async def test_testing_with_utilizing_retrieval_intents(
response_selector_agent: Agent, response_selector_test_stories: Path,
tmp_path: Path):
result = await rasa.core.test.test(
stories=response_selector_test_stories,
agent=response_selector_agent,
e2e=True,
out_directory=str(tmp_path),
disable_plotting=True,
warnings=False,
)
failed_stories_path = tmp_path / "failed_test_stories.yml"
failed_stories = read_yaml(read_file(failed_stories_path, "utf-8"))
# check that the intent is shown correctly in the failed test stories file
target_intents = {
"test 0": "chitchat/ask_name",
"test 1": "chitchat/ask_name",
"test 2": "chitchat",
"test 3": "chitchat",
}
for story in failed_stories["stories"]:
test_name = story["story"].split("-")[0].strip()
assert story["steps"][0]["intent"] == target_intents[test_name]
# check that retrieval intent for actions is retrieved correctly
# and only when it's needed.
target_actions = {
"utter_chitchat": "utter_chitchat",
"utter_chitchat/ask_name": "utter_chitchat/ask_name",
"utter_chitchat/ask_weather": "utter_chitchat/ask_name",
"utter_goodbye": "utter_chitchat/ask_name",
}
predicted_actions = result["actions"][::2]
for predicted_action in predicted_actions:
assert (target_actions[predicted_action["action"]] ==
predicted_action["predicted"])
def is_markdown_nlg_file(filename: Union[Text, Path]) -> bool:
"""Checks if given file contains NLG training data.
Args:
filename: Path to the training data file.
Returns:
`True` if file contains NLG training data, `False` otherwise.
"""
content = io_utils.read_file(filename)
return re.search(NLG_MARKDOWN_MARKER_REGEX, content) is not None
def json_unpickle(file_name: Union[Text, Path]) -> Any:
"""Unpickle an object from file using json.
Args:
file_name: the file to load the object from
Returns: the object
"""
import jsonpickle.ext.numpy as jsonpickle_numpy
import jsonpickle
jsonpickle_numpy.register_handlers()
file_content = read_file(file_name)
return jsonpickle.loads(file_content)
def read_config_file(filename: Text) -> Dict[Text, Any]:
"""Parses a yaml configuration file. Content needs to be a dictionary
Args:
filename: The path to the file which should be read.
"""
content = read_yaml(read_file(filename))
if content is None:
return {}
elif isinstance(content, dict):
return content
else:
raise ValueError("Tried to load invalid config file '{}'. "
"Expected a key value mapping but found {}"
".".format(filename, type(content)))