web_demo.py

import argparse
import models
import gradio as gr

MAX_TURNS = 20
MAX_BOXES = MAX_TURNS * 2

def predict(input, history=None):
    global model, args
    if history is None:
        history = []
    for response, history in model.run_web_demo(input, history):
        updates = []
        for query, response in history:
            updates.append(gr.update(visible=True, value="用户：" + query))
            updates.append(gr.update(visible=True, value=f"{args.model}：" + response))
        if len(updates) < MAX_BOXES:
            updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
        yield [history] + updates


if __name__ == "__main__":
    parser = argparse.ArgumentParser()
    parser.add_argument("model", choices=models.availabel_models)
    args = parser.parse_args()
    model = models.get_model(args)

    with gr.Blocks() as demo:
        state = gr.State([])
        text_boxes = []
        for i in range(MAX_BOXES):
            if i % 2 == 0:
                text_boxes.append(gr.Markdown(visible=False, label="提问："))
            else:
                text_boxes.append(gr.Markdown(visible=False, label="回复："))

        with gr.Row():
            with gr.Column(scale=4):
                txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", lines=11).style(
                    container=False)
            with gr.Column(scale=1):
                max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
                top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
                temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
                button = gr.Button("Generate")
        button.click(predict, [txt, state], [state] + text_boxes)
    demo.queue().launch(share=False, inbrowser=False, server_port=51234, server_name="0.0.0.0")