class_docstr: Integration with the Ludwig declarative ML library.
code: def _call_model(df, model):
      predictions = dask.compute(model.predict(df)[0])[0]
      target_name = model.config["output_features"][0]["column"]
  
      if target_name not in df:
          predictions.columns = [target_name]
      else:
          predictions.columns = ["prediction"]
  
      predictions[f"{target_name}_explain"] = None
      joined = df.join(predictions)
  
      if "prediction" in joined:
          joined = joined.rename(
              {
                  target_name: f"{target_name}_original",
                  "prediction": target_name,
              },
              axis=1,
          )
      return joined
  
file_path: mindsdb/mindsdb/integrations/handlers/ludwig_handler/ludwig_handler.py
imports: from typing import Optional
  import dill
  import dask
  import pandas
  from ludwig.automl import auto_train
  from mindsdb.integrations.libs.base import BaseMLEngine
  from .utils import RayConnection
label_desc: Use image node_id 3 for calling the LudwigHandler obj's underlying member method code with example usage: obj._call_model(df, model) and returns: joined