from evo_model import EvoTransformerConfig, EvoTransformerForClassification
import os

def initialize_and_save_model(save_path="trained_model"):
    config = EvoTransformerConfig()
    model = EvoTransformerForClassification(config)
    os.makedirs(save_path, exist_ok=True)
    model.save_pretrained(save_path)

def retrain_model():
    # Dummy retrain function – replace with actual training logic later
    initialize_and_save_model("trained_model")
    return "✅ Retrained and saved new model."