Palash Debnath
93025d9a81
The dictation hotkey could leave a blank dark square stuck on the desktop with no way to dismiss it. Three defects compounded: the tray listener's effect depended on [state], so it detached across an await on every state change and a press landing in that gap was lost; an idle pill renders null, so the window Rust had already shown was empty; and the opaque chrome background made that empty window a hard-edged square. Nothing could hide it — dismiss() is only reachable from the X button, Esc, or a post-session timer, none of which exist for a session that never started. Fixed at the invariant rather than the call sites: the listener subscribes once for the component's lifetime, the widget window's chrome background is transparent, and an idle-but-visible window reconciles itself to hidden. The reconcile is polled (a dropped press changes no React state, so there is nothing to key an effect off) and aborts if its effect is torn down mid-check, so it can never hide a dictation that has just started. Also in scope: - The rename sweep had repointed three data-dir literals at a brand-named directory that does not exist, so smoke-test.sh verified a directory the backend never writes and desktop-prod.sh silently stopped clearing backend state on Windows. Both invisible on macOS, where they are usually run. A guard test now pins the assignments specifically. - The dictation model picker's download sizes were wrong for all seven models, in both directions — Parakeet TDT v3 (the recommended default) understated 180 MB against an actual 670 MB, while the low-RAM fallbacks were overstated threefold, discouraging exactly the choice that would have helped. Measured from the published repos and pinned by a test. - The 0.6B Parakeet models now decode on more threads, capped by host cores and still overridable. - uninstall.ps1 gained a UTF-8 BOM (Windows PowerShell 5.1 mis-decodes its non-ASCII output without one), and sponsor.yml lost its last OmniVoice references.
254 lines
11 KiB
RPMSpec
254 lines
11 KiB
RPMSpec
# -*- mode: python ; coding: utf-8 -*-
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# PyInstaller spec for VoiceStudio backend.
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#
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# Produces a one-folder bundle at dist/omnivoice-backend/ that Tauri launches
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# as a sidecar binary. Kept intentionally permissive with collect_all(...)
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# on the heavy ML deps because PyInstaller's static analysis misses their
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# runtime-imported submodules, C extensions, and data files.
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#
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# Cross-platform: targets mac-ARM, mac-Intel, Linux x64, Windows x64. mlx
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# deps are gated on mac-ARM (sys.platform=='darwin' + machine=='arm64') so
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# PyInstaller on other hosts doesn't blow up trying to find mlx wheels.
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#
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# Run: uv run pyinstaller backend.spec --noconfirm --clean
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import platform
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import sys
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from PyInstaller.utils.hooks import collect_data_files, collect_all, collect_submodules, copy_metadata
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IS_MAC_ARM = sys.platform == "darwin" and platform.machine() == "arm64"
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datas = []
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binaries = []
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# Bundle the omnivoice package's .dist-info so importlib.metadata.version()
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# resolves inside the frozen build. Without it the backend can't read its own
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# version and falls back to the literal in backend/core/version.py — which is
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# how a 0.3.6 desktop build shipped reporting "0.3.5" in About + bug reports.
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datas += copy_metadata('omnivoice')
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hiddenimports = [
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# Web stack
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'uvicorn', 'uvicorn.logging', 'uvicorn.loops', 'uvicorn.loops.auto',
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'uvicorn.protocols', 'uvicorn.protocols.http', 'uvicorn.protocols.http.auto',
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'uvicorn.protocols.websockets', 'uvicorn.protocols.websockets.auto',
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'uvicorn.lifespan', 'uvicorn.lifespan.on',
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'fastapi', 'fastapi.responses', 'starlette',
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'multipart',
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# SOCKS proxy support (#959). httpx imports socksio lazily inside a
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# try/except (only when a socks5:// proxy env var is set), so
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# PyInstaller's static tracer never sees it — without this entry the
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# frozen installers keep raising "Using SOCKS proxy, but the 'socksio'
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# package is not installed" on every model load under a SOCKS proxy,
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# even though pyproject.toml ships the package. Guarded by
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# tests/test_socks_proxy.py.
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'socksio',
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# Core
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'uuid', 'asyncio',
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# Audio / ML
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'torch', 'torchaudio', 'soundfile', 'scipy', 'numpy',
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'numpy.random._pickle',
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# Cross-platform primary ASR — WhisperX (faster-whisper + wav2vec2
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# alignment) is the default on every platform. faster-whisper is the
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# transcription engine; WhisperX adds forced alignment for ±10-30 ms
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# word timing, which directly improves dub lip-sync. Both backends are
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# registered in asr_backend.py; the user can switch via Settings.
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'whisperx', 'whisperx.alignment', 'whisperx.asr', 'whisperx.diarize',
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'whisperx.vad', 'whisperx.audio', 'whisperx.utils',
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'faster_whisper', 'faster_whisper.transcribe', 'faster_whisper.audio',
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'faster_whisper.utils', 'faster_whisper.tokenizer', 'faster_whisper.vad',
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'ctranslate2',
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# Lightweight English TTS tier — ONNX-based, cross-platform. The ONNX
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# Runtime wheels ship platform-specific .so/.dll/.dylib which collect_all
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# picks up; the kittentts Python package is pure Python but has a couple
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# of asset files the bundler needs to include.
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'kittentts', 'onnxruntime',
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# Pipeline
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'yt_dlp', 'demucs', 'demucs.separate',
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# Numbers→words for the pre-TTS text normalization pass
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# (services/text_normalization.py). Imported inside a function (lazy),
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# so pin it explicitly rather than trusting the tracer.
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'num2words',
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# OmniVoice's own package
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'omnivoice', 'omnivoice.models', 'omnivoice.models.omnivoice',
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]
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if IS_MAC_ARM:
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# MLX Whisper on Apple Silicon (optional speedup path). mlx's pure-Python
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# submodules (nn, utils, …) are imported lazily by mlx_whisper at
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# transcribe time and the plain dep tracer misses them. We deliberately
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# do NOT collect_all() mlx because that double-registers mlx.core with
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# nanobind and the binary aborts on the first mlx.core touch.
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hiddenimports.append('mlx_whisper')
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# Parakeet TDT v3 ASR (services.asr_backend.ParakeetMLXBackend) — imported
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# lazily at is_available()/transcribe time, so the tracer misses it. Same
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# rule as mlx_whisper: list the package, never collect_all() anything that
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# touches nanobind-registered mlx.core.
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hiddenimports.append('parakeet_mlx')
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# mlx-audio engine multiplexer — Kokoro / CSM / Dia / Qwen3-TTS /
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# Chatterbox / MeloTTS / OuteTTS / … — gives mac-ARM users a rich
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# engine picker. Like mlx_whisper it's mac-ARM-only; also like
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# mlx_whisper we list it here but avoid collect_all() because it
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# depends on the same nanobind-registered mlx.core.
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hiddenimports += [
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'mlx_audio', 'mlx_audio.tts', 'mlx_audio.tts.utils',
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'mlx_audio.tts.models', 'mlx_audio.tts.generate',
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'mlx_audio.stt', 'mlx_audio.codec',
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]
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# Kokoro's phonemizer (misaki) loads the spaCy model en_core_web_sm
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# DYNAMICALLY (spacy.load by name), so PyInstaller never sees the import —
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# a frozen build without it would hit misaki's in-process downloader at
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# first English generation (#1133 class; contained since #1143, but the
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# generation still degrades). It's a plain data-heavy package with no
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# nanobind involvement, so collect_all is safe here (unlike mlx itself).
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_sm_datas, _sm_bins, _sm_hidden = collect_all('en_core_web_sm')
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datas += _sm_datas
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binaries += _sm_bins
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hiddenimports += _sm_hidden
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# Note: we deliberately DON'T enumerate mlx submodules here. Any variant of
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# `collect_submodules('mlx')` or `collect_all('mlx')` — even filtered to
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# exclude mlx.core — reliably re-triggers the nanobind duplicate-key error
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# the first time anything imports mlx.core ("refusing to add duplicate key
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# 'cpu' to enumeration mlx.core.DeviceType"). Shipping without mlx in the
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# frozen bundle leaves mlx-whisper unavailable; asr_backend falls back to
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# pytorch-whisper (slower but functional on Apple Silicon). Revisit once
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# we have a minimal repro or a PyInstaller hook specifically for mlx.
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# The nuclear option on heavy ML libs — pull every submodule, C ext, and
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# data file. Cost: bigger bundle. Benefit: we don't ship a binary that
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# ImportErrors the first time a user hits a code path.
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# Note: 'mlx' is intentionally NOT in this list. Calling collect_all('mlx')
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# alongside collect_all('mlx_whisper') causes the nanobind binding init to
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# run twice in the frozen bundle, crashing with
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# "Critical nanobind error: refusing to add duplicate key 'cpu'
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# to enumeration 'mlx.core.DeviceType'!"
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# the first time anything imports mlx.core. mlx_whisper already depends on
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# mlx and PyInstaller's dep tracer pulls the needed mlx submodules + the .so.
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_collect_pkgs = [
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'torch', 'torchaudio', 'soundfile', 'scipy', 'numpy',
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'omnivoice', 'demucs', 'yt_dlp', 'fastapi', 'uvicorn',
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# Primary cross-platform ASR. collect_all pulls CTranslate2's bundled
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# .so/.dylib/.dll plus its compiled kernel data. WhisperX ships its own
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# pure-Python code + some asset files (e.g. language metadata).
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'whisperx', 'faster_whisper', 'ctranslate2',
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# ONNX-based lightweight TTS. onnxruntime's collect_all pulls the
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# platform-appropriate .so/.dll/.dylib + CUDA providers when present.
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'kittentts', 'onnxruntime',
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]
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if IS_MAC_ARM:
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# Only attempt mlx_whisper collection on mac-ARM — no wheels exist for
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# Linux/Windows/mac-Intel, so collect_all would fail on CI for those.
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_collect_pkgs.append('mlx_whisper')
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for pkg in _collect_pkgs:
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try:
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tmp_datas, tmp_binaries, tmp_hidden = collect_all(pkg)
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datas += tmp_datas
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binaries += tmp_binaries
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hiddenimports += tmp_hidden
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except Exception as e: # noqa: BLE001
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print(f"[backend.spec] collect_all({pkg!r}) skipped: {e}")
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# Include the backend's own modules as data so imports like
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# `api.routers.dub_generate` resolve inside the frozen bundle.
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datas += [
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('backend/api', 'api'),
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('backend/core', 'core'),
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('backend/services', 'services'),
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('backend/schemas', 'schemas'),
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('backend/migrations', 'migrations'),
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]
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a = Analysis(
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['backend/main.py'],
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pathex=['backend', '.'],
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binaries=binaries,
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datas=datas,
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hiddenimports=hiddenimports,
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hookspath=[],
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hooksconfig={},
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runtime_hooks=[
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'backend/hooks/pyi_rth_numpy_compat.py',
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'backend/hooks/pyi_rth_torch_compiler_disable.py',
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],
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excludes=[
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# Desktop-only bloat the frozen backend never uses.
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'tkinter', 'matplotlib', 'PIL.ImageQt', 'PyQt5', 'PyQt6',
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# CUDA / NVIDIA wheels on every platform — we ship CPU-only inference
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# for the desktop app. Models download on first run via HF cache, and
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# GPU use is surfaced only when a user-installed driver is detected
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# at runtime. Excluding these saves ~2 GB per bundle, which is what
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# keeps Linux .deb / Windows MSI under GH Releases' 2 GB asset cap.
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'nvidia', 'nvidia.cublas', 'nvidia.cudnn', 'nvidia.cuda_runtime',
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'nvidia.cuda_nvrtc', 'nvidia.nccl', 'nvidia.nvtx',
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'nvidia.curand', 'nvidia.cusolver', 'nvidia.cusparse',
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'nvidia.cufft', 'nvidia.cuda_cupti', 'nvidia.cusparselt',
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'nvidia.nvjitlink', 'nvidia.cufile',
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'triton', 'flash_attn',
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# Torch internals we never invoke at inference time — distributed
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# training, compile, FX tracing, tensorboard, testing helpers. These
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# pull hundreds of MB of Python source + transitive deps.
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'torch.distributed', 'torch._dynamo', 'torch._inductor',
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'torch._export', 'torch.testing', 'torch.utils.tensorboard',
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'torch.utils.benchmark', 'torch.fx.experimental',
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'torch._functorch', 'torch.ao', 'torch.onnx',
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# torchaudio prototype / deprecated — nothing in the backend touches
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# these; removing saves tens of MB and silences the deprecation log
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# noise on startup.
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'torchaudio.prototype', 'torchaudio.models.hifigan',
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# Heavy optional deps that are in pyproject.toml but the Studio
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# backend never imports (verified with `grep ^import`). Excluding
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# keeps them out of the frozen bundle; nothing on the runtime path
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# breaks.
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'gradio', 'gradio_client', 'tensorboardX', 'webdataset',
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's3prl', 'funasr', 'pedalboard',
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# Test / example trees that get swept up by collect_all.
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'scipy.special.tests', 'scipy.tests', 'numpy.f2py.tests',
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'numpy.tests', 'numpy.testing.tests',
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],
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noarchive=False,
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# optimize=2 compiles the embedded stdlib + site-packages with -OO,
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# stripping assert statements + docstrings. Saves ~50-80 MB on a bundle
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# this size. Runtime impact is negligible because we never inspect
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# docstrings at runtime.
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optimize=2,
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)
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pyz = PYZ(a.pure)
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exe = EXE(
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pyz,
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a.scripts,
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[],
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exclude_binaries=True,
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name='omnivoice-backend',
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debug=False,
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bootloader_ignore_signals=False,
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# strip=True removes debug symbols from ELF/Mach-O binaries (no-op on
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# Windows since MSVC doesn't emit symbols in the same way). Saves
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# 10-30% on native libraries like libtorch_cpu.so (~300 MB → ~220 MB).
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strip=True,
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upx=False, # UPX often corrupts ML native libs — disabled.
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console=True,
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disable_windowed_traceback=False,
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argv_emulation=False,
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target_arch=None,
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codesign_identity=None,
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entitlements_file=None,
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)
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coll = COLLECT(
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exe,
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a.binaries,
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a.datas,
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strip=True,
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upx=False,
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upx_exclude=[],
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name='omnivoice-backend',
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)
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