code: def predict_v2(module_info: dict, input: dict):
      """
  
      Predict with `serving` API of module.
  
      Args:
           module_info(dict): Module info include module name, method name and
                              other info.
           input(dict): Data to input to predict API.
  
      Returns:
          dict: Response after packaging by func `package_result`
  
      Examples:
          .. code-block:: python
  
              module_info = {'module_name': 'lac'}}
              data = {'text': ['今天天气很好']}
              predict_v2(module_info=module_info, input=data)
      """
      serving_method_name = module_info["method_name"]
      serving_method = getattr(
          module_info["module"], serving_method_name
      )
      predict_args = module_info["predict_args"].copy()
      predict_args.update(input)
  
      for item in serving_method.__code__.co_varnames:
          if item in module_info.keys():
              predict_args.update({item: module_info[item]})
      try:
          output = serving_method(**predict_args)
      except Exception as err:
          log.logger.error(traceback.format_exc())
          return package_result("101", str(err), "")
  
      return package_result("000", "", output)
  
imports: import socket
  import threading
  import time
  import traceback
  from multiprocessing import Process
  from threading import Lock
  import requests
  from flask import Flask
  from flask import redirect
  from flask import request
  from flask import Response
  from paddlehub.serving.model_service.base_model_service import cv_module_info
  from paddlehub.serving.model_service.base_model_service import nlp_module_info
  from paddlehub.serving.model_service.base_model_service import v2_module_info
  from paddlehub.utils import log
  from paddlehub.utils import utils
label_desc: Use image node_id 3 for calling a global function with example usage: predict_v2(module_info, input) and returns: package_result, package_result