Upload app.py

app.py

@@ -111,6 +111,8 @@ def encode_quantize_encrypt(test_file, eval_key):
     # expect [1, 53] but we get (53)
     # pdb.set_trace()
     # features = pickle.loads(open(os.path.join("features.pkl"), "rb").read())
+
+    
     encodings = extract_infos(test_file)
 
     encodings = list(map(lambda x: encodings[x], ugly))
@@ -190,11 +192,34 @@ 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")
+
+        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"),
+        ]
+
+        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")
 
-        fn = (process_pipeline,)
+        
         inputs = (
             [
                 gr.File(label="Test File"),
@@ -211,4 +236,14 @@ if __name__ == "__main__":
         title = ("FHE Model",)
         description = ("This is a FHE Model",)
 
+        #gr.Interface(fn, inputs, outputs, title=title, description=description).launch()
+
+        run_bottn = gr.Button(label="Run ")
+
+        run_bottn.click(
+            fn=(process_pipeline,),
+            inputs=inputs, outputs=outputs
+        )
+
+
     demo.launch() #share=True)