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

.coveragerc

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

.github/workflows/ci.yml

@@ -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:

Makefile

@@ -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

buzz/model_loader.py

@@ -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":

buzz/recording_transcriber.py

@@ -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(
+            sounddevice.check_input_settings(device=device_id, samplerate=sample_rate)
-                device=device_id, samplerate=whisper_sample_rate
+            return sample_rate
-            )
-            return whisper_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 int(device_info.get("default_samplerate", sample_rate))
-            return whisper_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.

buzz/store/keyring_store.py

@@ -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:

buzz/transcriber.py

@@ -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.
+if sys.platform != "linux":
-# TODO: Remove flag and try-except when issue with loading
+    import faster_whisper
-# the DLL in some envs is fixed.
+    import whisper
-LOADED_WHISPER_DLL = False
+    import stable_whisper
-try:
-    import buzz.whisper_cpp as whisper_cpp
-
-    LOADED_WHISPER_DLL = True
-except ImportError:
-    logging.exception("")
 
 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, "
+            "Starting whisper_cpp file transcription, file path = %s, language = %s, "
-            "word level timings = %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)
+        audio = whisper_audio.load_audio(self.file_path)
-        self.duration_audio_ms = len(audio) * 1000 / whisper.audio.SAMPLE_RATE
+        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))
 

buzz/transformers_whisper.py

@@ -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,

buzz/whisper_audio.py

@@ -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

buzz/widgets/model_type_combo_box.py

@@ -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)

buzz/widgets/preferences_dialog/models/file_transcription_preferences.py

@@ -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())
+        model: TranscriptionModel = settings.value(
-        word_level_timings = settings.value("word_level_timings", False)
+            "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,

buzz/widgets/preferences_dialog/models_preferences_widget.py

@@ -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=[
+            model_types=model_types,
-                ModelType.WHISPER,
+            default_model=self.model.model_type if self.model is not None else None,
-                ModelType.WHISPER_CPP,
-                ModelType.FASTER_WHISPER,
-            ],
-            default_model=self.model.model_type,
             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

buzz/widgets/recording_transcriber_widget.py

@@ -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(
+                default_value=default_model,
-                    model_type=ModelType.WHISPER_CPP
-                    if LOADED_WHISPER_DLL
-                    else ModelType.WHISPER,
-                    whisper_model_size=WhisperModelSize.TINY,
-                ),
             ),
             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_types,
-            model_types=[
-                model_type
-                for model_type in ModelType
-                if model_type is not ModelType.OPEN_AI_WHISPER_API
-            ],
             parent=self,
         )
         transcription_options_group_box.transcription_options_changed.connect(

poetry.lock

@@ -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-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1" },
-    { file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015" },
+    { 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 = [
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 [package.dependencies]
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 ]
 
 [[package]]
@@ -1792,13 +1793,13 @@ files = [
 
 [[package]]
 name = "pytest"
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+version = "7.4.4"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -2089,28 +2090,28 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "ruff"
-version = "0.1.9"
+version = "0.1.11"
 description = "An extremely fast Python linter and code formatter, written in Rust."
 optional = false
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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"

pyproject.toml

@@ -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"

tests/gui_test.py

@@ -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.assert_called()
-            mock_transcription_options_changed.call_args[0][0]
-        )
-        assert transcription_options.model.model_type == ModelType.WHISPER_CPP

tests/mock_sounddevice.py

@@ -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
 

tests/transcriber_benchmarks_test.py

@@ -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

tests/transcriber_test.py

@@ -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)

tests/transformers_whisper_test.py

@@ -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")

tests/widgets/file_transcriber_widget_test.py

@@ -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)
 

tests/widgets/main_window_test.py

@@ -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

tests/widgets/model_type_combo_box_test.py

@@ -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.count() == len(model_types)
-        assert widget.itemText(0) == "Whisper"
+        for index, model_type in enumerate(model_types):
-        assert widget.itemText(1) == "Whisper.cpp"
+            assert widget.itemText(index) == model_type
-        assert widget.itemText(2) == "Hugging Face"
-        assert widget.itemText(3) == "Faster Whisper"
-        assert widget.itemText(4) == "OpenAI Whisper API"

tests/widgets/preferences_dialog/folder_watch_preferences_widget_test.py

@@ -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="",

tests/widgets/preferences_dialog/models_preferences_widget_test.py

@@ -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)
+        for model_type in ModelType:
-        if os.path.isfile(file_path):
+            if model_type.is_available():
-            os.remove(file_path)
+                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(
+        assert widget.model.get_local_model_path() is None
-            model_type=ModelType.WHISPER, whisper_model_size=WhisperModelSize.TINY
-        )
-
-        assert 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(widget.model.get_local_model_path())
-            assert os.path.isfile(get_whisper_file_path(size=model.whisper_model_size))
 
         qtbot.wait_until(callback=downloaded_model, timeout=60_000)
 
     @pytest.fixture(scope="class")
-    def whisper_tiny_model_path(self) -> str:
+    def default_model_path(self) -> str:
-        return get_model_path(
+        return get_model_path(transcription_model=(TranscriptionModel.default()))
-            transcription_model=TranscriptionModel(
-                model_type=ModelType.WHISPER, whisper_model_size=WhisperModelSize.TINY
-            )
-        )
 
-    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)

tests/widgets/transcription_task_folder_watcher_test.py

@@ -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="",