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# utils/flexflow_integration.py | |
from .lora_integration import LoRaIntegration | |
from .encryption import encrypt_data, decrypt_data | |
class FlexFlowIntegration: | |
def encrypt_and_send(data): | |
encrypted_data = encrypt_data(data) | |
LoRaIntegration.send_data(encrypted_data) | |
def receive_and_decrypt(): | |
received_data = LoRaIntegration.receive_data() | |
if received_data: | |
return decrypt_data(received_data) | |
else: | |
return None | |
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 | |