import os
from model.train import fine_tune_gpt2
from model.utils import load_feedback_data

def trigger_auto_learning(threshold=10):
    feedback_files = os.listdir("data/feedback")
    if len(feedback_files) >= threshold:
        print("Iniciando autoaprendizado...")
        feedback_data = load_feedback_data()
        
        # Salvar dados processados para fine-tuning
        with open("data/processed/train.txt", "w") as f:
            for item in feedback_data:
                f.write(item["prompt"] + " " + item["generated_text"] + "\n")
        
        # Fine-tuning com novos dados
        fine_tune_gpt2("data/processed/train.txt")
        
        # Limpar feedback após treinamento
        for file in feedback_files:
            os.remove(os.path.join("data/feedback", file))
        print("Autoaprendizado concluído!")
    else:
        print(f"Feedback insuficiente ({len(feedback_files)}/{threshold}).")

if __name__ == "__main__":
    trigger_auto_learning()