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import pytest
from scraibe import Scraibe, Diariser, Transcriber, Transcript
import os
@pytest.fixture
def create_scraibe_instance():
if "HF_TOKEN" in os.environ:
return Scraibe(use_auth_token=os.environ["HF_TOKEN"], whisper_model= "tiny")
else:
return Scraibe()
def test_scraibe_init(create_scraibe_instance):
model = create_scraibe_instance
assert isinstance(model.transcriber, Transcriber)
assert isinstance(model.diariser, Diariser)
def test_scraibe_autotranscribe(create_scraibe_instance):
model = create_scraibe_instance
transcript = model.autotranscribe('tests/audio_test_2.mp4')
assert isinstance(transcript, Transcript)
def test_scraibe_diarization(create_scraibe_instance):
model = create_scraibe_instance
diarisation_result = model.diarization('tests/audio_test_2.mp4')
assert isinstance(diarisation_result, dict)
def test_scraibe_transcribe(create_scraibe_instance):
model = create_scraibe_instance
transcription_result = model.transcribe('tests/audio_test_2.mp4')
assert isinstance(transcription_result, str)
""" def test_remove_audio_file(create_scraibe_instance):
model = create_scraibe_instance
with pytest.raises(ValueError):
model.remove_audio_file("non_existing_audio_file")
model.remove_audio_file("audio_test_2.mp4")
assert not os.path.exists("audio_test_2.mp4") """
""" def test_get_audio_file(create_scraibe_instance):
model = create_scraibe_instance
audio_file = os.path.exist("audio_test_2.mp4")
assert isinstance(audio_file, AudioProcessor)
assert isinstance(audio_file.waveform, torch.Tensor)
assert isinstance(audio_file.sr, torch.Tensor) """
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