rasahq--rasa/tests/core/training/test_interactive.py

import asyncio
import json
import os
import uuid
from collections import deque
from pathlib import Path
from typing import Any, Dict, List, Text, Tuple
from tests.conftest import AsyncMock

import pytest
from _pytest.monkeypatch import MonkeyPatch
from aioresponses import aioresponses
import unittest.mock
from unittest.mock import Mock

import rasa.shared.utils.io
import rasa.utils.io
from rasa.core.actions import action
from rasa.core.training import interactive
from rasa.shared.constants import (
    INTENT_MESSAGE_PREFIX,
    DEFAULT_SENDER_ID,
    DOCS_URL_POLICIES,
    LATEST_TRAINING_DATA_FORMAT_VERSION,
)
from rasa.shared.core.constants import ACTION_LISTEN_NAME, ACTION_UNLIKELY_INTENT_NAME
from rasa.shared.core.domain import Domain
from rasa.shared.core.events import BotUttered, ActionExecuted, UserUttered
from rasa.shared.core.trackers import DialogueStateTracker
from rasa.shared.core.training_data.story_reader.yaml_story_reader import (
    YAMLStoryReader,
)
from rasa.shared.importers.rasa import TrainingDataImporter
from rasa.shared.nlu.constants import TEXT
from rasa.shared.nlu.training_data.formats import RasaYAMLReader
from rasa.shared.nlu.training_data.loading import RASA, UNK, RASA_YAML
from rasa.shared.nlu.training_data.message import Message
from rasa.utils.endpoints import EndpointConfig
from tests import utilities


@pytest.fixture
def mock_endpoint() -> EndpointConfig:
    return EndpointConfig("https://example.com")


@pytest.fixture
def mock_file_importer(
    stack_config_path: Text, nlu_data_path: Text, stories_path: Text, domain_path: Text
):
    domain_path = domain_path
    return TrainingDataImporter.load_from_config(
        stack_config_path, domain_path, [nlu_data_path, stories_path]
    )


@pytest.mark.parametrize(
    "domain_file, expected_intents",
    [
        (
            "data/test_domains/default_unfeaturized_entities.yml",
            [
                "greet",
                "default",
                "goodbye",
                "thank",
                "ask",
                "why",
                "pure_intent",
            ],
        ),
        (
            "data/test_domains/default.yml",
            [
                "greet",
                "default",
                "goodbye",
            ],
        ),
    ],
)
def test_intent_names_from_domain(domain_file, expected_intents):
    test_domain = Domain.load(domain_file)

    intents = interactive.intent_names_from_domain(test_domain.as_dict())
    assert set(intents) == set(expected_intents)


async def test_send_message(mock_endpoint: EndpointConfig):
    sender_id = uuid.uuid4().hex

    url = f"{mock_endpoint.url}/conversations/{sender_id}/messages"
    with aioresponses() as mocked:
        mocked.post(url, payload={})

        await interactive.send_message(mock_endpoint, sender_id, "Hello")

        r = utilities.latest_request(mocked, "post", url)

        assert r

        expected = {"sender": "user", "text": "Hello", "parse_data": None}

        assert utilities.json_of_latest_request(r) == expected


async def test_request_prediction(mock_endpoint: EndpointConfig):
    sender_id = uuid.uuid4().hex

    url = f"{mock_endpoint.url}/conversations/{sender_id}/predict"

    with aioresponses() as mocked:
        mocked.post(url, payload={})

        await interactive.request_prediction(mock_endpoint, sender_id)

        assert utilities.latest_request(mocked, "post", url) is not None


def test_bot_output_format():
    message = {
        "event": "bot",
        "text": "Hello!",
        "data": {
            "image": "http://example.com/myimage.png",
            "attachment": "My Attachment",
            "buttons": [
                {"title": "yes", "payload": "/yes"},
                {"title": "no", "payload": "/no", "extra": "extra"},
            ],
            "elements": [
                {
                    "title": "element1",
                    "buttons": [{"title": "button1", "payload": "/button1"}],
                },
                {
                    "title": "element2",
                    "buttons": [{"title": "button2", "payload": "/button2"}],
                },
            ],
            "quick_replies": [
                {
                    "title": "quick_reply1",
                    "buttons": [{"title": "button3", "payload": "/button3"}],
                },
                {
                    "title": "quick_reply2",
                    "buttons": [{"title": "button4", "payload": "/button4"}],
                },
            ],
        },
    }
    from rasa.shared.core.events import Event

    bot_event = Event.from_parameters(message)

    assert isinstance(bot_event, BotUttered)

    formatted = interactive.format_bot_output(bot_event)
    assert formatted == (
        "Hello!\n"
        "Image: http://example.com/myimage.png\n"
        "Attachment: My Attachment\n"
        "Buttons:\n"
        "1: yes (/yes)\n"
        '2: no (/no) - {"extra": "extra"}\n'
        "Type out your own message...\n"
        "Elements:\n"
        '1: element1 - {"buttons": '
        '[{"payload": "/button1", "title": "button1"}]'
        '}\n2: element2 - {"buttons": '
        '[{"payload": "/button2", "title": "button2"}]'
        "}\nQuick replies:\n"
        '1: quick_reply1 - {"buttons": '
        '[{"payload": "/button3", "title": "button3"}'
        ']}\n2: quick_reply2 - {"buttons": '
        '[{"payload": "/button4", "title": "button4"}'
        "]}"
    )


def test_latest_user_message():
    tracker_dump = "data/test_trackers/tracker_moodbot.json"
    tracker_json = json.loads(rasa.shared.utils.io.read_file(tracker_dump))

    m = interactive.latest_user_message(tracker_json.get("events"))

    assert m is not None
    assert m["event"] == "user"
    assert m["text"] == "/mood_great"


def test_latest_user_message_on_no_events():
    m = interactive.latest_user_message([])

    assert m is None


def test_all_events_before_user_msg():
    tracker_dump = "data/test_trackers/tracker_moodbot.json"
    tracker_json = json.loads(rasa.shared.utils.io.read_file(tracker_dump))
    evts = tracker_json.get("events")

    m = all_events_before_latest_user_msg(evts)

    assert m is not None
    assert m == evts[:4]


def all_events_before_latest_user_msg(
    events: List[Dict[Text, Any]]
) -> List[Dict[Text, Any]]:
    """Return all events that happened before the most recent user message."""

    for i, e in enumerate(reversed(events)):
        if e.get("event") == UserUttered.type_name:
            return events[: -(i + 1)]
    return events


def test_all_events_before_user_msg_on_no_events():
    assert all_events_before_latest_user_msg([]) == []


async def test_print_history(mock_endpoint):
    tracker_dump = rasa.shared.utils.io.read_file(
        "data/test_trackers/tracker_moodbot.json"
    )

    sender_id = uuid.uuid4().hex

    url = "{}/conversations/{}/tracker?include_events=AFTER_RESTART".format(
        mock_endpoint.url, sender_id
    )
    with aioresponses() as mocked:
        mocked.get(url, body=tracker_dump, headers={"Accept": "application/json"})

        await interactive._print_history(sender_id, mock_endpoint)

        assert utilities.latest_request(mocked, "get", url) is not None


async def test_is_listening_for_messages(mock_endpoint):
    tracker_dump = rasa.shared.utils.io.read_file(
        "data/test_trackers/tracker_moodbot.json"
    )

    sender_id = uuid.uuid4().hex

    url = "{}/conversations/{}/tracker?include_events=APPLIED".format(
        mock_endpoint.url, sender_id
    )
    with aioresponses() as mocked:
        mocked.get(url, body=tracker_dump, headers={"Content-Type": "application/json"})

        is_listening = await interactive.is_listening_for_message(
            sender_id, mock_endpoint
        )

        assert is_listening


def test_splitting_conversation_at_restarts():
    tracker_dump = "data/test_trackers/tracker_moodbot.json"
    evts = json.loads(rasa.shared.utils.io.read_file(tracker_dump)).get("events")
    evts_wo_restarts = evts[:]
    evts.insert(2, {"event": "restart"})
    evts.append({"event": "restart"})

    split = interactive._split_conversation_at_restarts(evts)
    assert len(split) == 2
    assert [e for s in split for e in s] == evts_wo_restarts
    assert len(split[0]) == 2
    assert len(split[0]) == 2


def test_as_md_message():
    parse_data = {
        "text": "Hello there rasa.",
        "entities": [{"start": 12, "end": 16, "entity": "name", "value": "rasa"}],
        "intent": {"name": "greeting", "confidence": 0.9},
    }
    md = interactive._as_md_message(parse_data)
    assert md == "Hello there [rasa](name)."


@pytest.mark.parametrize(
    "parse_original, parse_annotated, expected_entities",
    [
        (
            {
                "text": "Hello there rasa, it's me, paula.",
                "entities": [
                    {
                        "start": 12,
                        "end": 16,
                        "entity": "name1",
                        "value": "rasa",
                        "extractor": "batman",
                    }
                ],
                "intent": {"name": "greeting", "confidence": 0.9},
            },
            {
                "text": "Hello there rasa, it's me, paula.",
                "entities": [
                    {"start": 12, "end": 16, "entity": "name1", "value": "rasa"},
                    {"start": 26, "end": 31, "entity": "name2", "value": "paula"},
                ],
                "intent": {"name": "greeting", "confidence": 0.9},
            },
            [
                {
                    "start": 12,
                    "end": 16,
                    "entity": "name1",
                    "value": "rasa",
                    "extractor": "batman",
                },
                {"start": 26, "end": 31, "entity": "name2", "value": "paula"},
            ],
        ),
        (
            {
                "text": "I am flying from Berlin to London.",
                "entities": [
                    {
                        "start": 17,
                        "end": 23,
                        "entity": "location",
                        "role": "from",
                        "value": "Berlin",
                        "extractor": "DIETClassifier",
                    }
                ],
                "intent": {"name": "inform", "confidence": 0.9},
            },
            {
                "text": "I am flying from Berlin to London.",
                "entities": [
                    {
                        "start": 17,
                        "end": 23,
                        "entity": "location",
                        "value": "Berlin",
                        "role": "from",
                    },
                    {
                        "start": 27,
                        "end": 33,
                        "entity": "location",
                        "value": "London",
                        "role": "to",
                    },
                ],
                "intent": {"name": "inform", "confidence": 0.9},
            },
            [
                {
                    "start": 17,
                    "end": 23,
                    "entity": "location",
                    "value": "Berlin",
                    "role": "from",
                },
                {
                    "start": 27,
                    "end": 33,
                    "entity": "location",
                    "value": "London",
                    "role": "to",
                },
            ],
        ),
        (
            {
                "text": "A large pepperoni and a small mushroom.",
                "entities": [
                    {
                        "start": 2,
                        "end": 7,
                        "entity": "size",
                        "group": "1",
                        "value": "large",
                        "extractor": "DIETClassifier",
                    },
                    {
                        "start": 24,
                        "end": 29,
                        "entity": "size",
                        "value": "small",
                        "extractor": "DIETClassifier",
                    },
                ],
                "intent": {"name": "inform", "confidence": 0.9},
            },
            {
                "text": "A large pepperoni and a small mushroom.",
                "entities": [
                    {
                        "start": 2,
                        "end": 7,
                        "entity": "size",
                        "group": "1",
                        "value": "large",
                    },
                    {
                        "start": 8,
                        "end": 17,
                        "entity": "toppings",
                        "group": "1",
                        "value": "pepperoni",
                    },
                    {
                        "start": 30,
                        "end": 38,
                        "entity": "toppings",
                        "group": "1",
                        "value": "mushroom",
                    },
                    {
                        "start": 24,
                        "end": 29,
                        "entity": "size",
                        "group": "2",
                        "value": "small",
                    },
                ],
                "intent": {"name": "inform", "confidence": 0.9},
            },
            [
                {
                    "start": 2,
                    "end": 7,
                    "entity": "size",
                    "group": "1",
                    "value": "large",
                },
                {
                    "start": 8,
                    "end": 17,
                    "entity": "toppings",
                    "group": "1",
                    "value": "pepperoni",
                },
                {
                    "start": 30,
                    "end": 38,
                    "entity": "toppings",
                    "group": "1",
                    "value": "mushroom",
                },
                {
                    "start": 24,
                    "end": 29,
                    "entity": "size",
                    "group": "2",
                    "value": "small",
                },
            ],
        ),
    ],
)
def test__merge_annotated_and_original_entities(
    parse_original: Dict[Text, Any],
    parse_annotated: Dict[Text, Any],
    expected_entities: List[Dict[Text, Any]],
):
    entities = interactive._merge_annotated_and_original_entities(
        parse_annotated, parse_original
    )
    assert entities == expected_entities


def test_validate_user_message():
    parse_data = {
        "text": "Hello there rasa.",
        "parse_data": {
            "entities": [{"start": 12, "end": 16, "entity": "name", "value": "rasa"}],
            "intent": {"name": "greeting", "confidence": 0.9},
        },
    }
    assert interactive._validate_user_regex(parse_data, ["greeting", "goodbye"])
    assert not interactive._validate_user_regex(parse_data, ["goodbye"])


async def test_undo_latest_msg(mock_endpoint):
    tracker_dump = rasa.shared.utils.io.read_file(
        "data/test_trackers/tracker_moodbot.json"
    )

    sender_id = uuid.uuid4().hex

    url = "{}/conversations/{}/tracker?include_events=ALL".format(
        mock_endpoint.url, sender_id
    )
    append_url = "{}/conversations/{}/tracker/events".format(
        mock_endpoint.url, sender_id
    )
    with aioresponses() as mocked:
        mocked.get(url, body=tracker_dump)
        mocked.post(append_url)

        await interactive._undo_latest(sender_id, mock_endpoint)

        r = utilities.latest_request(mocked, "post", append_url)

        assert r

        # this should be the events the interactive call send to the endpoint
        # these events should have the last utterance omitted
        corrected_event = utilities.json_of_latest_request(r)
        assert corrected_event["event"] == "undo"


async def test_write_stories_to_file(mock_endpoint: EndpointConfig, tmp_path):
    tracker_dump = rasa.shared.utils.io.read_file(
        "data/test_trackers/tracker_moodbot_with_new_utterances.json"
    )

    sender_id = uuid.uuid4().hex

    url = f"{mock_endpoint.url}/conversations/{sender_id}/tracker?include_events=ALL"
    append_url = f"{mock_endpoint.url}/conversations/{sender_id}/tracker/events"
    domain_url = f"{mock_endpoint.url}/domain"

    target_files = [
        {
            "name": str(tmp_path / "stories.yml"),
            "validator": YAMLStoryReader.is_stories_file,
        },
        {
            "name": str(tmp_path / "nlu.yml"),
            "validator": RasaYAMLReader.is_yaml_nlu_file,
        },
        {"name": str(tmp_path / "domain.yml"), "validator": lambda path: True},
    ]

    async def info() -> Tuple[Text, Text, Text]:
        return target_files[0]["name"], target_files[1]["name"], target_files[2]["name"]

    with aioresponses() as mocked:
        mocked.get(url, body=tracker_dump)
        mocked.post(append_url)
        mocked.get(domain_url, payload={})

        interactive._request_export_info = info
        await interactive._write_data_to_file(sender_id, mock_endpoint)

    for target_file in target_files:
        assert os.path.exists(target_file["name"])
        assert target_file["validator"](target_file["name"])


def test_utter_custom_message():
    test_event = """
      {
      "data": {
        "attachment": null,
        "buttons": null,
        "elements": [
          {
            "a": "b"
          }
        ]
      },
      "event": "bot",
      "text": null,
      "timestamp": 1542649219.331037
    }
    """
    actual = interactive._chat_history_table([json.loads(test_event)])

    assert json.dumps({"a": "b"}) in actual


async def test_interactive_domain_persistence(
    mock_endpoint: EndpointConfig, tmp_path: Path
):
    # Test method interactive._write_domain_to_file

    tracker_dump = "data/test_trackers/tracker_moodbot.json"
    tracker_json = rasa.shared.utils.io.read_json_file(tracker_dump)

    events = tracker_json.get("events", [])

    domain_path = str(tmp_path / "interactive_domain_save.yml")

    url = f"{mock_endpoint.url}/domain"
    with aioresponses() as mocked:
        mocked.get(url, payload={})

        serialised_domain = await interactive.retrieve_domain(mock_endpoint)
        old_domain = Domain.from_dict(serialised_domain)

        interactive._write_domain_to_file(domain_path, events, old_domain)

    saved_domain = rasa.shared.utils.io.read_config_file(domain_path)

    for default_action in action.default_actions():
        assert default_action.name() not in saved_domain["actions"]


async def test_write_domain_to_file_with_form(tmp_path: Path):
    domain_path = str(tmp_path / "domain.yml")
    form_name = "my_form"
    old_domain = Domain.from_yaml(
        f"""
        version: "{LATEST_TRAINING_DATA_FORMAT_VERSION}"
        actions:
        - utter_greet
        - utter_goodbye
        forms:
          {form_name}:
            required_slots: []
        intents:
        - greet
        """
    )

    events = [ActionExecuted(form_name), ActionExecuted(ACTION_LISTEN_NAME)]
    events = [e.as_dict() for e in events]

    interactive._write_domain_to_file(domain_path, events, old_domain)

    assert set(Domain.from_path(domain_path).action_names_or_texts) == set(
        old_domain.action_names_or_texts
    )


async def test_filter_intents_before_save_nlu_file(domain_path: Text):
    # Test method interactive._filter_messages
    from random import choice

    greet = {"text": "How are you?", "intent": "greet", "text_features": [0.5]}
    goodbye = {"text": "I am inevitable", "intent": "goodbye", "text_features": [0.5]}
    test_msgs = [Message(data=greet), Message(data=goodbye)]

    domain_file = domain_path
    domain = Domain.load(domain_file)
    intents = domain.intents

    msgs = test_msgs.copy()
    if intents:
        another_greet = greet.copy()
        another_greet[TEXT] = INTENT_MESSAGE_PREFIX + choice(intents)
        msgs.append(Message(data=another_greet))

    assert test_msgs == interactive._filter_messages(msgs)


@pytest.mark.parametrize(
    "path, expected_format",
    [("bla.json", RASA), ("other.yml", RASA_YAML), ("unknown", UNK)],
)
def test_get_nlu_target_format(path: Text, expected_format: Text):
    assert interactive._get_nlu_target_format(path) == expected_format


@pytest.mark.parametrize(
    "trackers, expected_trackers",
    [
        ([DialogueStateTracker.from_events("one", [])], [deque([]), DEFAULT_SENDER_ID]),
        (
            [
                str(i)
                for i in range(
                    interactive.MAX_NUMBER_OF_TRAINING_STORIES_FOR_VISUALIZATION + 1
                )
            ],
            [DEFAULT_SENDER_ID],
        ),
    ],
)
async def test_initial_plotting_call(
    mock_endpoint: EndpointConfig,
    monkeypatch: MonkeyPatch,
    trackers: List[Text],
    expected_trackers: List[Text],
    mock_file_importer: TrainingDataImporter,
):
    get_training_trackers = Mock(return_value=trackers)
    monkeypatch.setattr(interactive, "_get_training_trackers", get_training_trackers)

    monkeypatch.setattr(interactive.utils, "is_limit_reached", lambda _, __: True)

    plot_trackers = Mock()
    monkeypatch.setattr(interactive, "_plot_trackers", asyncio.coroutine(plot_trackers))

    url = f"{mock_endpoint.url}/domain"
    with aioresponses() as mocked:
        mocked.get(url, payload={})

        await interactive.record_messages(mock_endpoint, mock_file_importer)

    get_training_trackers.assert_called_once()
    plot_trackers.assert_called_once_with(
        expected_trackers, interactive.DEFAULT_STORY_GRAPH_FILE, mock_endpoint
    )


async def test_not_getting_trackers_when_skipping_visualization(
    mock_endpoint: EndpointConfig, monkeypatch: MonkeyPatch
):
    get_trackers = Mock()
    monkeypatch.setattr(interactive, "_get_tracker_events_to_plot", get_trackers)

    monkeypatch.setattr(interactive.utils, "is_limit_reached", lambda _, __: True)

    url = f"{mock_endpoint.url}/domain"
    with aioresponses() as mocked:
        mocked.get(url, payload={})

        await interactive.record_messages(
            mock_endpoint, mock_file_importer, skip_visualization=True
        )

    get_trackers.assert_not_called()


class QuestionaryConfirmMock:
    def __init__(self, tries: int) -> None:
        self.tries = tries

    def __call__(self, text: Text) -> "QuestionaryConfirmMock":
        return self

    async def ask_async(self) -> bool:
        self.tries -= 1
        if self.tries == 0:
            return False
        else:
            return True


async def test_retry_on_error_success(monkeypatch: MonkeyPatch):
    monkeypatch.setattr(interactive.questionary, "confirm", QuestionaryConfirmMock(3))

    m = Mock(return_value=None)
    await interactive._retry_on_error(m, "export_path", 1, a=2)
    m.assert_called_once_with("export_path", 1, a=2)


@pytest.mark.parametrize(
    "action_name, question, is_marked_as_correct, sent_action_name",
    [
        (
            ACTION_UNLIKELY_INTENT_NAME,
            f"The bot wants to run 'action_unlikely_intent' "
            f"to indicate that the last user message was unexpected "
            f"at this point in the conversation. "
            f"Check out UnexpecTEDIntentPolicy "
            f"({DOCS_URL_POLICIES}#unexpected-intent-policy) "
            f"to learn more. Is that correct?",
            True,
            ACTION_UNLIKELY_INTENT_NAME,
        ),
        (
            ACTION_UNLIKELY_INTENT_NAME,
            f"The bot wants to run 'action_unlikely_intent' "
            f"to indicate that the last user message was unexpected "
            f"at this point in the conversation. "
            f"Check out UnexpecTEDIntentPolicy "
            f"({DOCS_URL_POLICIES}#unexpected-intent-policy) "
            f"to learn more. Is that correct?",
            False,
            ACTION_UNLIKELY_INTENT_NAME,
        ),
        (
            "action_test",
            "The bot wants to run 'action_test', correct?",
            True,
            "action_test",
        ),
        (
            "action_test",
            "The bot wants to run 'action_test', correct?",
            False,
            "action_another_one",
        ),
    ],
)
async def test_correct_question_for_action_name_was_asked(
    monkeypatch: MonkeyPatch,
    mock_endpoint: EndpointConfig,
    action_name: Text,
    question: Text,
    is_marked_as_correct: bool,
    sent_action_name: Text,
):
    conversation_id = "conversation_id"
    policy = "policy"
    tracker = DialogueStateTracker.from_events("some_sender", [])

    monkeypatch.setattr(
        interactive, "retrieve_tracker", AsyncMock(return_value=tracker.current_state())
    )
    monkeypatch.setattr(
        interactive, "_ask_questions", AsyncMock(return_value=is_marked_as_correct)
    )
    monkeypatch.setattr(
        interactive,
        "_request_action_from_user",
        AsyncMock(return_value=("action_another_one", False)),
    )

    mocked_send_action = AsyncMock()
    monkeypatch.setattr(interactive, "send_action", mocked_send_action)

    mocked_confirm = Mock(return_value=None)
    monkeypatch.setattr(interactive.questionary, "confirm", mocked_confirm)

    # validate the action and make sure that the correct question was asked
    await interactive._validate_action(
        action_name, policy, 1.0, [], mock_endpoint, conversation_id
    )
    mocked_confirm.assert_called_once_with(question)
    args, kwargs = mocked_send_action.call_args_list[-1]
    assert args[2] == sent_action_name


async def test_retry_on_error_three_retries(monkeypatch: MonkeyPatch):
    monkeypatch.setattr(interactive.questionary, "confirm", QuestionaryConfirmMock(3))

    m = Mock(side_effect=PermissionError())
    with pytest.raises(PermissionError):
        await interactive._retry_on_error(m, "export_path", 1, a=2)
    c = unittest.mock.call("export_path", 1, a=2)
    m.assert_has_calls([c, c, c])


@pytest.mark.parametrize(
    "text,wrapping_width,true_wrapping_width",
    [
        ("abcdefgh", 8, 8),
        ("abcdefgh", 4, 4),
        ("abcdefgh", 50, 50),
        ("Well, hello there my friend!", 20, 20),
        ("我要去北京", 8, 4),
        (
            "牙龈出血的症状对应得疾病可能有：肥大性龈炎、骨髓增生异常综合征、"
            "口腔疾病、小儿出血性疾病、边缘性龈炎、获得性维生素K依赖性凝血因子异常、"
            "小儿白血病、回归热、坏死性龈口炎、青春期功能失调性子宫出血、郎-奥韦综合征、"
            "急性淋巴细胞白血病、感染性血小板减少性紫癜、单纯性牙周炎、单核细胞白血病、"
            "δ-贮存池病、小儿特发性血小板减少性紫癜、老年人真性红细胞增多症、"
            "急性根尖牙周炎、慢性根尖牙周炎、创伤性口炎、青少年牙周炎、慢性牙周炎",
            120,
            60,
        ),
    ],
)
def test_calc_true_wrapping_width(
    text: Text, wrapping_width: int, true_wrapping_width: int
) -> None:
    assert (
        interactive.calc_true_wrapping_width(text, wrapping_width)
        == true_wrapping_width
    )


def test_no_chat_history_overflow() -> None:
    """Should run without crashing.

    originally the long chinese utterance lead to a table width overflow and
    available width for new utterances being < 0."""
    events = [
        {
            "event": "action",
            "timestamp": 1619956299.2875981,
            "name": "action_session_start",
            "policy": None,
            "confidence": 1.0,
            "action_text": None,
            "hide_rule_turn": False,
        },
        {"event": "session_started", "timestamp": 1619956299.287627},
        {
            "event": "bot",
            "timestamp": 1619956324.2313201,
            "metadata": {"utter_action": "utter_long_chinese"},
            "text": "牙龈出血的症状对应得疾病可能有：肥大性龈炎、骨髓增生异常综合征、"
            "口腔疾病、小儿出血性疾病、边缘性龈炎、获得性维生素K依赖性凝血因子异常、"
            "小儿白血病、回归热、坏死性龈口炎、青春期功能失调性子宫出血、"
            "郎-奥韦综合征、急性淋巴细胞白血病、感染性血小板减少性紫癜、"
            "单纯性牙周炎、单核细胞白血病、δ-贮存池病、小儿特发性血小板减少性紫癜、"
            "老年人真性红细胞增多症、急性根尖牙周炎、慢性根尖牙周炎、创伤性口炎、"
            "青少年牙周炎、慢性牙周炎",
        },
        {
            "event": "user",
            "timestamp": 1619956299.509249,
            "text": "hi",
            "parse_data": {
                "intent": {
                    "id": -2517711783688260279,
                    "name": "greet",
                    "confidence": 1.0,
                },
                "entities": [],
                "text": "hi",
                "message_id": "4a95248b3c6b480c9550f9c19062e2bc",
                "metadata": {},
            },
            "input_channel": None,
            "message_id": "4a95248b3c6b480c9550f9c19062e2bc",
            "metadata": {},
        },
    ]

    rasa.core.training.interactive._chat_history_table(events)