code: def _process_embeddings_response_for_mlflow_serving(self, response):
      try:
          validated_response = EmbeddingsResponse(**response)
          inference_data = validated_response.predictions
      except ValidationError as e:
          raise HTTPException(status_code=502, detail=str(e))
  
      return 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 6 for calling the MlflowModelServingProvider obj's underlying member method code with example usage: obj._process_embeddings_response_for_mlflow_serving(response) and returns: inference_data