# 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