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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() |