def test_dump_trainable_entities(entity_extractor: Optional[Text],
expected_output: Text):
training_data_json = {
"rasa_nlu_data": {
"common_examples": [{
"text":
"test",
"intent":
"greet",
"entities": [{
"start": 0,
"end": 4,
"value": "random",
"entity": "word"
}],
}]
}
}
if entity_extractor is not None:
training_data_json["rasa_nlu_data"]["common_examples"][0]["entities"][
0]["extractor"] = entity_extractor
training_data_object = RasaReader().read_from_json(training_data_json)
md_dump = MarkdownWriter().dumps(training_data_object)
assert md_dump.splitlines()[1] == expected_output
def test_dump_entities(entity: Dict[Text, Any], expected_output: Text):
training_data_json = {
"rasa_nlu_data": {
"common_examples": [
{"text": "test", "intent": "greet", "entities": [entity]}
]
}
}
training_data_object = RasaReader().read_from_json(training_data_json)
md_dump = MarkdownWriter().dumps(training_data_object)
assert md_dump.splitlines()[1] == expected_output