code: def _process_chat_response_for_mlflow_serving(self, response):
      try:
          validated_response = ServingTextResponse(**response)
          inference_data = validated_response.predictions
      except ValidationError as e:
          raise HTTPException(status_code=502, detail=str(e))
  
      return [
          {
              "message": {"role": "assistant", "content": entry},
              "metadata": {},
          }
          for entry in inference_data
      ]
  
imports: import time
  from typing import List
  from fastapi import HTTPException
  from fastapi.encoders import jsonable_encoder
  from pydantic import BaseModel, StrictFloat, StrictStr, ValidationError, validator
  from mlflow.gateway.config import MlflowModelServingConfig, RouteConfig
  from mlflow.gateway.constants import MLFLOW_SERVING_RESPONSE_KEY
  from mlflow.gateway.providers.base import BaseProvider
  from mlflow.gateway.providers.utils import send_request
  from mlflow.gateway.schemas import chat, completions, embeddings
label_desc: Use image node_id 5 for calling the MlflowModelServingProvider obj's underlying member method code with example usage: obj._process_chat_response_for_mlflow_serving(response) and returns: unknown