code: def test_evaluate_step_writes_card_with_model_and_run_links_on_databricks(
      monkeypatch,
      tmp_recipe_root_path: Path,
      tmp_recipe_exec_path: Path,
  ):
      workspace_host = "https://dev.databricks.com"
      workspace_id = 123456
      workspace_url = f"{workspace_host}?o={workspace_id}"
  
      monkeypatch.setenv("_DATABRICKS_WORKSPACE_HOST", workspace_host)
      monkeypatch.setenv("_DATABRICKS_WORKSPACE_ID", workspace_id)
  
      recipe_yaml = tmp_recipe_root_path.joinpath(
          _RECIPE_CONFIG_FILE_NAME
      )
      recipe_yaml.write_text(
          f"""
  recipe: "regression/v1"
  target_col: "y"
  experiment:
    tracking_uri: {mlflow.get_tracking_uri()}
  steps:
    evaluate:
      validation_criteria:
        - metric: root_mean_squared_error
          threshold: 1_000_000
  """
      )
  
      evaluate_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "evaluate", "outputs"
      )
      evaluate_step_output_dir.mkdir(parents=True)
  
      recipe_config = read_yaml(
          tmp_recipe_root_path, _RECIPE_CONFIG_FILE_NAME
      )
      evaluate_step = EvaluateStep.from_recipe_config(
          recipe_config, str(tmp_recipe_root_path)
      )
      evaluate_step.run(str(evaluate_step_output_dir))
  
      train_step_output_dir = tmp_recipe_exec_path.joinpath(
          "steps", "train", "outputs"
      )
      with open(train_step_output_dir / "run_id") as f:
          run_id = f.read()
  
      assert (evaluate_step_output_dir / "card.html").exists()
      with open(evaluate_step_output_dir / "card.html") as f:
          step_card_content = f.read()
  
      assert (
          f"<a href={workspace_url}#mlflow/experiments/1/runs/{run_id}>"
          in step_card_content
      )
      assert (
          f"<a href={workspace_url}#mlflow/experiments/1/runs/{run_id}/artifactPath/train/model>"
          in step_card_content
      )
  
imports: import os
  import shutil
  from pathlib import Path
  from unittest import mock
  import pytest
  from sklearn.datasets import load_diabetes, load_iris
  import mlflow
  from mlflow.exceptions import MlflowException
  from mlflow.recipes.steps.evaluate import EvaluateStep
  from mlflow.recipes.steps.split import _OUTPUT_TEST_FILE_NAME, _OUTPUT_VALIDATION_FILE_NAME
  from mlflow.recipes.steps.train import TrainStep
  from mlflow.recipes.utils import _RECIPE_CONFIG_FILE_NAME
  from mlflow.utils.file_utils import read_yaml
  from tests.recipes.helper_functions import train_and_log_classification_model, train_and_log_model
label_desc: Use image node_id 9 for calling a global function with example usage: test_evaluate_step_writes_card_with_model_and_run_links_on_databricks(monkeypatch, tmp_recipe_root_path, tmp_recipe_exec_path) without return types