code: def load_model(model_uri, dst_path=None):
      """
      Load a Promptflow model from a local file or a run.
  
      :param model_uri: The location, in URI format, of the MLflow model. For example:
  
                        - ``/Users/me/path/to/local/model``
                        - ``relative/path/to/local/model``
                        - ``s3://my_bucket/path/to/model``
                        - ``runs:/<mlflow_run_id>/run-relative/path/to/model``
  
                        For more information about supported URI schemes, see
                        `Referencing Artifacts <https://www.mlflow.org/docs/latest/tracking.html#
                        artifact-locations>`_.
      :param dst_path: The local filesystem path to which to download the model artifact.
                       This directory must already exist. If unspecified, a local output
                       path will be created.
  
      :return: A Promptflow model instance
      """
      from promptflow import load_flow
  
      local_model_path = _download_artifact_from_uri(
          artifact_uri=model_uri, output_path=dst_path
      )
      model_data_path = os.path.join(
          local_model_path, _MODEL_FLOW_DIRECTORY
      )
      return load_flow(model_data_path)
  
imports: import logging
  import os
  import shutil
  from pathlib import Path
  from typing import Any, Dict, List, Optional, Union
  import pandas
  import yaml
  import mlflow
  from mlflow import pyfunc
  from mlflow.models import Model, ModelSignature
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.signature import _infer_signature_from_input_example
  from mlflow.models.utils import ModelInputExample, _save_example
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.utils.annotations import experimental
  from mlflow.utils.docstring_utils import LOG_MODEL_PARAM_DOCS, format_docstring
  from mlflow.utils.environment import _CONDA_ENV_FILE_NAME, _CONSTRAINTS_FILE_NAME, _PYTHON_ENV_FILE_NAME, _REQUIREMENTS_FILE_NAME, _mlflow_conda_env, _process_conda_env, _process_pip_requirements, _PythonEnv, _validate_env_arguments
  from mlflow.utils.file_utils import write_to
  from mlflow.utils.model_utils import _validate_and_copy_code_paths, _validate_and_prepare_target_save_path
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 7 for calling a global function with example usage: load_model(model_uri, dst_path) and returns: load_flow