def recipe_for_name(name: Optional[Text]) -> Recipe:
"""Returns `Recipe` based on an optional recipe identifier.
Args:
name: The identifier which is used to select a certain `Recipe`. If `None`
the default recipe will be used.
Returns:
A recipe which can be used to convert a given config to train and predict
graph schemas.
"""
from rasa.engine.recipes.default_recipe import DefaultV1Recipe
from rasa.engine.recipes.graph_recipe import GraphV1Recipe
if name is None:
rasa.shared.utils.io.raise_deprecation_warning(
"From Rasa Open Source 4.0.0 onwards it will be required to specify "
"a recipe in your model configuration. Defaulting to recipe "
f"'{DefaultV1Recipe.name}'."
)
return DefaultV1Recipe()
recipes = {
DefaultV1Recipe.name: DefaultV1Recipe,
GraphV1Recipe.name: GraphV1Recipe,
}
recipe_constructor = recipes.get(name)
if recipe_constructor:
return recipe_constructor()
raise InvalidRecipeException(
f"No recipe with name '{name}' was found. "
f"Available recipes are: "
f"'{DefaultV1Recipe.name}'."
)
def test_train_core_without_nlu_pipeline():
with pytest.raises(InvalidConfigException):
DefaultV1Recipe().graph_config_for_recipe(
{"policies": []},
{},
TrainingType.CORE,
)
def test_retrieve_via_invalid_module_path():
with pytest.raises(ImportError):
path = "rasa.core.policies.ted_policy.TEDPolicy1000"
DefaultV1Recipe().graph_config_for_recipe(
{"policies": [{
"name": path
}]}, {}, TrainingType.CORE)
def test_no_warnings_with_default_project(tmp_path: Path):
rasa.utils.common.copy_directory(Path("rasa/cli/initial_project"),
tmp_path)
importer = TrainingDataImporter.load_from_config(
config_path=str(tmp_path / "config.yml"),
domain_path=str(tmp_path / "domain.yml"),
training_data_paths=[str(tmp_path / "data")],
)
config, _missing_keys, _configured_keys = DefaultV1Recipe.auto_configure(
importer.get_config_file_for_auto_config(),
importer.get_config(),
TrainingType.END_TO_END,
)
graph_config = DefaultV1Recipe().graph_config_for_recipe(
config, cli_parameters={}, training_type=TrainingType.END_TO_END)
validator = DefaultV1RecipeValidator(graph_config.train_schema)
with pytest.warns(
UserWarning,
match="Slot auto-fill has been removed in 3.0") as records:
validator.validate(importer)
assert all([
warn.message.args[0].startswith("Slot auto-fill has been removed")
for warn in records.list
])
def test_nlu_do_not_raise_if_trainable_tokenizer():
config = rasa.shared.utils.io.read_yaml_file(
"data/test_config/config_pretrained_embeddings_mitie_zh.yml")
graph_config = DefaultV1Recipe().graph_config_for_recipe(config,
cli_parameters={})
importer = DummyImporter()
validator = DefaultV1RecipeValidator(graph_config.train_schema)
# Does not raise
validator.validate(importer)
def test_nlu_do_not_raise_if_two_tokenizers_with_end_to_end():
config = rasa.shared.utils.io.read_yaml_file(
"rasa/engine/recipes/config_files/default_config.yml")
graph_config = DefaultV1Recipe().graph_config_for_recipe(
config, cli_parameters={}, training_type=TrainingType.END_TO_END)
importer = DummyImporter()
validator = DefaultV1RecipeValidator(graph_config.train_schema)
# Does not raise
validator.validate(importer)
def test_retrieve_via_module_path():
model_config = DefaultV1Recipe().graph_config_for_recipe(
{"policies": [{
"name": "rasa.core.policies.ted_policy.TEDPolicy"
}]},
{},
TrainingType.CORE,
)
assert any(
issubclass(node.uses, TEDPolicy)
for node in model_config.train_schema.nodes.values())
assert any(
issubclass(node.uses, TEDPolicy)
for node in model_config.predict_schema.nodes.values())
def test_no_warnings_with_default_project(tmp_path: Path):
rasa.utils.common.copy_directory(Path("rasa/cli/initial_project"),
tmp_path)
importer = TrainingDataImporter.load_from_config(
config_path=str(tmp_path / "config.yml"),
domain_path=str(tmp_path / "domain.yml"),
training_data_paths=[str(tmp_path / "data")],
)
config, _missing_keys, _configured_keys = DefaultV1Recipe.auto_configure(
importer.get_config_file_for_auto_config(),
importer.get_config(),
TrainingType.END_TO_END,
)
graph_config = DefaultV1Recipe().graph_config_for_recipe(
config, cli_parameters={}, training_type=TrainingType.END_TO_END)
validator = DefaultV1RecipeValidator(graph_config.train_schema)
with pytest.warns(None) as records:
validator.validate(importer)
assert len(records) == 0