code: def __initialize_dbt() -> None:
      """Invoke the dbt runner from the appropriate directory so we can fetch the relevant adapter.
  
      We use the debug command to initialize the profile and make it accessible. This has the nice property of
      triggering a failure with reasonable error messages in the event the dbt configs are not set up correctly.
      """
      dbtRunner().invoke(
          ["debug"],
          project_dir=dbt_project_dir(),
          PROFILES_DIR=dbt_project_dir(),
      )
  
imports: from __future__ import annotations
  import json
  import logging
  import os
  from typing import Generator
  import pytest
  import sqlalchemy
  from dbt.adapters.factory import get_adapter_by_type
  from dbt.cli.main import dbtRunner
  from metricflow.protocols.sql_client import SqlClient
  from metricflow.test.fixtures.setup_fixtures import MetricFlowTestSessionState, dbt_project_dir, dialect_from_url
  from metricflow.test.fixtures.sql_clients.adapter_backed_ddl_client import AdapterBackedDDLSqlClient
  from metricflow.test.fixtures.sql_clients.common_client import SqlDialect
  from metricflow.test.fixtures.sql_clients.ddl_sql_client import SqlClientWithDDLMethods
label_desc: Use image node_id 4 for calling a global function with example usage: __initialize_dbt() without return types