Upload app.py

app.py

@@ -192,20 +192,58 @@ def process_pipeline(test_file):
     return eval_key, encodings, encrypted_quantized_encoding, encrypted_prediction
 
 if __name__ == "__main__":
+    """
+    with gr.Blocks() as demo:
+        print("Starting the FHE Model")
 
-    app = gr.Interface(
-        fn=process_pipeline,
-        inputs=[
-            gr.File(label="Test File"),
-        ],
-        outputs=[
+        inputs = [gr.File(label="Test File")]
+        outputs = [
             gr.Textbox(label="Evaluation Key"),
             gr.Textbox(label="Encodings"),
             gr.Textbox(label="Encrypted Quantized Encoding"),
             gr.Textbox(label="Encrypted Prediction"),
-        ],
-        title="FHE Model",
-        description="This is a FHE Model",
-    )
+        ]
+
+        run_bottn = gr.Button(label="Run")
+
+        run_bottn.click(
+            fn=process_pipeline,  # Pass process_pipeline directly
+            inputs=inputs,
+            outputs=outputs
+        )
+
+    demo.launch()
+
+
+    """
+    with gr.Blocks() as demo:
+        print("Starting the FHE Model")
+
+        
+        inputs = (
+            [
+                gr.File(label="Test File"),
+            ],
+        )
+        outputs = (
+            [
+                gr.Textbox(label="Evaluation Key"),
+                gr.Textbox(label="Encodings"),
+                gr.Textbox(label="Encrypted Quantized Encoding"),
+                gr.Textbox(label="Encrypted Prediction"),
+            ],
+        )
+        title = ("FHE Model",)
+        description = ("This is a FHE Model",)
+
+        #gr.Interface(fn, inputs, outputs, title=title, description=description).launch()
+
+        run_bottn = gr.Button("Run")
+
+        run_bottn.click(
+            fn=(process_pipeline()),
+            inputs=inputs, outputs=outputs
+        )
+
 
-    app.launch()  # share=True)
+    demo.launch() #share=True)