code: def create_gradio_app(self):
      import gradio as gr
  
      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(self, task)
          try:
              result = func(
                  text, min_dec_len, seq_len, topp, penalty_score
              )
              return result
          except Exception as error:
              return str(error)
  
      examples = [
          [
              "text_summarization",
              "外媒7月18日报道，阿联酋政府当日证实该国将建设首个核电站，以应对不断上涨的用电需求。分析称阿联酋作为世界第三大石油出口国，更愿意将该能源用于出口，而非发电。首座核反应堆预计在2017年运行。cntv李婉然编译报道",
              4,
              512,
              0.3,
              1.0,
          ],
          ["copywriting_generation", "芍药香氛的沐浴乳", 8, 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", "做生意的基本原则是什么？", 2, 512, 0.5, 1.2],
          ["couplet_continuation", "天增岁月人增寿", 2, 512, 1.0, 1.0],
          ["composition_generation", "拔河比赛", 128, 512, 0.9, 1.2],
          ["text_cloze", "她有着一双[MASK]的眼眸。", 1, 512, 0.3, 1.2],
      ]
  
      text = gr.Textbox(
          label="input_text",
          placeholder="Please enter Chinese 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.Text(label="generated_text")
      interface = gr.Interface(
          inference,
          [task, text, min_dec_len, seq_len, topp, penalty_score],
          [text_gen],
          examples=examples,
          allow_flagging="never",
          title="ERNIE-Zeus",
      )
      return interface
  
imports: import argparse
  import json
  import os
  import requests
  from paddlehub.module.module import moduleinfo
  from paddlehub.module.module import runnable
  from paddlehub.module.module import serving
label_desc: Use image node_id 12 for calling the ERNIEZeus obj's underlying member method code with example usage: obj.create_gradio_app() and returns: interface, result, str