mirror of
https://github.com/jamiepine/voicebox.git
synced 2026-09-15 04:40:40 -07:00
James Pine
0dabb121c9
Replace verbose startup messages with a clean summary: - App version, Python version, OS/arch - Database path (fix None display), data directory - Profile and generation counts - Backend, GPU, model cache path - Clean up stale loading_model status on startup - Remove noisy progress manager log line
389 lines
12 KiB
Python
389 lines
12 KiB
Python
"""
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PyInstaller build script for creating standalone Python server binary.
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Usage:
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python build_binary.py # Build default (CPU) server binary
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python build_binary.py --cuda # Build CUDA-enabled server binary
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"""
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import PyInstaller.__main__
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import argparse
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import logging
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import os
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import platform
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import sys
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from pathlib import Path
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logger = logging.getLogger(__name__)
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def is_apple_silicon():
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"""Check if running on Apple Silicon."""
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return platform.system() == "Darwin" and platform.machine() == "arm64"
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def build_server(cuda=False):
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"""Build Python server as standalone binary.
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Args:
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cuda: If True, build with CUDA support and name the binary
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voicebox-server-cuda instead of voicebox-server.
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"""
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backend_dir = Path(__file__).parent
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binary_name = "voicebox-server-cuda" if cuda else "voicebox-server"
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# PyInstaller arguments
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args = [
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"server.py", # Use server.py as entry point instead of main.py
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"--onefile",
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"--name",
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binary_name,
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]
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# Hide console window on Windows only. On macOS/Linux the sidecar needs
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# stdout/stderr for Tauri to capture logs.
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if platform.system() == "Windows":
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args.append("--noconsole")
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# Add local qwen_tts path if specified (for editable installs)
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qwen_tts_path = os.getenv("QWEN_TTS_PATH")
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if qwen_tts_path and Path(qwen_tts_path).exists():
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args.extend(["--paths", str(qwen_tts_path)])
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logger.info("Using local qwen_tts source from: %s", qwen_tts_path)
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# Add common hidden imports
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args.extend(
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[
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"--hidden-import",
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"backend",
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"--hidden-import",
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"backend.main",
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"--hidden-import",
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"backend.config",
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"--hidden-import",
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"backend.database",
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"--hidden-import",
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"backend.models",
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"--hidden-import",
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"backend.services.profiles",
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"--hidden-import",
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"backend.services.history",
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"--hidden-import",
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"backend.services.tts",
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"--hidden-import",
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"backend.services.transcribe",
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"--hidden-import",
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"backend.utils.platform_detect",
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"--hidden-import",
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"backend.backends",
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"--hidden-import",
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"backend.backends.pytorch_backend",
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"--hidden-import",
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"backend.utils.audio",
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"--hidden-import",
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"backend.utils.cache",
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"--hidden-import",
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"backend.utils.progress",
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"--hidden-import",
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"backend.utils.hf_progress",
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"--hidden-import",
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"backend.services.cuda",
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"--hidden-import",
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"backend.services.effects",
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"--hidden-import",
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"backend.utils.effects",
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"--hidden-import",
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"backend.services.versions",
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"--hidden-import",
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"pedalboard",
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"--hidden-import",
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"chatterbox",
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"--hidden-import",
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"chatterbox.tts_turbo",
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"--hidden-import",
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"chatterbox.mtl_tts",
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"--hidden-import",
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"backend.backends.chatterbox_backend",
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"--hidden-import",
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"backend.backends.chatterbox_turbo_backend",
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"--hidden-import",
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"backend.backends.luxtts_backend",
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"--hidden-import",
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"zipvoice",
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"--hidden-import",
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"zipvoice.luxvoice",
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"--collect-all",
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"zipvoice",
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"--collect-all",
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"linacodec",
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"--hidden-import",
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"torch",
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"--hidden-import",
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"transformers",
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"--hidden-import",
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"fastapi",
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"--hidden-import",
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"uvicorn",
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"--hidden-import",
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"sqlalchemy",
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"--hidden-import",
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"librosa",
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"--hidden-import",
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"soundfile",
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"--hidden-import",
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"qwen_tts",
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"--hidden-import",
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"qwen_tts.inference",
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"--hidden-import",
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"qwen_tts.inference.qwen3_tts_model",
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"--hidden-import",
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"qwen_tts.inference.qwen3_tts_tokenizer",
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"--hidden-import",
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"qwen_tts.core",
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"--hidden-import",
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"qwen_tts.cli",
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"--copy-metadata",
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"qwen-tts",
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"--copy-metadata",
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"requests",
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"--copy-metadata",
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"transformers",
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"--copy-metadata",
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"huggingface-hub",
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"--copy-metadata",
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"tokenizers",
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"--copy-metadata",
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"safetensors",
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"--copy-metadata",
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"tqdm",
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"--hidden-import",
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"requests",
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"--collect-submodules",
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"qwen_tts",
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"--collect-data",
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"qwen_tts",
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# Fix for pkg_resources and jaraco namespace packages
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"--hidden-import",
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"pkg_resources.extern",
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"--collect-submodules",
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"jaraco",
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# inflect uses typeguard @typechecked which calls inspect.getsource()
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# at import time — needs .py source files, not just .pyc bytecode
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"--collect-all",
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"inflect",
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# perth ships pretrained watermark model files (hparams.yaml, .pth.tar)
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# in perth/perth_net/pretrained/ — needed by chatterbox at runtime
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"--collect-all",
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"perth",
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# piper_phonemize ships espeak-ng-data/ (phoneme tables, language dicts)
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# needed by LuxTTS for text-to-phoneme conversion
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"--collect-all",
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"piper_phonemize",
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]
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)
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# Add CUDA-specific hidden imports
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if cuda:
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logger.info("Building with CUDA support")
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args.extend(
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[
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"--hidden-import",
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"torch.cuda",
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"--hidden-import",
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"torch.backends.cudnn",
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]
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)
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else:
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# Exclude NVIDIA CUDA packages from CPU-only builds to keep binary small.
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# When building from a venv with CUDA torch installed, PyInstaller would
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# bundle ~3GB of NVIDIA shared libraries. We exclude both the Python
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# modules and the binary DLLs.
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nvidia_packages = [
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"nvidia",
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"nvidia.cublas",
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"nvidia.cuda_cupti",
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"nvidia.cuda_nvrtc",
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"nvidia.cuda_runtime",
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"nvidia.cudnn",
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"nvidia.cufft",
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"nvidia.curand",
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"nvidia.cusolver",
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"nvidia.cusparse",
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"nvidia.nccl",
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"nvidia.nvjitlink",
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"nvidia.nvtx",
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]
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for pkg in nvidia_packages:
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args.extend(["--exclude-module", pkg])
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# Add MLX-specific imports if building on Apple Silicon (never for CUDA builds)
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if is_apple_silicon() and not cuda:
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logger.info("Building for Apple Silicon - including MLX dependencies")
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args.extend(
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[
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"--hidden-import",
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"backend.backends.mlx_backend",
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"--hidden-import",
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"mlx",
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"--hidden-import",
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"mlx.core",
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"--hidden-import",
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"mlx.nn",
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"--hidden-import",
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"mlx_audio",
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"--hidden-import",
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"mlx_audio.tts",
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"--hidden-import",
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"mlx_audio.stt",
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"--collect-submodules",
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"mlx",
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"--collect-submodules",
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"mlx_audio",
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# Use --collect-all so PyInstaller bundles both data files AND
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# native shared libraries (.dylib, .metallib) for MLX.
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# Previously only --collect-data was used, which caused MLX to
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# raise OSError at runtime inside the bundled binary because
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# the Metal shader libraries were missing.
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"--collect-all",
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"mlx",
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"--collect-all",
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"mlx_audio",
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]
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)
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elif not cuda:
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logger.info("Building for non-Apple Silicon platform - PyTorch only")
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dist_dir = str(backend_dir / "dist")
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build_dir = str(backend_dir / "build")
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args.extend(
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[
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"--distpath",
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dist_dir,
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"--workpath",
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build_dir,
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"--noconfirm",
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"--clean",
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]
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)
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# Change to backend directory
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os.chdir(backend_dir)
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# For CPU builds on Windows, ensure we're using CPU-only torch.
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# If CUDA torch is installed (local dev), swap to CPU torch before building,
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# then restore CUDA torch after. This prevents PyInstaller from bundling
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# ~3GB of CUDA DLLs into the CPU binary.
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restore_cuda = False
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if not cuda and platform.system() == "Windows":
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import subprocess
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result = subprocess.run(
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[sys.executable, "-c", "import torch; print(torch.version.cuda or '')"], capture_output=True, text=True
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)
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has_cuda_torch = bool(result.stdout.strip())
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if has_cuda_torch:
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logger.info("CUDA torch detected — installing CPU torch for CPU build...")
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subprocess.run(
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[
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sys.executable,
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"-m",
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"pip",
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"install",
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"torch",
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"torchvision",
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"torchaudio",
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"--index-url",
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"https://download.pytorch.org/whl/cpu",
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"--force-reinstall",
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"-q",
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],
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check=True,
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)
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restore_cuda = True
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# Run PyInstaller
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try:
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PyInstaller.__main__.run(args)
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finally:
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# Restore CUDA torch if we swapped it out (even on build failure)
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if restore_cuda:
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logger.info("Restoring CUDA torch...")
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import subprocess
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subprocess.run(
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[
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sys.executable,
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"-m",
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"pip",
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"install",
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"torch",
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"torchvision",
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"torchaudio",
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"--index-url",
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"https://download.pytorch.org/whl/cu126",
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"--force-reinstall",
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"-q",
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],
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check=True,
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)
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logger.info("Binary built in %s", backend_dir / "dist" / binary_name)
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def _get_cuda_dll_excludes():
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"""Get list of CUDA DLL filenames to exclude from CPU builds.
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When building locally with CUDA torch installed, PyInstaller bundles ~3GB of
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CUDA DLLs from torch/lib/. Returns a list of DLL filenames to exclude.
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"""
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try:
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import torch
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torch_lib = Path(torch.__file__).parent / "lib"
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except ImportError:
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return []
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cuda_prefixes = (
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"torch_cuda",
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"cublas",
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"cublasLt",
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"cudnn",
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"cusparse",
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"cufft",
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"cusolver",
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"cusolverMg",
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"curand",
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"nvrtc",
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"nvJitLink",
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"nccl",
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"nvperf",
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"nvrtc-builtins",
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)
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exclude_dlls = []
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if torch_lib.exists():
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for f in torch_lib.iterdir():
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if f.suffix == ".dll" and any(f.name.startswith(p) for p in cuda_prefixes):
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exclude_dlls.append(f.name)
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if exclude_dlls:
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total_mb = (
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sum((torch_lib / dll).stat().st_size for dll in exclude_dlls if (torch_lib / dll).exists()) / 1024 / 1024
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)
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logger.info("CPU build: will exclude %d CUDA DLLs (%.0f MB)", len(exclude_dlls), total_mb)
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return exclude_dlls
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Build voicebox-server binary")
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parser.add_argument(
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"--cuda",
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action="store_true",
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help="Build CUDA-enabled binary (voicebox-server-cuda)",
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)
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cli_args = parser.parse_args()
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build_server(cuda=cli_args.cuda)
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