Streamlit_code / utils /flexflow_integration.py
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Create utils/flexflow_integration.py
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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