class_docstr: Represents the predictions and metadata returned in response to a scoring request, such as a
  REST API request sent to the ``/invocations`` endpoint of an MLflow Model Server.
class_docstr_tok: ["Represents","the","predictions","and","metadata","returned","in","response","to","a","scoring","request",",","such","as","a","REST","API","request","sent","to","the","``","\/invocations","``","endpoint","of","an","MLflow","Model","Server","."]
code: def from_json(cls, json_str):
      try:
          parsed_response = json.loads(json_str)
      except Exception as e:
          raise MlflowException(
              "Predictions response contents are not valid JSON"
          ) from e
      if (
          not isinstance(parsed_response, dict)
          or "predictions" not in parsed_response
      ):
          raise MlflowException(
              f"Invalid response. Predictions response contents must be a dictionary"
              f" containing a 'predictions' field. Instead, received: {parsed_response}"
          )
      return PredictionsResponse(parsed_response)
  
file_path: mlflow/mlflow/deployments/__init__.py
imports: import contextlib
  import json
  from mlflow.deployments.base import BaseDeploymentClient
  from mlflow.deployments.databricks import DatabricksDeploymentClient, DatabricksEndpoint
  from mlflow.deployments.interface import get_deploy_client, run_local
  from mlflow.deployments.openai import OpenAIDeploymentClient
  from mlflow.deployments.utils import get_deployments_target, set_deployments_target
  from mlflow.exceptions import MlflowException
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
label_desc: Use image node_id 3 for calling the PredictionsResponse obj's underlying member method code with example usage: obj.from_json(cls, json_str) and returns: PredictionsResponse