trinity_v8_core.spec

# -*- mode: python ; coding: utf-8 -*-
# VOXIS V4.0.0 DENSE — Trinity V8 PyInstaller Spec
# Copyright © 2026 Glass Stone LLC. All Rights Reserved.
# CEO: Gabriel B. Rodriguez

import os
from PyInstaller.utils.hooks import collect_data_files, collect_dynamic_libs

# IMPORTANT: Build environment must use:
#   setuptools == 69.5.1   (pkg_resources.NullProvider compatibility with PyInstaller)
#   numpy      <  2.0      (numpy.core._multiarray_umath compatibility)
# Run before building:
#   pip install "setuptools==69.5.1" "numpy<2.0"

block_cipher = None

hiddenimports = [
    # PyTorch / torchaudio
    'torch', 'torchaudio', 'torchaudio.transforms', 'torchaudio.functional',
    'torchaudio.backend', 'torchaudio.io',
    'torch.nn', 'torch.nn.functional', 'torch.backends.mps',
    'torch.utils.data',
    # Audio processing
    'librosa', 'librosa.core', 'librosa.feature', 'librosa.effects',
    'librosa.util', 'librosa.filters',
    'soundfile',
    'numpy', 'numpy.core', 'numpy.random',
    'scipy', 'scipy.signal', 'scipy.fftpack', 'scipy.io', 'scipy.io.wavfile',
    # audio-separator (all architecture backends required at runtime)
    'audio_separator', 'audio_separator.separator',
    'audio_separator.separator.architectures',
    'audio_separator.separator.architectures.mdx_separator',
    'audio_separator.separator.architectures.vr_separator',
    'onnxruntime', 'onnxruntime.capi',
    # AudioSR (latent diffusion upsampler — all submodules required)
    'audiosr', 'audiosr.pipeline', 'audiosr.lowpass',
    'audiosr.clap', 'audiosr.utils',
    'audiosr.latent_diffusion',
    'audiosr.latent_diffusion.models', 'audiosr.latent_diffusion.models.ddim',
    'audiosr.latent_diffusion.models.ddpm', 'audiosr.latent_diffusion.models.plms',
    'audiosr.latent_diffusion.modules',
    'audiosr.latent_diffusion.modules.attention',
    'audiosr.latent_diffusion.modules.diffusionmodules',
    'audiosr.latent_diffusion.modules.diffusionmodules.model',
    'audiosr.latent_diffusion.modules.diffusionmodules.openaimodel',
    'audiosr.latent_diffusion.modules.diffusionmodules.util',
    'audiosr.latent_diffusion.modules.distributions',
    'audiosr.latent_diffusion.modules.distributions.distributions',
    'audiosr.latent_diffusion.modules.encoders',
    'audiosr.latent_diffusion.modules.encoders.modules',
    'audiosr.latent_diffusion.modules.audiomae',
    'audiosr.latent_diffusion.modules.audiomae.AudioMAE',
    'audiosr.latent_diffusion.modules.audiomae.models_vit',
    'audiosr.latent_diffusion.modules.audiomae.models_mae',
    'audiosr.latent_diffusion.modules.phoneme_encoder',
    # Pedalboard
    'pedalboard', 'pedalboard._pedalboard',
    # HuggingFace / transformers
    'transformers', 'transformers.modeling_utils',
    'huggingface_hub', 'huggingface_hub.utils', 'huggingface_hub.file_download',
    'tokenizers',
    'einops', 'omegaconf', 'yaml',
    'packaging', 'packaging.version',
    'filelock', 'requests', 'urllib3', 'certifi',
    # PIL / Pillow (needed by audio-separator + audiosr)
    'PIL', 'PIL.Image',
    # torchdiffeq (needed by VoiceRestore — loaded from datas at runtime)
    'torchdiffeq',
    # amfm_decompy (F0 extraction for Diff-HierVC)
    'amfm_decompy', 'amfm_decompy.pYAAPT', 'amfm_decompy.basic_tools',
    # x_transformers (needed by VoiceRestore voice_restore.py)
    'x_transformers', 'x_transformers.x_transformers', 'x_transformers.attend',
    'rotary_embedding_torch', 'gateloop_transformer',
    # jaxtyping (needed by VoiceRestore tensor_typing.py)
    'jaxtyping',
    # System / Cross-platform
    'psutil', 'platform', 'hashlib', 'contextlib',
    # Voxis pipeline modules (v8.2 resilient backend)
    'model_registry',
    'modules.ingest',
    'modules.device_utils',
    'modules.path_utils',
    'modules.coreml_bridge',
    'modules.onnx_bridge',
    'modules.adaptive_chunker',
    'modules.uvr_processor',
    'modules.spectrum_analyzer',
    'modules.voicerestore_wrapper',
    'modules.upsampler',
    'modules.mastering_phase',
    'modules.phaselimiter_wrapper',
    'modules.error_telemetry',
    'modules.pipeline_cache',
    'modules.retry_engine',
    'modules.diffhiervc_wrapper',
    'modules.temp_manager',
    # Diff-HierVC (vocal refinement)
    'amfm_decompy', 'amfm_decompy.pYAAPT', 'amfm_decompy.basic_tools',
    'alias_free_torch',
    # Apple CoreML
    'coremltools', 'coremltools.models', 'coremltools.models.MLModel',
    'coremltools.converters', 'coremltools.converters.mil',
    'coremltools.converters.mil.frontend.torch',
    'coremltools.converters.mil.frontend.torch.ops',
    'coremltools.proto', 'coremltools.optimize',
    # ONNX + ONNX Runtime (cross-platform acceleration)
    'onnx', 'onnx.checker', 'onnx.numpy_helper', 'onnx.helper',
    'onnxruntime', 'onnxruntime.capi', 'onnxruntime.capi._pybind_state',
    # VoiceRestore / BigVGAN / Diff-HierVC — NOT frozen here.
    # Loaded at runtime via importlib from extracted data files (modules/external/)
    # to avoid name collisions (model.py vs model/ package, utils.py conflicts, etc.)
    'pkg_resources',
]

datas = [
    ('trinity_engine/modules/external', 'modules/external'),
    # PhaseLimiter resource dir (sound_quality2_cache for mastering presets)
    ('trinity_engine/modules/external/phase/resource', 'modules/external/phase/resource'),
]

# ── PhaseLimiter native binary (bundled — ships with installer) ──────────────
_phaselimiter_bin = os.path.join('trinity_engine', 'modules', 'external', 'phase', 'bin', 'Release', 'phase_limiter')
if os.path.isfile(_phaselimiter_bin):
    datas += [(_phaselimiter_bin, os.path.join('modules', 'external', 'phase', 'bin', 'Release'))]
    print(f"[SPEC] PhaseLimiter binary bundled: {_phaselimiter_bin}")
else:
    print(f"[SPEC] WARNING: PhaseLimiter binary not found at {_phaselimiter_bin}")
    print(f"[SPEC] Build it first: cd trinity_engine/modules/external/phase && ./build_macos_native.sh")
try:
    # PyTorch JIT compiler needs raw source to compile scripts at runtime.
    datas += collect_data_files('x_transformers', includes=['**/*.py'])
    datas += collect_data_files('gateloop_transformer', includes=['**/*.py'])
except Exception:
    pass
try:
    datas += collect_data_files('librosa', includes=['**/*'])
except Exception:
    pass
try:
    datas += collect_data_files('audio_separator', includes=['**/*'])
except Exception:
    pass
try:
    datas += collect_data_files('audiosr', includes=['**/*'])
except Exception:
    pass
try:
    datas += collect_data_files('language_tags', includes=['**/*'])
except Exception:
    pass
try:
    datas += collect_data_files('coremltools', includes=['**/*.py', '**/*.proto', '**/*.mlmodel'])
except Exception:
    pass
try:
    datas += collect_data_files('alias_free_torch', includes=['**/*'])
except Exception:
    pass
try:
    datas += collect_data_files('amfm_decompy', includes=['**/*'])
except Exception:
    pass

binaries = []
try:
    binaries += collect_dynamic_libs('numba')
    binaries += collect_dynamic_libs('llvmlite')
except Exception:
    pass

a = Analysis(
    ['trinity_engine/trinity_core.py'],
    pathex=[
        os.path.abspath('trinity_engine'),
        os.path.abspath('trinity_engine/modules'),
        # VoiceRestore/BigVGAN/Diff-HierVC paths intentionally EXCLUDED —
        # their modules are loaded at runtime via importlib from datas.
    ],
    binaries=binaries,
    datas=datas,
    hiddenimports=hiddenimports,
    hookspath=[],
    hooksconfig={},
    runtime_hooks=['trinity_engine/pyinstaller_runtime_hook.py'],
    excludes=[
        'tkinter', 'matplotlib', 'cv2', 'flask',
        'jupyter', 'notebook', 'IPython', 'wx',
    ],
    noarchive=False,
    optimize=0,  # 0 retains assert statements and docstrings (required for TorchScript)
)

pyz = PYZ(a.pure, cipher=block_cipher)

exe = EXE(
    pyz,
    a.scripts,
    a.binaries,
    a.datas,
    [],
    name='trinity_v8_core',
    debug=False,
    bootloader_ignore_signals=False,
    strip=False,
    upx=False,
    upx_exclude=[],
    runtime_tmpdir=None,
    console=True,
    disable_windowed_traceback=False,
    argv_emulation=False,
    target_arch=None,
    codesign_identity=None,
    entitlements_file=None,
)