Update app.py

app.py

@@ -167,9 +167,15 @@ with gr.Blocks(fill_height=True) as demo:
             btn_2 = gr.Button("Logout", visible=True, scale=0)
             btn_2.click(hide_and_show_panel, outputs=[panel_2, panel_1, user_text, input_text])  # Hide Panel 2 and show Panel 1
         with gr.Row():
-            start_input = gr.Textbox(label="Start Date:", placeholder="Enter date (e.g., 2023-09-01)", max_lines=1)
-            prediction_input = gr.Text(label="Month Prediction:", placeholder="Enter date (e.g., 2024-10-31)", max_lines=1)
-            range_input = gr.Slider(3, 10, 6, label="Window / Moving Average Period")
+            with gr.Column:               
+                start_input = gr.Textbox(label="Start Date:", placeholder="Enter date (e.g., 2023-09-01)", max_lines=1)
+                gr.Markdown("### Po")
+            with gr.Column:  
+                prediction_input = gr.Text(label="Month Prediction:", placeholder="Enter date (e.g., 2024-10-31)", max_lines=1)
+                gr.Markdown("### Po")
+            with gr.Column:  
+                range_input = gr.Slider(3, 10, 6, label="Window / Moving Average Period")
+                gr.Markdown("#### * Window = 3: With a 3-period window, the predictive model reacts more quickly to recent monthly payment fluctuations, but it may also include more noise and false signals. <br>* Window = 12: With a 12-period window, the predictive model adjusts more slowly and is less sensitive to small fluctuations, making it more reliable, but also slower to react to sharp changes.")
         
         table_ = gr.DataFrame(value=df, label="Predictions (consult 'revenue' column):")
         btn_update = gr.Button("Run Forecast")