from types import SimpleNamespace
from unittest.mock import MagicMock

import pytest

from local_transcriber.backends.faster_whisper import FasterWhisperBackend
from local_transcriber.types import Word


def test_transcribe_returns_canonical_words(tmp_path):
    audio = tmp_path / "audio.wav"
    raw_word = SimpleNamespace(start=0.2, end=0.7, word=" Привет")
    raw_segment = SimpleNamespace(
        start=0.0,
        end=1.0,
        text=" Привет",
        words=[raw_word],
    )
    info = SimpleNamespace(duration=1.0, language="ru", language_probability=0.99)
    model = MagicMock()
    model.transcribe.return_value = (iter([raw_segment]), info)

    result = FasterWhisperBackend().transcribe(model, audio, language="ru")

    assert result.words == [Word(start=0.2, end=0.7, text=" Привет")]
    model.transcribe.assert_called_once_with(
        str(audio),
        language="ru",
        word_timestamps=True,
    )


def test_transcribe_rejects_nonempty_result_without_word_timestamps(tmp_path):
    raw_segment = SimpleNamespace(
        start=0.0,
        end=1.0,
        text=" Текст есть",
        words=None,
    )
    info = SimpleNamespace(duration=1.0, language="ru", language_probability=1.0)
    model = MagicMock()
    model.transcribe.return_value = (iter([raw_segment]), info)

    with pytest.raises(RuntimeError, match="пословные таймкоды"):
        FasterWhisperBackend().transcribe(model, tmp_path / "audio.wav", "ru")


def test_transcribe_rejects_one_nonempty_segment_without_word_timestamps(tmp_path):
    timestamped = SimpleNamespace(
        start=0.0,
        end=1.0,
        text=" Первое",
        words=[SimpleNamespace(start=0.0, end=1.0, word=" Первое")],
    )
    missing = SimpleNamespace(
        start=1.0,
        end=2.0,
        text=" Второе",
        words=None,
    )
    info = SimpleNamespace(duration=2.0, language="ru", language_probability=1.0)
    model = MagicMock()
    model.transcribe.return_value = (iter([timestamped, missing]), info)

    with pytest.raises(RuntimeError, match="пословные таймкоды"):
        FasterWhisperBackend().transcribe(model, tmp_path / "audio.wav", "ru")