Update app.py

app.py

@@ -23,34 +23,35 @@ def load_and_process_data(dataset_choice: str, num_rows: int) -> Dict[str, Any]:
         processed_data = data.head(num_rows)
 
         return {
-            "Processed Data": processed_data.to_dict()  # Convert DataFrame to dictionary for JSON serialization
+            "processed_data": processed_data.to_dict()  # Convert DataFrame to dictionary for JSON serialization
         }
     except Exception as e:
         # Log the exception
         print(f"Error processing data: {str(e)}")
         return {"error": "Unable to process data. Please check the logs for details."}
 
-# Create a Gradio interface with more features
+# Create a Gradio interface with updated components
 def create_interface():
-    # Interface inputs (updated for Gradio v5.x)
-    dataset_choice = gr.Dropdown(
+    # Interface inputs
+    dataset_choice = gr.components.Dropdown(
         choices=["Dask Data", "Polars Data", "Another Dask Data"], 
         label="Select Dataset"
     )
-    num_rows = gr.Slider(
-        minimum=1, maximum=100, default=5, label="Number of Rows to Display"
+    num_rows = gr.components.Slider(
+        minimum=1, maximum=100, value=5, label="Number of Rows to Display"
     )
 
     # Interface definition
-    demo = gr.Interface(
-        fn=load_and_process_data,
-        inputs=[dataset_choice, num_rows],  # User can select dataset and number of rows
-        outputs="json",  # Display output as JSON
-        title="Enhanced Dataset Loader Demo",
-        description="Interact with various datasets and select the amount of data to display.",
-        allow_flagging="never"  # Disable flagging if not needed
-    )
-
+    with gr.Blocks() as demo:
+        gr.Markdown("# Enhanced Dataset Loader Demo")
+        gr.Markdown("Interact with various datasets and select the amount of data to display.")
+        with gr.Row():
+            dataset_choice.render()
+            num_rows.render()
+        processed_data_output = gr.JSON(label="Processed Data")
+        processed_data_output.render()
+
+    demo.add(dataset_choice, num_rows, processed_data_output, load_and_process_data)
     demo.launch()
 
 if __name__ == "__main__":