class_docstr: Wrapper for locally served model.
  
  The purpose of ServedModelWrapper is to provide an abstraction
  for locally served models. This allows us to use the same code in
  RAIInsights for loaded models that can run in the same environment and
  also for locally served models.
  
  Locally served in this case means on localhost via HTTP.
  This could be in a separate conda environment, or even in a Docker
  container.
  
  :param port: The port on which the model is served.
  :type port: int
class_docstr_tok: ["Wrapper","for","locally","served","model",".","The","purpose","of","ServedModelWrapper","is","to","provide","an","abstraction","for","locally","served","models",".","This","allows","us","to","use","the","same","code","in","RAIInsights","for","loaded","models","that","can","run","in","the","same","environment","and","also","for","locally","served","models",".","Locally","served","in","this","case","means","on","localhost","via","HTTP",".","This","could","be","in","a","separate","conda","environment",",","or","even","in","a","Docker","container",".",":","param","port",":","The","port","on","which","the","model","is","served",".",":","type","port",":","int"]
code: def __init__(self, port):
      self.port = port
  
imports: import json
  import requests
  from responsibleai.serialization_utilities import serialize_json_safe
label_desc: Use image node_id 1 to create a new ServedModelWrapper object  with example: obj = ServedModelWrapper(port)