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# utils/flexflow_integration.py
from .lora_integration import LoRaIntegration
from .encryption import encrypt_data, decrypt_data

class FlexFlowIntegration:
    @staticmethod
    def encrypt_and_send(data):
        encrypted_data = encrypt_data(data)
        LoRaIntegration.send_data(encrypted_data)

    @staticmethod
    def receive_and_decrypt():
        received_data = LoRaIntegration.receive_data()
        if received_data:
            return decrypt_data(received_data)
        else:
            return None

    @staticmethod
    def execute_model(data):
        # Placeholder for FlexFlow model execution logic
        print(f"Executing FlexFlow model with data: {data}")
        result = {"prediction": "Fraud" if data["score"] > 0.5 else "Non-Fraud"}
        print("Model execution completed.")
        return result