from app.models.feedback_manager import FeedbackManager
from app.models.matcher import PuzzleMatchingEngine

def retrain_model():
    feedback_manager = FeedbackManager()
    training_data = feedback_manager.get_training_data()
    
    # Dummy retraining logic (adjust weights based on feedback)
    matcher = PuzzleMatchingEngine()
    positive_samples = training_data['positive']
    negative_samples = training_data['negative']
    
    # Example: Increase weights for correct matches
    if positive_samples:
        matcher.weight_geometric += 0.01
        matcher.weight_color += 0.01
        matcher.weight_edge += 0.01
        total = matcher.weight_geometric + matcher.weight_color + matcher.weight_edge
        matcher.weight_geometric /= total
        matcher.weight_color /= total
        matcher.weight_edge /= total
    
    print("Model weights updated:", {
        'geometric': matcher.weight_geometric,
        'color': matcher.weight_color,
        'edge': matcher.weight_edge
    })

if __name__ == '__main__':
    retrain_model()