class_docstr: Base class for `Recipe`s which convert configs to graph schemas.
docstr: Converts a config to a graph compatible model configuration.
  
  Args:
      config: The config which the `Recipe` is supposed to convert.
      cli_parameters: Potential CLI params which should be interpolated into the
          components configs.
      training_type: The current training type. Can be used to omit / add certain
          parts of the graphs.
      is_finetuning: If `True` then the components should load themselves from
          trained version of themselves instead of using `create` to start from
          scratch.
  
  Returns:
      The model configuration which enables to run the model as a graph for
      training and prediction.
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code: def graph_config_for_recipe(
      self,
      config: Dict,
      cli_parameters: Dict[Text, Any],
      training_type: TrainingType = TrainingType.BOTH,
      is_finetuning: bool = False,
  ) -> GraphModelConfiguration:
      """Converts a config to a graph compatible model configuration.
  
      Args:
          config: The config which the `Recipe` is supposed to convert.
          cli_parameters: Potential CLI params which should be interpolated into the
              components configs.
          training_type: The current training type. Can be used to omit / add certain
              parts of the graphs.
          is_finetuning: If `True` then the components should load themselves from
              trained version of themselves instead of using `create` to start from
              scratch.
  
      Returns:
          The model configuration which enables to run the model as a graph for
          training and prediction.
      """
      ...
  
file_path: rasa/rasa/engine/recipes/recipe.py
imports: from __future__ import annotations
  import abc
  from typing import Text, Dict, Any, Optional, Tuple, Set
  import rasa.shared.utils.io
  from rasa.engine.graph import GraphModelConfiguration
  from rasa.shared.exceptions import RasaException
  from rasa.shared.data import TrainingType
label_desc: Use image node_id 3 for calling the Recipe obj's underlying member method code with example usage: obj.graph_config_for_recipe(config, cli_parameters, training_type, is_finetuning) without return types