use persistent mem

app.py

@@ -250,11 +250,11 @@ Our model is trained separately for different tasks, so it’s best to use the c
                     value=40,  # Replace with defaults that work for your model
                 )
 
-        # call_count_display = gr.Textbox(
-        #     label="Model Call Count", 
-        #     value=f"Model has been called {get_call_count()} times",
-        #     interactive=False
-        # )
+        call_count_display = gr.Textbox(
+            label="Model Call Count", 
+            value=f"Model has been called {get_call_count()} times",
+            interactive=False
+        )
     gr.on(
         triggers=[run_button.click, prompt.submit],
         fn=infer,
@@ -268,7 +268,7 @@ Our model is trained separately for different tasks, so it’s best to use the c
             num_inference_steps,
             lora_model,
         ],
-        outputs=[result, seed_display],
+        outputs=[result, seed_display, call_count_display],
     )
 
 if __name__ == "__main__":

model_call_counter.txt

@@ -0,0 +1 @@
+256