def test_nlu_intents_are_converted(tmpdir: Path):
converted_data_folder = tmpdir / "converted_data"
os.mkdir(converted_data_folder)
training_data_folder = tmpdir / "data"
os.makedirs(training_data_folder, exist_ok=True)
training_data_file = Path(training_data_folder) / "responses.md"
simple_nlg_md = ("## ask name\n"
"* chitchat/ask_name\n"
"- my name is Sara, Rasa's documentation bot!\n")
with open(training_data_file, "w") as f:
f.write(simple_nlg_md)
NLGMarkdownToYamlConverter().convert_and_write(training_data_file,
converted_data_folder)
assert len(os.listdir(converted_data_folder)) == 1
with open(f"{converted_data_folder}/responses_converted.yml", "r") as f:
content = f.read()
assert content == (
f'version: "{LATEST_TRAINING_DATA_FORMAT_VERSION}"\n'
"responses:\n"
" chitchat/ask_name:\n"
" - text: my name is Sara, Rasa's documentation bot!\n")
def _convert_nlg_data(args: argparse.Namespace) -> None:
from rasa.nlu.training_data.converters.nlg_markdown_to_yaml_converter import (
NLGMarkdownToYamlConverter, )
if args.format == "yaml":
_convert_to_yaml(args, NLGMarkdownToYamlConverter())
else:
print_error_and_exit(
"Could not recognize output format. Supported output formats: "
"'yaml'. Specify the desired output format with '--format'.")
def _convert_nlg_data(args: argparse.Namespace) -> None:
from rasa.nlu.training_data.converters.nlg_markdown_to_yaml_converter import (
NLGMarkdownToYamlConverter, )
if args.format == "yaml":
rasa.utils.common.run_in_loop(
_convert_to_yaml(args, NLGMarkdownToYamlConverter()))
telemetry.track_data_convert(args.format, "nlg")
else:
rasa.shared.utils.cli.print_error_and_exit(
"Could not recognize output format. Supported output formats: "
"'yaml'. Specify the desired output format with '--format'.")
def test_converter_filters_correct_files(training_data_file: Text,
should_filter: bool):
assert should_filter == NLGMarkdownToYamlConverter.filter(
Path(training_data_file))
