Function test_train_nlu_success

tests/test_server.py:330–365

(
    rasa_app: SanicASGITestClient,
    stack_config_path: Text,
    nlu_data_path: Text,
    domain_path: Text,
    tmp_path_factory: TempPathFactory,
)

async def test_train_nlu_success(
    rasa_app: SanicASGITestClient,
    stack_config_path: Text,
    nlu_data_path: Text,
    domain_path: Text,
    tmp_path_factory: TempPathFactory,
):
    domain_data = rasa.shared.utils.io.read_yaml_file(domain_path)
    config_data = rasa.shared.utils.io.read_yaml_file(stack_config_path)
    nlu_data = rasa.shared.utils.io.read_yaml_file(nlu_data_path)

    # combine all data into our payload
    payload = {
        key: val for d in [domain_data, config_data, nlu_data] for key, val in d.items()
    }

    data = StringIO()
    rasa.shared.utils.io.write_yaml(payload, data)

    _, response = await rasa_app.post(
        "/model/train",
        data=data.getvalue(),
        headers={"Content-type": rasa.server.YAML_CONTENT_TYPE},
    )
    assert response.status == HTTPStatus.OK

    # save model to temporary file
    model_path = str(Path(tmp_path_factory.mktemp("model_dir")) / "model.tar.gz")
    with open(model_path, "wb") as f:
        f.write(response.body)

    storage_path = tmp_path_factory.mktemp("storage_path")
    model_storage, model_metadata = LocalModelStorage.from_model_archive(
        storage_path, model_path
    )
    assert model_metadata.model_id


async def test_train_core_success_with(