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from energy_prediction.EnergyPredictionNorth import EnergyPredictionNorth
from energy_prediction.EnergyPredictionSouth import EnergyPredictionSouth
from energy_prediction.EnergyPredictionPipeline import EnergyPredictionPipeline

def main():
    # Energy Prediction North wing
    EnergyPredictionNorth = EnergyPredictionNorth(
        model_path="src/energy_prediction/models/lstm_energy_north_01.keras"
    )
    # Energy Prediction South wing

    def on_message(client, userdata, message):
        df = EnergyPredictionPipeline.fit(message)
        
        if not df is None:
            out_vav = EnergyPredictionNorth.pipeline(df, EnergyPredictionPipeline.scaler)

    broker_address = "localhost"
    broker_port = 1883
    topic = "sensor_data"
    client = mqtt.Client(mqtt.CallbackAPIVersion.VERSION1)
    print("Connecting to broker")
    client.on_message = on_message
    client.connect(broker_address, broker_port)
    client.subscribe(topic)
    client.loop_forever()

if __name__ == "__main__":
    main()