1. import gradio as gr
2.  
3. def prediction_percentage():
4.     predictions = RFC.predict(X_test)
5.     rejected = sum(predictions)
6.     accepted = len(predictions) - sum(predictions)
7.     return {"Rejected": float(rejected)/len(predictions), "Accepted": float(accepted)/len(predictions)}
8.  
9. def prediction_result():
10.     predictions = RFC.predict(X_test)
11.     rejected = sum(predictions)
12.     accepted = len(predictions) - sum(predictions)
13.     return rejected,accepted
14.    
15.    
16. label = gr.Label()
17.  
18. predict_btn = gr.Button(value="Predict")
19. with gr.Blocks() as demo:
20.     with gr.Column():
21.         label = gr.Label()
22.         #text = gr.Text()
23.         #plot = gr.Plot()
24.         predict_btn = gr.Button(value="Percentage")
25.         interpret_btn = gr.Button(value="Predict")
26.  
27.         with gr.Row():
28.             predict_btn.click(
29.                 prediction_percentage,
30.                 inputs=[],
31.                 outputs=[label],
32.             )
33.  
34.         with gr.Row():
35.             interpret_btn.click(
36.                 prediction_result,
37.                 inputs=[],
38.                 outputs=[gr.outputs.Textbox(label="Rejected Transactions"),gr.outputs.Textbox(label="Accepted Transactions")],
39.             )
40.  
41. demo.launch()
42.  
43. interface = gr.Interface(prediction_result, inputs=[]
44.                          ,outputs=[gr.outputs.Textbox(label="Rejected Transactions"),gr.outputs.Textbox(label="Accepted Transactions")])
45. interface.launch()