code: def run_multi_modal_example(
      file_path: str,
      visualization: bool = False,
      with_tuning: bool = True,
      timeout: float = 10.0,
  ) -> float:
      """
      Runs FEDOT on multimodal data from the `Wine Reviews dataset
      <https://www.kaggle.com/datasets/zynicide/wine-reviews>`_.
      The dataset contains information about wine country, region, price, etc.
      with text features in the ``description`` column and other columns containing
      numerical and categorical features. It is a classification task for wine variety prediction.
  
      Args:
          file_path: path to the file with multimodal data.
          visualization: if True, then final pipeline will be visualised.
          with_tuning: if True, then pipeline will be tuned.
          timeout: overall fitting duration
  
      Returns:
          F1 metrics of the model.
      """
      task = "classification"
      path = fedot_project_root().joinpath(file_path)
      data = MultiModalData.from_csv(
          file_path=path,
          task=task,
          target_columns="variety",
          index_col=None,
      )
      fit_data, predict_data = train_test_data_setup(
          data, shuffle=True, split_ratio=0.7
      )
  
      automl_model = Fedot(
          problem=task,
          timeout=timeout,
          with_tuning=with_tuning,
          n_jobs=1,
      )
      automl_model.fit(features=fit_data, target=fit_data.target)
  
      _ = automl_model.predict(predict_data)
      metrics = automl_model.get_metrics(metric_names="f1")
  
      if visualization:
          automl_model.current_pipeline.show()
  
      print(f'F1 for validation sample is {round(metrics["f1"], 3)}')
  
      return metrics["f1"]
  
imports: from fedot import Fedot
  from fedot.core.data.data_split import train_test_data_setup
  from fedot.core.data.multi_modal import MultiModalData
  from fedot.core.utils import fedot_project_root
  from fedot.core.utils import set_random_seed
label_desc: Use image node_id 1 for calling a global function with example usage: run_multi_modal_example(file_path, visualization, with_tuning, timeout) and returns: metrics