app.py

import gradio as gr
import paddlehub as hub

ernie_zeus = hub.Module(name='ernie_zeus')


def inference(task: str,
              text: str,
              min_dec_len: int = 2,
              seq_len: int = 512,
              topp: float = 0.9,
              penalty_score: float = 1.0):

    func = getattr(ernie_zeus, task)
    try:
        result = func(text, min_dec_len, seq_len, topp, penalty_score)
        return result
    except Exception as error:
        return str(error)

title = "ERNIE-Zeus"

description = "ERNIE-Zeus model, which supports Chinese text generates task."

block = gr.Blocks()

examples = [
    [
        'text_summarization',
        '在芬兰、瑞典提交“入约”申请近一个月来，北约成员国内部尚未对此达成一致意见。与此同时，俄罗斯方面也多次对北约“第六轮扩张”发出警告。据北约官网显示，北约秘书长斯托尔滕贝格将于本月12日至13日出访瑞典和芬兰，并将分别与两国领导人进行会晤。',
        4, 512, 0.0, 1.0
    ],
    [
        'copywriting_generation',
        '芍药香氛的沐浴乳',
        32, 512, 0.9, 1.2
    ],
    [
        'novel_continuation',
        '昆仑山可以说是天下龙脉的根源，所有的山脉都可以看作是昆仑的分支。这些分出来的枝枝杈杈，都可以看作是一条条独立的龙脉。',
        2, 512, 0.9, 1.2
    ],
    [
        'answer_generation',
        '杜鹃花怎么养？',
        2, 512, 0.9, 1.2
    ],
    [
        'couplet_continuation',
        '天增岁月人增寿',
        2, 512, 0.9, 1.0
    ],
    [
        'composition_generation',
        '诚以养德，信以修身',
        128, 512, 0.9, 1.2
    ],
    [
        'text_cloze',
        '她有着一双[MASK]的眼眸。',
        1, 512, 0.9, 1.0
    ],
]

with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
              <div
                style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                  margin-bottom: 10px;
                  justify-content: center;
                "
              >
              <img src="https://user-images.githubusercontent.com/22424850/187387422-f6c9ccab-7fda-416e-a24d-7d6084c46f67.jpg" alt="Paddlehub" width="40%">
              </div> 
              <div
                style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                  margin-bottom: 10px;
                  justify-content: center;
                ">
              <h1 style="font-weight: 900; margin-bottom: 7px;">
                  ERNIE-Zeus Demo
              </h1>
              </div> 
              <p style="margin-bottom: 10px; font-size: 94%">
                ERNIE-Zeus is a state-of-the-art Chinese text generates model.
              </p>
            </div>
        """
    )
    with gr.Group():
        text = gr.Textbox(
            label="input_text",
            placeholder="Please enter Chinese text.",
        )
        btn = gr.Button(value="Generate text")
        task = gr.Dropdown(label="task",
                           choices=[
                               'text_summarization',
                               'copywriting_generation',
                               'novel_continuation',
                               'answer_generation',
                               'couplet_continuation',
                               'composition_generation',
                               'text_cloze'
                           ],
                           value='text_summarization')

        min_dec_len = gr.Slider(minimum=1, maximum=511, value=1, label="min_dec_len", step=1, interactive=True)
        seq_len = gr.Slider(minimum=2, maximum=512, value=128, label="seq_len", step=1, interactive=True)
        topp = gr.Slider(minimum=0.0, maximum=1.0, value=1.0, label="topp", step=0.01, interactive=True)
        penalty_score = gr.Slider(minimum=1.0, maximum=2.0, value=1.0, label="penalty_score", step=0.01, interactive=True)

        text_gen = gr.Textbox(label="generated_text")

        ex = gr.Examples(examples=examples, fn=inference, inputs=[task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen, cache_examples=False)

        text.submit(inference, inputs=[task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen)
        btn.click(inference, inputs=[task, text, min_dec_len, seq_len, topp, penalty_score], outputs=text_gen)
        gr.HTML(
            """
                <div class="footer">
                    <p>Model by <a href="https://github.com/PaddlePaddle/PaddleHub" style="text-decoration: underline;" target="_blank">PaddleHub</a> and <a href="https://wenxin.baidu.com" style="text-decoration: underline;" target="_blank">文心大模型</a> - Gradio Demo by 🤗 Hugging Face
                    </p>
                </div>
                 
           """
        )

block.queue(max_size=100000, concurrency_count=100000).launch()