code: def chatbot_postprocess(response):
      response_json = response.json()
      chatbot_value = list(
          zip(
              response_json["conversation"]["past_user_inputs"],
              response_json["conversation"]["generated_responses"],
          )
      )
      return chatbot_value, response_json
  
imports: from __future__ import annotations
  import json
  import os
  import re
  import tempfile
  import warnings
  from pathlib import Path
  from typing import TYPE_CHECKING, Callable
  import httpx
  from gradio_client import Client
  from gradio_client import utils
  from gradio_client.client import Endpoint
  from gradio_client.documentation import document, set_documentation_group
  from packaging import version
  import gradio
  from gradio import components, utils
  from gradio.context import Context
  from gradio.exceptions import Error, GradioVersionIncompatibleError, ModelNotFoundError, TooManyRequestsError
  from gradio.external_utils import cols_to_rows, encode_to_base64, get_tabular_examples, postprocess_label, rows_to_cols, streamline_spaces_interface
  from gradio.processing_utils import extract_base64_data, save_base64_to_cache, to_binary
label_desc: Use image node_id 4 for calling a global function with example usage: chatbot_postprocess(response) and returns: chatbot_value,  response_json