code: def load_model(model_uri, dst_path=None):
      """
      Load an OpenAI model from a local file or a run.
  
      Args:
          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>`_.
          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.
  
      Returns:
          A dictionary representing the OpenAI model.
      """
      local_model_path = _download_artifact_from_uri(
          artifact_uri=model_uri, output_path=dst_path
      )
      flavor_conf = _get_flavor_configuration(
          local_model_path, FLAVOR_NAME
      )
      _add_code_from_conf_to_system_path(local_model_path, flavor_conf)
      model_data_path = os.path.join(
          local_model_path, flavor_conf.get("data", MODEL_FILENAME)
      )
      return _load_model(model_data_path)
  
imports: import itertools
  import logging
  import os
  import warnings
  from string import Formatter
  from typing import Any, Dict, Optional, Set
  import yaml
  import mlflow
  from mlflow import pyfunc
  from mlflow.environment_variables import _MLFLOW_TESTING, MLFLOW_OPENAI_SECRET_SCOPE
  from mlflow.exceptions import MlflowException
  from mlflow.models import Model, ModelInputExample, ModelSignature
  from mlflow.models.model import MLMODEL_FILE_NAME
  from mlflow.models.utils import _save_example
  from mlflow.protos.databricks_pb2 import INVALID_PARAMETER_VALUE
  from mlflow.tracking._model_registry import DEFAULT_AWAIT_MAX_SLEEP_SECONDS
  from mlflow.tracking.artifact_utils import _download_artifact_from_uri
  from mlflow.types import ColSpec, Schema, TensorSpec
  from mlflow.utils.annotations import experimental
  from mlflow.utils.databricks_utils import check_databricks_secret_scope_access, is_in_databricks_runtime
  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 _add_code_from_conf_to_system_path, _get_flavor_configuration, _validate_and_copy_code_paths, _validate_and_prepare_target_save_path
  from mlflow.utils.openai_utils import REQUEST_URL_CHAT, REQUEST_URL_COMPLETIONS, REQUEST_URL_EMBEDDINGS, _OAITokenHolder, _OpenAIApiConfig, _OpenAIEnvVar, _validate_model_params
  from mlflow.utils.requirements_utils import _get_pinned_requirement
label_desc: Use image node_id 18 for calling a global function with example usage: load_model(model_uri, dst_path) and returns: _load_model