Update app.py

app.py

@@ -145,7 +145,13 @@ def gradio_interface_function(template, text, size, is_example):
         return  # End the function since there was an error
 
     # Initialize the sliding window prediction process
-    prediction_generator = sliding_window_prediction(template, text, model, tokenizer, window_size=int(size))
+    # Check if size is a boolean (from examples) and use a default if it is
+    if isinstance(size, bool) or size == 'True':
+        window_size = 4000  # Use default window size for examples
+    else:
+        window_size = int(size)
+        
+    prediction_generator = sliding_window_prediction(template, text, model, tokenizer, window_size=window_size)
 
     # Iterate over the generator to return values at each step
     for progress, full_pred, html_content in prediction_generator: