdigest()


def generate_flashcard_types(topic: str, difficulty: str) -> Dict:
    """Generate different types of flashcards based on difficulty"""
    summary_data = fetch_wikipedia_summary(topic)

    if not summary_data:
        return {"error": "Topic not found", "status": False}

    title = summary_data.get("title", topic)
    extract = summary_data.get("extract", "")
    description = summary_data.get("description", "")

    # Also try to get Wikibooks content for educational material
    wikibooks_content = fetch_wikibooks_content(topic)

    flashcard_types = {
        "Easy": {
            "front": f"What is {title}?",
            "back": extract[:200] + "..." if len(extract) > 200 else extract,
            "type": "definition",
        },
        "Medium": {
            "front": f"Explain the key concepts of {title}",
            "back": extract[:300] + "..." if len(extract) > 300 else extract,
            "type": "conceptual",
        },
        "Hard": {
            "front": f"How does {title} relate to its field and what are its applications?",
            "back": extract
            + (
                f"\n\nAdditional context: {wikibooks_content[:200]}"
                if wikibooks_content
                else ""
            ),
            "type": "analytical",
        },
    }

    flashcard = flashcard_types.get(difficulty, flashcard_types["Easy"])

    # Add categories as tags
    categories = fetch_wikipedia_categories(title)
    
    # Generate item_id
    item_id = _generate_item_id(flashcard["front"] + flashcard["back"])

    return {
        "item_id": item_id, # Add unique ID
        "front": flashcard["front"],
        "back": flashcard["back"],
        "hint": description,
        "topic": title,
        "difficulty": difficulty,
        "type": flashcard["type"],
        "tags": categories[:3] if categories else [],
        "status": True,
    }


def generate_flashcard(topic: str, difficulty: str = "Medium", adaptive_engine=None) -> Dict:
    """Generate an enhanced flashcard for a given topic, prioritizing review items."""
    
    # First, check for items due for review if adaptive engine is provided
    if adaptive_engine:
        review_item_ids = adaptive_engine.get_items_due_for_review(topic=topic, limit=1)
        if review_item_ids:
            # If a review item is found, we need to reconstruct the flashcard data
            # This assumes that the item_id is sufficient to retrieve the original flashcard content
            # For simplicity, we'll generate a new one for that topic, ideally, you'd load it from storage
            # For this implementation, we'll try to generate a flashcard for that specific item's topic
            # A more robust solution would store flashcard content with the item_id in the AdaptiveEngine data
            
            # For now, let's just use the topic associated with the item_id in adaptive engine
            # This requires adaptive engine to store topic with item_id
            item_data = adaptive_engine.data["item_performance"].get(review_item_ids[0])
            if item_data and item_data.get("topic"):
                return generate_flashcard_types(item_data["topic"], difficulty)
            
    # If no review items, or if adaptive_engine is not provided, generate a new flashcard
    return generate_flashcard_types(topic, difficulty)


def generate_flashcard_deck(
    topics: List[str], difficulty: str = "Medium", adaptive_engine=None
) -> List[Dict]:
    """Generate a deck of flashcards, incorporating spaced repetition."""
    deck = []
    
    # Prioritize review items if adaptive engine is provided
    if adaptive_engine:
        review_item_ids = adaptive_engine.get_items_due_for_review(limit=len(topics) * 2) # Get more than needed
        for item_id in review_item_ids:
            item_data = adaptive_engine.data["item_performance"].get(item_id)
            if item_data and item_data.get("topic"):
                card = generate_flashcard_types(item_data["topic"], item_data.get("difficulty", "Medium"))
                if card.get("status") and card["item_id"] == item_id: # Ensure the generated card matches the item_id
                    deck.append(card)
                    if len(deck) >= len(topics): # Fill up to requested deck size
                        break
    
    # Fill the rest of the deck with new flashcards if needed
    current_deck_size = len(deck)
    if current_deck_size < len(topics):
        new_topics_needed = len(topics) - current_deck_size
        new_topics = random.sample(topics, min(new_topics_needed, len(topics))) # Pick random topics for new cards
        for topic_name in new_topics:
            card = generate_flashcard_types(topic_name, difficulty)
            if card.get("status") and card not in deck: # Avoid duplicates
                deck.append(card)
                if len(deck) >= len(topics):
                    break
    
    # Ensure all cards have a unique card_number and total_cards
    for i, card in enumerate(deck):
        card["card_number"] = i + 1
        card["total_cards"] = len(deck)

    random.shuffle(deck) # Shuffle the final deck
    return deck


def generate_smart_deck(
    main_topic: str, deck_size: int = 10, difficulty: str = "Medium", adaptive_engine=None
) -> List[Dict]:
    """Generate a smart deck with related topics, incorporating spaced repetition."""
    # Start with the main topic
    topics_pool = [main_topic]

    # Add related topics
    related = fetch_related_topics(main_topic, deck_size - 1)
    topics_pool.extend(related)
    
    # Add some random topics to ensure variety
    topics_pool.extend(random.sample(topics_pool, min(5, len(topics_pool)))) # Add some random from pool
    
    # Remove duplicates and shuffle
    topics_pool = list(set(topics_pool))
    random.shuffle(topics_pool)

    # Generate the deck using the new generate_flashcard_deck
    deck = generate_flashcard_deck(topics_pool[:deck_size], difficulty, adaptive_engine)

    return deck