demo.py

import gradio as gr

# Mock function for testing layout
def run_test_power(model_name, real_text, generated_text, N=10):
    return "Prediction: Human (Mocked)"

css = """
#header { text-align: center; font-size: 1.5em; margin-bottom: 20px; }
#output-text { font-weight: bold; font-size: 1.2em; }
"""

# Gradio App
with gr.Blocks(css=css) as app:
    with gr.Row():
        gr.HTML('<div id="header">Human or AI Text Detector</div>')
    with gr.Row():
        gr.Markdown(
            """
            [Paper](https://openreview.net/forum?id=z9j7wctoGV) | [Code](https://github.com/xLearn-AU/R-Detect) | [Contact](mailto:[email protected])
            """
        )
    with gr.Row():
        input_text = gr.Textbox(
            label="Input Text",
            placeholder="Enter the text to check",
            lines=8,
        )
    with gr.Row():
        model_name = gr.Dropdown(
            [
                "gpt2-medium",
                "gpt2-large",
                "t5-large",
                "t5-small",
                "roberta-base",
                "roberta-base-openai-detector",
                "falcon-rw-1b",
            ],
            label="Select Model",
            value="gpt2-medium",
        )
    with gr.Row():
        submit_button = gr.Button("Run Detection", variant="primary")
        clear_button = gr.Button("Clear", variant="secondary")
    with gr.Row():
        output = gr.Textbox(
            label="Prediction",
            placeholder="Prediction: Human or AI",
            elem_id="output-text",
        )
    submit_button.click(
        run_test_power, inputs=[model_name, "Example real text", input_text], outputs=output
    )
    clear_button.click(lambda: ("", ""), inputs=[], outputs=[input_text, output])

app.launch()