app.py

# original:
#import gradio as gr
#gr.Interface.load("models/sileod/deberta-v3-base-tasksource-nli").launch()

# chatGPT prompt1: Rewrite this program in python and gradio to load an example file with two input text fields and output of the classification field.

import gradio as gr

def classify_text(text1, text2):
    # Load pre-trained model
    model = gr.Interface.load("models/sileod/deberta-v3-base-tasksource-nli")
    
    # Perform classification on input text
    output = model.predict([text1, text2])[0]
    
    return output

# Create input fields
input_text1 = gr.Textbox(label="Input Text 1")
input_text2 = gr.Textbox(label="Input Text 2")

# Create output field
output_text = gr.Textbox(label="Classification Output")

# Create Gradio interface
gr.Interface(classify_text, 
             inputs=[input_text1, input_text2], 
             outputs=output_text, 
             examples=[["Example Text 1", "Example Text 2"]]).launch()