Create utils/flexflow_integration.py

utils/flexflow_integration.py

@@ -0,0 +1,25 @@
+# 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