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fix: disable whisper, faster_whisper, and hugging_face transcriptions in linux build (#659)

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Chidi Williams 2024-01-05 19:09:26 +00:00 committed by GitHub
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commit c7be2f1578
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26 changed files with 512 additions and 342 deletions
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3
.coveragerc
View file

@ -5,6 +5,3 @@ omit =
[html]
directory = coverage/html
[report]
fail_under = 75

2
.github/workflows/ci.yml vendored
View file

@ -88,7 +88,6 @@ jobs:
include:
- os: macos-latest
- os: windows-latest
- os: ubuntu-20.04
steps:
- uses: actions/checkout@v3
with:
@ -298,7 +297,6 @@ jobs:
include:
- os: macos-latest
- os: windows-latest
- os: ubuntu-20.04
needs: [ build, test ]
if: startsWith(github.ref, 'refs/tags/')
steps:

7
Makefile
View file

@ -31,8 +31,13 @@ clean:
rm -f buzz/whisper_cpp.py
rm -rf dist/* || true
COVERAGE_THRESHOLD := 75
ifeq ($(UNAME_S),Linux)
COVERAGE_THRESHOLD := 70
endif
test: buzz/whisper_cpp.py translation_mo
pytest -vv --cov=buzz --cov-report=xml --cov-report=html --benchmark-skip
pytest -vv --cov=buzz --cov-report=xml --cov-report=html --benchmark-skip --cov-fail-under=${COVERAGE_THRESHOLD}
benchmarks: buzz/whisper_cpp.py translation_mo
pytest -vv --benchmark-only --benchmark-json benchmarks.json

63
buzz/model_loader.py
View file

@ -2,22 +2,38 @@ import enum
import hashlib
import logging
import os
import shutil
import subprocess
import sys
import tempfile
import warnings
from dataclasses import dataclass
from typing import Optional
import shutil
import faster_whisper
import huggingface_hub
import requests
import whisper
from PyQt6.QtCore import QObject, pyqtSignal, QRunnable
from platformdirs import user_cache_dir
from tqdm.auto import tqdm
whisper = None
faster_whisper = None
huggingface_hub = None
if sys.platform != "linux":
import faster_whisper
import whisper
import huggingface_hub
# Catch exception from whisper.dll not getting loaded.
# TODO: Remove flag and try-except when issue with loading
# the DLL in some envs is fixed.
LOADED_WHISPER_DLL = False
try:
import buzz.whisper_cpp as whisper_cpp # noqa: F401
LOADED_WHISPER_DLL = True
except ImportError:
logging.exception("")
class WhisperModelSize(str, enum.Enum):
TINY = "tiny"
@ -42,6 +58,38 @@ class ModelType(enum.Enum):
FASTER_WHISPER = "Faster Whisper"
OPEN_AI_WHISPER_API = "OpenAI Whisper API"
def supports_recording(self):
# Live transcription with OpenAI Whisper API not supported
return self != ModelType.OPEN_AI_WHISPER_API
def is_available(self):
if (
# Hide Whisper.cpp option if whisper.dll did not load correctly.
# See: https://github.com/chidiwilliams/buzz/issues/274,
# https://github.com/chidiwilliams/buzz/issues/197
(self == ModelType.WHISPER_CPP and not LOADED_WHISPER_DLL)
# Disable Whisper and Faster Whisper options
# on Linux due to execstack errors on Snap
or (
sys.platform == "linux"
and self
in (
ModelType.WHISPER,
ModelType.FASTER_WHISPER,
ModelType.HUGGING_FACE,
)
)
):
return False
return True
def is_manually_downloadable(self):
return self in (
ModelType.WHISPER,
ModelType.WHISPER_CPP,
ModelType.FASTER_WHISPER,
)
@dataclass()
class TranscriptionModel:
@ -76,6 +124,13 @@ class TranscriptionModel:
return
self.open_path(path=os.path.dirname(model_path))
@staticmethod
def default():
model_type = next(
model_type for model_type in ModelType if model_type.is_available()
)
return TranscriptionModel(model_type=model_type)
@staticmethod
def open_path(path: str):
if sys.platform == "win32":

20
buzz/recording_transcriber.py
View file

@ -1,25 +1,29 @@
import datetime
import logging
import sys
import threading
from typing import Optional
import numpy as np
import sounddevice
import whisper
from PyQt6.QtCore import QObject, pyqtSignal
from sounddevice import PortAudioError
from buzz import transformers_whisper
from buzz import transformers_whisper, whisper_audio
from buzz.model_loader import ModelType
from buzz.transcriber import TranscriptionOptions, WhisperCpp, whisper_cpp_params
from buzz.transformers_whisper import TransformersWhisper
if sys.platform != "linux":
import whisper
class RecordingTranscriber(QObject):
transcription = pyqtSignal(str)
finished = pyqtSignal()
error = pyqtSignal(str)
is_running = False
SAMPLE_RATE = whisper_audio.SAMPLE_RATE
MAX_QUEUE_SIZE = 10
def __init__(
@ -149,17 +153,15 @@ class RecordingTranscriber(QObject):
provided by Whisper if the microphone supports it, or else it uses the device's default
sample rate.
"""
whisper_sample_rate = whisper.audio.SAMPLE_RATE
sample_rate = whisper_audio.SAMPLE_RATE
try:
sounddevice.check_input_settings(
device=device_id, samplerate=whisper_sample_rate
)
return whisper_sample_rate
sounddevice.check_input_settings(device=device_id, samplerate=sample_rate)
return sample_rate
except PortAudioError:
device_info = sounddevice.query_devices(device=device_id)
if isinstance(device_info, dict):
return int(device_info.get("default_samplerate", whisper_sample_rate))
return whisper_sample_rate
return int(device_info.get("default_samplerate", sample_rate))
return sample_rate
def stream_callback(self, in_data: np.ndarray, frame_count, time_info, status):
# Try to enqueue the next block. If the queue is already full, drop the block.

2
buzz/store/keyring_store.py
View file

@ -18,7 +18,7 @@ class KeyringStore:
return ""
return password
except (KeyringLocked, KeyringError) as exc:
logging.error("Unable to read from keyring: %s", exc)
logging.warning("Unable to read from keyring: %s", exc)
return ""
def set_password(self, username: Key, password: str) -> None:

135
buzz/transcriber.py
View file

@ -17,31 +17,22 @@ from random import randint
from threading import Thread
from typing import Any, List, Optional, Tuple, Union, Set
import faster_whisper
import numpy as np
import openai
import stable_whisper
import tqdm
import whisper
from PyQt6.QtCore import QObject, pyqtSignal, pyqtSlot
from dataclasses_json import dataclass_json, config, Exclude
from whisper import tokenizer
from . import transformers_whisper
from buzz.model_loader import whisper_cpp
from . import transformers_whisper, whisper_audio
from .conn import pipe_stderr
from .locale import _
from .model_loader import TranscriptionModel, ModelType
# Catch exception from whisper.dll not getting loaded.
# TODO: Remove flag and try-except when issue with loading
# the DLL in some envs is fixed.
LOADED_WHISPER_DLL = False
try:
import buzz.whisper_cpp as whisper_cpp
LOADED_WHISPER_DLL = True
except ImportError:
logging.exception("")
if sys.platform != "linux":
import faster_whisper
import whisper
import stable_whisper
DEFAULT_WHISPER_TEMPERATURE = (0.0, 0.2, 0.4, 0.6, 0.8, 1.0)
@ -58,7 +49,108 @@ class Segment:
text: str
LANGUAGES = tokenizer.LANGUAGES
LANGUAGES = {
"en": "english",
"zh": "chinese",
"de": "german",
"es": "spanish",
"ru": "russian",
"ko": "korean",
"fr": "french",
"ja": "japanese",
"pt": "portuguese",
"tr": "turkish",
"pl": "polish",
"ca": "catalan",
"nl": "dutch",
"ar": "arabic",
"sv": "swedish",
"it": "italian",
"id": "indonesian",
"hi": "hindi",
"fi": "finnish",
"vi": "vietnamese",
"he": "hebrew",
"uk": "ukrainian",
"el": "greek",
"ms": "malay",
"cs": "czech",
"ro": "romanian",
"da": "danish",
"hu": "hungarian",
"ta": "tamil",
"no": "norwegian",
"th": "thai",
"ur": "urdu",
"hr": "croatian",
"bg": "bulgarian",
"lt": "lithuanian",
"la": "latin",
"mi": "maori",
"ml": "malayalam",
"cy": "welsh",
"sk": "slovak",
"te": "telugu",
"fa": "persian",
"lv": "latvian",
"bn": "bengali",
"sr": "serbian",
"az": "azerbaijani",
"sl": "slovenian",
"kn": "kannada",
"et": "estonian",
"mk": "macedonian",
"br": "breton",
"eu": "basque",
"is": "icelandic",
"hy": "armenian",
"ne": "nepali",
"mn": "mongolian",
"bs": "bosnian",
"kk": "kazakh",
"sq": "albanian",
"sw": "swahili",
"gl": "galician",
"mr": "marathi",
"pa": "punjabi",
"si": "sinhala",
"km": "khmer",
"sn": "shona",
"yo": "yoruba",
"so": "somali",
"af": "afrikaans",
"oc": "occitan",
"ka": "georgian",
"be": "belarusian",
"tg": "tajik",
"sd": "sindhi",
"gu": "gujarati",
"am": "amharic",
"yi": "yiddish",
"lo": "lao",
"uz": "uzbek",
"fo": "faroese",
"ht": "haitian creole",
"ps": "pashto",
"tk": "turkmen",
"nn": "nynorsk",
"mt": "maltese",
"sa": "sanskrit",
"lb": "luxembourgish",
"my": "myanmar",
"bo": "tibetan",
"tl": "tagalog",
"mg": "malagasy",
"as": "assamese",
"tt": "tatar",
"haw": "hawaiian",
"ln": "lingala",
"ha": "hausa",
"ba": "bashkir",
"jw": "javanese",
"su": "sundanese",
"yue": "cantonese",
}
@dataclass()
@ -168,6 +260,7 @@ class FileTranscriber(QObject):
try:
segments = self.transcribe()
except Exception as exc:
logging.error(exc)
self.error.emit(exc)
return
@ -230,8 +323,8 @@ class WhisperCppFileTranscriber(FileTranscriber):
model_path = self.model_path
logging.debug(
"Starting whisper_cpp file transcription, file path = %s, language = %s, task = %s, model_path = %s, "
"word level timings = %s",
"Starting whisper_cpp file transcription, file path = %s, language = %s, "
"task = %s, model_path = %s, word level timings = %s",
self.file_path,
self.language,
self.task,
@ -239,8 +332,8 @@ class WhisperCppFileTranscriber(FileTranscriber):
self.word_level_timings,
)
audio = whisper.audio.load_audio(self.file_path)
self.duration_audio_ms = len(audio) * 1000 / whisper.audio.SAMPLE_RATE
audio = whisper_audio.load_audio(self.file_path)
self.duration_audio_ms = len(audio) * 1000 / whisper_audio.SAMPLE_RATE
whisper_params = whisper_cpp_params(
language=self.language if self.language is not None else "",
@ -722,7 +815,7 @@ class WhisperCpp:
def transcribe(self, audio: Union[np.ndarray, str], params: Any):
if isinstance(audio, str):
audio = whisper.audio.load_audio(audio)
audio = whisper_audio.load_audio(audio)
logging.debug("Loaded audio with length = %s", len(audio))

13
buzz/transformers_whisper.py
View file

@ -1,9 +1,13 @@
import sys
from typing import Optional, Union
import numpy as np
import whisper
from tqdm import tqdm
from transformers import WhisperProcessor, WhisperForConditionalGeneration
WhisperProcessor = WhisperForConditionalGeneration = None
if sys.platform != "linux":
import whisper
from transformers import WhisperProcessor, WhisperForConditionalGeneration
def load_model(model_name_or_path: str):
@ -13,14 +17,13 @@ def load_model(model_name_or_path: str):
class TransformersWhisper:
SAMPLE_RATE = whisper.audio.SAMPLE_RATE
N_SAMPLES_IN_CHUNK = whisper.audio.N_SAMPLES
def __init__(
self, processor: WhisperProcessor, model: WhisperForConditionalGeneration
):
self.processor = processor
self.model = model
self.SAMPLE_RATE = whisper.audio.SAMPLE_RATE
self.N_SAMPLES_IN_CHUNK = whisper.audio.N_SAMPLES
# Patch implementation of transcribing with transformers' WhisperProcessor until long-form transcription and
# timestamps are available. See: https://github.com/huggingface/transformers/issues/19887,

50
buzz/whisper_audio.py Normal file
View file

@ -0,0 +1,50 @@
from subprocess import CalledProcessError, run
import numpy as np
SAMPLE_RATE = 16000
N_FFT = 400
HOP_LENGTH = 160
CHUNK_LENGTH = 30
N_SAMPLES = CHUNK_LENGTH * SAMPLE_RATE # 480000 samples in a 30-second chunk
def load_audio(file: str, sr: int = SAMPLE_RATE):
"""
Open an audio file and read as mono waveform, resampling as necessary
Parameters
----------
file: str
The audio file to open
sr: int
The sample rate to resample the audio if necessary
Returns
-------
A NumPy array containing the audio waveform, in float32 dtype.
"""
# This launches a subprocess to decode audio while down-mixing
# and resampling as necessary. Requires the ffmpeg CLI in PATH.
# fmt: off
cmd = [
"ffmpeg",
"-nostdin",
"-threads", "0",
"-i", file,
"-f", "s16le",
"-ac", "1",
"-acodec", "pcm_s16le",
"-ar", str(sr),
"-"
]
# fmt: on
try:
out = run(cmd, capture_output=True, check=True).stdout
except CalledProcessError as e:
raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e
return np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0

9
buzz/widgets/model_type_combo_box.py
View file

@ -4,7 +4,6 @@ from PyQt6.QtCore import pyqtSignal
from PyQt6.QtWidgets import QComboBox, QWidget
from buzz.model_loader import ModelType
from buzz.transcriber import LOADED_WHISPER_DLL
class ModelTypeComboBox(QComboBox):
@ -19,13 +18,11 @@ class ModelTypeComboBox(QComboBox):
super().__init__(parent)
if model_types is None:
model_types = [model_type for model_type in ModelType]
model_types = [
model_type for model_type in ModelType if model_type.is_available()
]
for model_type in model_types:
# Hide Whisper.cpp option is whisper.dll did not load correctly.
# See: https://github.com/chidiwilliams/buzz/issues/274, https://github.com/chidiwilliams/buzz/issues/197
if model_type == ModelType.WHISPER_CPP and LOADED_WHISPER_DLL is False:
continue
self.addItem(model_type.value)
self.currentTextChanged.connect(self.on_text_changed)

12
buzz/widgets/preferences_dialog/models/file_transcription_preferences.py
View file

@ -39,15 +39,19 @@ class FileTranscriptionPreferences:
def load(cls, settings: QSettings) -> "FileTranscriptionPreferences":
language = settings.value("language", None)
task = settings.value("task", Task.TRANSCRIBE)
model = settings.value("model", TranscriptionModel())
word_level_timings = settings.value("word_level_timings", False)
model: TranscriptionModel = settings.value(
"model", TranscriptionModel.default()
)
word_level_timings = bool(settings.value("word_level_timings", False))
temperature = settings.value("temperature", DEFAULT_WHISPER_TEMPERATURE)
initial_prompt = settings.value("initial_prompt", "")
output_formats = settings.value("output_formats", [])
output_formats = settings.value("output_formats", []) or []
return FileTranscriptionPreferences(
language=language,
task=task,
model=model,
model=model
if model.model_type.is_available()
else TranscriptionModel.default(),
word_level_timings=word_level_timings,
temperature=temperature,
initial_prompt=initial_prompt,

29
buzz/widgets/preferences_dialog/models_preferences_widget.py
View file

@ -23,6 +23,8 @@ from buzz.widgets.model_type_combo_box import ModelTypeComboBox
class ModelsPreferencesWidget(QWidget):
model: Optional[TranscriptionModel]
def __init__(
self,
progress_dialog_modality=Qt.WindowModality.WindowModal,
@ -31,8 +33,19 @@ class ModelsPreferencesWidget(QWidget):
super().__init__(parent)
self.model_downloader: Optional[ModelDownloader] = None
self.model = TranscriptionModel(
model_type=ModelType.WHISPER, whisper_model_size=WhisperModelSize.TINY
model_types = [
model_type
for model_type in ModelType
if model_type.is_available() and model_type.is_manually_downloadable()
]
self.model = (
TranscriptionModel(
model_type=model_types[0], whisper_model_size=WhisperModelSize.TINY
)
if model_types[0] is not None
else None
)
self.progress_dialog_modality = progress_dialog_modality
@ -40,12 +53,8 @@ class ModelsPreferencesWidget(QWidget):
layout = QFormLayout()
model_type_combo_box = ModelTypeComboBox(
model_types=[
ModelType.WHISPER,
ModelType.WHISPER_CPP,
ModelType.FASTER_WHISPER,
],
default_model=self.model.model_type,
model_types=model_types,
default_model=self.model.model_type if self.model is not None else None,
parent=self,
)
model_type_combo_box.changed.connect(self.on_model_type_changed)
@ -119,6 +128,10 @@ class ModelsPreferencesWidget(QWidget):
self.model_list_widget.expandToDepth(2)
self.model_list_widget.setHeaderHidden(True)
self.model_list_widget.setAlternatingRowColors(True)
if self.model is None:
return
for model_size in WhisperModelSize:
model = TranscriptionModel(
model_type=self.model.model_type, whisper_model_size=model_size

26
buzz/widgets/recording_transcriber_widget.py
View file

@ -12,14 +12,12 @@ from buzz.model_loader import (
ModelDownloader,
TranscriptionModel,
ModelType,
WhisperModelSize,
)
from buzz.recording import RecordingAmplitudeListener
from buzz.recording_transcriber import RecordingTranscriber
from buzz.settings.settings import Settings
from buzz.transcriber import (
TranscriptionOptions,
LOADED_WHISPER_DLL,
Task,
DEFAULT_WHISPER_TEMPERATURE,
)
@ -65,15 +63,20 @@ class RecordingTranscriberWidget(QWidget):
default_language = self.settings.value(
key=Settings.Key.RECORDING_TRANSCRIBER_LANGUAGE, default_value=""
)
model_types = [
model_type
for model_type in ModelType
if model_type.is_available() and model_type.supports_recording()
]
default_model: Optional[TranscriptionModel] = None
if len(model_types) > 0:
default_model = TranscriptionModel(model_type=model_types[0])
self.transcription_options = TranscriptionOptions(
model=self.settings.value(
key=Settings.Key.RECORDING_TRANSCRIBER_MODEL,
default_value=TranscriptionModel(
model_type=ModelType.WHISPER_CPP
if LOADED_WHISPER_DLL
else ModelType.WHISPER,
whisper_model_size=WhisperModelSize.TINY,
),
default_value=default_model,
),
task=self.settings.value(
key=Settings.Key.RECORDING_TRANSCRIBER_TASK,
@ -102,12 +105,7 @@ class RecordingTranscriberWidget(QWidget):
transcription_options_group_box = TranscriptionOptionsGroupBox(
default_transcription_options=self.transcription_options,
# Live transcription with OpenAI Whisper API not implemented
model_types=[
model_type
for model_type in ModelType
if model_type is not ModelType.OPEN_AI_WHISPER_API
],
model_types=model_types,
parent=self,
)
transcription_options_group_box.transcription_options_changed.connect(

235
poetry.lock generated
View file

@ -161,21 +161,22 @@ files = [
[[package]]
name = "attrs"
version = "23.1.0"
version = "23.2.0"
description = "Classes Without Boilerplate"
optional = false
python-versions = ">=3.7"
files = [
{ file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04" },
{ file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015" },
{ file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1" },
{ file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30" },
]
[package.extras]
cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
dev = ["attrs[docs,tests]", "pre-commit"]
dev = ["attrs[tests]", "pre-commit"]
docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
tests = ["attrs[tests-no-zope]", "zope-interface"]
tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
[[package]]
name = "autopep8"
@ -489,63 +490,63 @@ cron = ["capturer (>=2.4)"]
[[package]]
name = "coverage"
version = "7.3.4"
version = "7.4.0"
description = "Code coverage measurement for Python"
optional = false
python-versions = ">=3.8"
files = [
{ file = "coverage-7.3.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:aff2bd3d585969cc4486bfc69655e862028b689404563e6b549e6a8244f226df" },
{ file = "coverage-7.3.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:e4353923f38d752ecfbd3f1f20bf7a3546993ae5ecd7c07fd2f25d40b4e54571" },
{ file = "coverage-7.3.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ea473c37872f0159294f7073f3fa72f68b03a129799f3533b2bb44d5e9fa4f82" },
{ file = "coverage-7.3.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:5214362abf26e254d749fc0c18af4c57b532a4bfde1a057565616dd3b8d7cc94" },
{ file = "coverage-7.3.4-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f99b7d3f7a7adfa3d11e3a48d1a91bb65739555dd6a0d3fa68aa5852d962e5b1" },
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]
[[package]]
@ -2769,4 +2770,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
[metadata]
lock-version = "2.0"
python-versions = ">=3.9.13,<3.11"
content-hash = "fbf6f74ef9a08a29eee546c598925e282607d282773bd9204ac9ee9c7aece129"
content-hash = "7fa77e9810e1dfc8deb6d5df8ceada1267a6d832c6a0bbbf7d7d8e9363815369"

16
pyproject.toml
View file

@ -14,23 +14,29 @@ packages = [
[tool.poetry.dependencies]
python = ">=3.9.13,<3.11"
sounddevice = "^0.4.5"
torch = "1.12.1"
transformers = "~4.24.0"
appdirs = "^1.4.4"
humanize = "^4.4.0"
PyQt6 = "^6.4.0"
stable-ts = "1.0.2"
openai = "^0.27.1"
faster-whisper = "^0.4.1"
keyring = "^23.13.1"
openai-whisper = "v20231106"
platformdirs = "^3.5.3"
dataclasses-json = "^0.5.9"
ffmpeg-python = "0.2.0"
numpy = "^1.21.2"
# Only install on non-Linux to prevent execstack errors
stable-ts = { version = "1.0.2", markers = "sys_platform != 'linux'" }
faster-whisper = { version = "^0.4.1", markers = "sys_platform != 'linux'" }
openai-whisper = { version = "v20231106", markers = "sys_platform != 'linux'" }
torch = { version = "1.12.1", markers = "sys_platform != 'linux'" }
transformers = { version = "~4.24.0", markers = "sys_platform != 'linux'" }
[tool.poetry.group.dev.dependencies]
autopep8 = "^1.7.0"
pyinstaller = "^5.4.1"
# Lock to 2023.11 to fix error in 2023.12:
# AttributeError: module 'dataclasses' has no attribute '__version__'
pyinstaller-hooks-contrib = "2023.11"
six = "^1.16.0"
pytest = "^7.1.3"
pytest-cov = "^4.0.0"

6
tests/gui_test.py
View file

@ -22,7 +22,6 @@ from buzz.widgets.transcriber.hugging_face_search_line_edit import (
from buzz.widgets.transcriber.languages_combo_box import LanguagesComboBox
from buzz.widgets.transcriber.temperature_validator import TemperatureValidator
from buzz.widgets.about_dialog import AboutDialog
from buzz.model_loader import ModelType
from buzz.settings.settings import Settings
from buzz.transcriber import (
TranscriptionOptions,
@ -246,7 +245,4 @@ class TestTranscriptionOptionsGroupBox:
widget.model_type_combo_box.setCurrentIndex(1)
transcription_options: TranscriptionOptions = (
mock_transcription_options_changed.call_args[0][0]
)
assert transcription_options.model.model_type == ModelType.WHISPER_CPP
mock_transcription_options_changed.assert_called()

7
tests/mock_sounddevice.py
View file

@ -6,7 +6,8 @@ from unittest.mock import MagicMock
import numpy as np
import sounddevice
import whisper
from buzz import whisper_audio
mock_query_devices = [
{
@ -114,11 +115,11 @@ class MockInputStream(MagicMock):
self.thread.start()
def target(self):
sample_rate = whisper.audio.SAMPLE_RATE
sample_rate = whisper_audio.SAMPLE_RATE
file_path = os.path.join(
os.path.dirname(__file__), "../testdata/whisper-french.mp3"
)
audio = whisper.load_audio(file_path, sr=sample_rate)
audio = whisper_audio.load_audio(file_path, sr=sample_rate)
chunk_duration_secs = 1

95
tests/transcriber_benchmarks_test.py
View file

@ -1,95 +0,0 @@
import platform
from unittest.mock import Mock
import pytest
from buzz.model_loader import WhisperModelSize, ModelType, TranscriptionModel
from buzz.transcriber import (
FileTranscriptionOptions,
FileTranscriptionTask,
Task,
WhisperCppFileTranscriber,
TranscriptionOptions,
WhisperFileTranscriber,
FileTranscriber,
)
from tests.model_loader import get_model_path
def get_task(model: TranscriptionModel):
file_transcription_options = FileTranscriptionOptions(
file_paths=["testdata/whisper-french.mp3"]
)
transcription_options = TranscriptionOptions(
language="fr", task=Task.TRANSCRIBE, word_level_timings=False, model=model
)
model_path = get_model_path(transcription_options.model)
return FileTranscriptionTask(
file_path="testdata/audio-long.mp3",
transcription_options=transcription_options,
file_transcription_options=file_transcription_options,
model_path=model_path,
)
def transcribe(qtbot, transcriber: FileTranscriber):
mock_completed = Mock()
transcriber.completed.connect(mock_completed)
with qtbot.waitSignal(transcriber.completed, timeout=10 * 60 * 1000):
transcriber.run()
segments = mock_completed.call_args[0][0]
return segments
@pytest.mark.parametrize(
"transcriber",
[
pytest.param(
WhisperCppFileTranscriber(
task=(
get_task(
TranscriptionModel(
model_type=ModelType.WHISPER_CPP,
whisper_model_size=WhisperModelSize.TINY,
)
)
)
),
id="Whisper.cpp - Tiny",
),
pytest.param(
WhisperFileTranscriber(
task=(
get_task(
TranscriptionModel(
model_type=ModelType.WHISPER,
whisper_model_size=WhisperModelSize.TINY,
)
)
)
),
id="Whisper - Tiny",
),
pytest.param(
WhisperFileTranscriber(
task=(
get_task(
TranscriptionModel(
model_type=ModelType.FASTER_WHISPER,
whisper_model_size=WhisperModelSize.TINY,
)
)
)
),
id="Faster Whisper - Tiny",
marks=pytest.mark.skipif(
platform.system() == "Darwin",
reason="Error with libiomp5 already initialized on GH action runner: https://github.com/chidiwilliams/buzz/actions/runs/4657331262/jobs/8241832087",
),
),
],
)
def test_should_transcribe_and_benchmark(qtbot, benchmark, transcriber):
segments = benchmark(transcribe, qtbot, transcriber)
assert len(segments) > 0

14
tests/transcriber_test.py
View file

@ -3,6 +3,7 @@ import os
import pathlib
import platform
import shutil
import sys
import tempfile
import time
from typing import List
@ -141,11 +142,16 @@ class TestWhisperCppFileTranscriber:
)
mock_progress = Mock(side_effect=lambda value: print("progress: ", value))
mock_completed = Mock()
mock_error = Mock()
transcriber.progress.connect(mock_progress)
transcriber.completed.connect(mock_completed)
with qtbot.waitSignal(transcriber.completed, timeout=10 * 60 * 1000):
transcriber.error.connect(mock_error)
with qtbot.wait_signal(transcriber.completed, timeout=10 * 60 * 1000):
transcriber.run()
mock_error.assert_not_called()
mock_progress.assert_called()
segments = [
segment
@ -307,6 +313,9 @@ class TestWhisperFileTranscriber:
),
],
)
@pytest.mark.skipif(
sys.platform == "linux", reason="Avoid execstack errors on Snap"
)
def test_transcribe(
self,
qtbot: QtBot,
@ -356,6 +365,9 @@ class TestWhisperFileTranscriber:
assert len(segments[i].text) > 0
logging.debug(f"{segments[i].start} {segments[i].end} {segments[i].text}")
@pytest.mark.skipif(
sys.platform == "linux", reason="Avoid execstack errors on Snap"
)
def test_transcribe_from_folder_watch_source(self, qtbot):
file_path = tempfile.mktemp(suffix=".mp3")
shutil.copy("testdata/whisper-french.mp3", file_path)

5
tests/transformers_whisper_test.py
View file

@ -1,6 +1,11 @@
import sys
import pytest
from buzz.transformers_whisper import load_model
@pytest.mark.skipif(sys.platform == "linux", reason="Not supported on Linux")
class TestTransformersWhisper:
def test_should_transcribe(self):
model = load_model("openai/whisper-tiny")

2
tests/widgets/file_transcriber_widget_test.py
View file

@ -11,7 +11,6 @@ class TestFileTranscriberWidget:
widget = FileTranscriberWidget(
file_paths=["testdata/whisper-french.mp3"],
default_output_file_name="",
parent=None,
)
qtbot.add_widget(widget)
assert widget.windowTitle() == "whisper-french.mp3"
@ -20,7 +19,6 @@ class TestFileTranscriberWidget:
widget = FileTranscriberWidget(
file_paths=["testdata/whisper-french.mp3"],
default_output_file_name="",
parent=None,
)
qtbot.add_widget(widget)

22
tests/widgets/main_window_test.py
View file

@ -79,12 +79,11 @@ class TestMainWindow:
assert open_transcript_action.isEnabled()
window.close()
# @pytest.mark.skip(reason='Timing out or crashing')
def test_should_run_and_cancel_transcription_task(self, qtbot, tasks_cache):
window = MainWindow(tasks_cache=tasks_cache)
qtbot.add_widget(window)
self._start_new_transcription(window)
self._start_new_transcription(window, long_audio=True)
table_widget: QTableWidget = window.findChild(QTableWidget)
@ -205,12 +204,16 @@ class TestMainWindow:
window.close()
@staticmethod
def _start_new_transcription(window: MainWindow):
def _start_new_transcription(window: MainWindow, long_audio: bool = False):
with patch(
"PyQt6.QtWidgets.QFileDialog.getOpenFileNames"
) as open_file_names_mock:
open_file_names_mock.return_value = (
[get_test_asset("whisper-french.mp3")],
[
get_test_asset(
"audio-long.mp3" if long_audio else "whisper-french.mp3"
)
],
"",
)
new_transcription_action = TestMainWindow._get_toolbar_action(
@ -226,11 +229,18 @@ class TestMainWindow:
@staticmethod
def get_assert_task_status_callback(
table_widget: QTableWidget, row_index: int, expected_status: str
table_widget: QTableWidget,
row_index: int,
expected_status: str,
long_audio: bool = False,
):
def assert_task_status():
assert table_widget.rowCount() > 0
assert table_widget.item(row_index, 1).text() == "whisper-french.mp3"
assert (
table_widget.item(row_index, 1).text() == "audio-long.mp3"
if long_audio
else "whisper-french.mp3"
)
assert expected_status in table_widget.item(row_index, 4).text()
return assert_task_status

38
tests/widgets/model_type_combo_box_test.py
View file

@ -1,14 +1,38 @@
import sys
import pytest
from buzz.widgets.model_type_combo_box import ModelTypeComboBox
class TestModelTypeComboBox:
def test_should_display_items(self, qtbot):
@pytest.mark.parametrize(
"model_types",
[
pytest.param(
[
"Whisper",
"Whisper.cpp",
"Hugging Face",
"Faster Whisper",
"OpenAI Whisper API",
],
marks=pytest.mark.skipif(
sys.platform == "linux", reason="Skip on Linux"
),
),
pytest.param(
["Whisper.cpp", "OpenAI Whisper API"],
marks=pytest.mark.skipif(
sys.platform != "linux", reason="Skip on non-Linux"
),
),
],
)
def test_should_display_items(self, qtbot, model_types):
widget = ModelTypeComboBox()
qtbot.add_widget(widget)
assert widget.count() == 5
assert widget.itemText(0) == "Whisper"
assert widget.itemText(1) == "Whisper.cpp"
assert widget.itemText(2) == "Hugging Face"
assert widget.itemText(3) == "Faster Whisper"
assert widget.itemText(4) == "OpenAI Whisper API"
assert widget.count() == len(model_types)
for index, model_type in enumerate(model_types):
assert widget.itemText(index) == model_type

2
tests/widgets/preferences_dialog/folder_watch_preferences_widget_test.py
View file

@ -25,7 +25,7 @@ class TestFolderWatchPreferencesWidget:
file_transcription_options=FileTranscriptionPreferences(
language=None,
task=Task.TRANSCRIBE,
model=TranscriptionModel(),
model=TranscriptionModel.default(),
word_level_timings=False,
temperature=DEFAULT_WHISPER_TEMPERATURE,
initial_prompt="",

29
tests/widgets/preferences_dialog/models_preferences_widget_test.py
View file

@ -6,8 +6,6 @@ from PyQt6.QtWidgets import QComboBox, QPushButton
from pytestqt.qtbot import QtBot
from buzz.model_loader import (
get_whisper_file_path,
WhisperModelSize,
TranscriptionModel,
ModelType,
)
@ -20,9 +18,11 @@ from tests.model_loader import get_model_path
class TestModelsPreferencesWidget:
@pytest.fixture(scope="class")
def clear_model_cache(self):
file_path = get_whisper_file_path(size=WhisperModelSize.TINY)
if os.path.isfile(file_path):
os.remove(file_path)
for model_type in ModelType:
if model_type.is_available():
path = TranscriptionModel(model_type=model_type).get_local_model_path()
if path and os.path.isfile(path):
os.remove(path)
def test_should_show_model_list(self, qtbot):
widget = ModelsPreferencesWidget()
@ -55,11 +55,7 @@ class TestModelsPreferencesWidget:
)
qtbot.add_widget(widget)
model = TranscriptionModel(
model_type=ModelType.WHISPER, whisper_model_size=WhisperModelSize.TINY
)
assert model.get_local_model_path() is None
assert widget.model.get_local_model_path() is None
available_item = widget.model_list_widget.topLevelItem(1)
assert available_item.text(0) == "Available for Download"
@ -87,20 +83,15 @@ class TestModelsPreferencesWidget:
or _available_item.child(0).text(0) != "Tiny"
)
# model file exists
assert os.path.isfile(get_whisper_file_path(size=model.whisper_model_size))
assert os.path.isfile(widget.model.get_local_model_path())
qtbot.wait_until(callback=downloaded_model, timeout=60_000)
@pytest.fixture(scope="class")
def whisper_tiny_model_path(self) -> str:
return get_model_path(
transcription_model=TranscriptionModel(
model_type=ModelType.WHISPER, whisper_model_size=WhisperModelSize.TINY
)
)
def default_model_path(self) -> str:
return get_model_path(transcription_model=(TranscriptionModel.default()))
def test_should_show_downloaded_model(self, qtbot, whisper_tiny_model_path):
def test_should_show_downloaded_model(self, qtbot, default_model_path):
widget = ModelsPreferencesWidget()
widget.show()
qtbot.add_widget(widget)

12
tests/widgets/transcription_task_folder_watcher_test.py
View file

@ -4,7 +4,7 @@ from tempfile import mkdtemp
from pytestqt.qtbot import QtBot
from buzz.model_loader import TranscriptionModel
from buzz.model_loader import TranscriptionModel, ModelType
from buzz.transcriber import (
Task,
DEFAULT_WHISPER_TEMPERATURE,
@ -24,6 +24,12 @@ from buzz.widgets.transcription_task_folder_watcher import (
class TestTranscriptionTaskFolderWatcher:
def default_model(self):
model_type = next(
model_type for model_type in ModelType if model_type.is_available()
)
return TranscriptionModel(model_type=model_type)
def test_should_add_task_not_in_tasks(self, qtbot: QtBot):
input_directory = mkdtemp()
watcher = TranscriptionTaskFolderWatcher(
@ -35,7 +41,7 @@ class TestTranscriptionTaskFolderWatcher:
file_transcription_options=FileTranscriptionPreferences(
language=None,
task=Task.TRANSCRIBE,
model=TranscriptionModel(),
model=self.default_model(),
word_level_timings=False,
temperature=DEFAULT_WHISPER_TEMPERATURE,
initial_prompt="",
@ -76,7 +82,7 @@ class TestTranscriptionTaskFolderWatcher:
file_transcription_options=FileTranscriptionPreferences(
language=None,
task=Task.TRANSCRIBE,
model=TranscriptionModel(),
model=self.default_model(),
word_level_timings=False,
temperature=DEFAULT_WHISPER_TEMPERATURE,
initial_prompt="",