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