"""
PyInstaller build script for creating standalone Python server binary.

Usage:
    python build_binary.py           # Build default (CPU) server binary
    python build_binary.py --cuda    # Build CUDA-enabled server binary
"""

import PyInstaller.__main__
import argparse
import os
import platform
from pathlib import Path


def is_apple_silicon():
    """Check if running on Apple Silicon."""
    return platform.system() == "Darwin" and platform.machine() == "arm64"


def build_server(cuda=False):
    """Build Python server as standalone binary.

    Args:
        cuda: If True, build with CUDA support and name the binary
              voicebox-server-cuda instead of voicebox-server.
    """
    backend_dir = Path(__file__).parent

    binary_name = 'voicebox-server-cuda' if cuda else 'voicebox-server'

    # PyInstaller arguments
    args = [
        'server.py',  # Use server.py as entry point instead of main.py
        '--onefile',
        '--name', binary_name,
    ]

    # Add local qwen_tts path if specified (for editable installs)
    qwen_tts_path = os.getenv('QWEN_TTS_PATH')
    if qwen_tts_path and Path(qwen_tts_path).exists():
        args.extend(['--paths', str(qwen_tts_path)])
        print(f"Using local qwen_tts source from: {qwen_tts_path}")

    # Add common hidden imports
    args.extend([
        '--hidden-import', 'backend',
        '--hidden-import', 'backend.main',
        '--hidden-import', 'backend.config',
        '--hidden-import', 'backend.database',
        '--hidden-import', 'backend.models',
        '--hidden-import', 'backend.profiles',
        '--hidden-import', 'backend.history',
        '--hidden-import', 'backend.tts',
        '--hidden-import', 'backend.transcribe',
        '--hidden-import', 'backend.platform_detect',
        '--hidden-import', 'backend.backends',
        '--hidden-import', 'backend.backends.pytorch_backend',
        '--hidden-import', 'backend.utils.audio',
        '--hidden-import', 'backend.utils.cache',
        '--hidden-import', 'backend.utils.progress',
        '--hidden-import', 'backend.utils.hf_progress',
        '--hidden-import', 'backend.utils.validation',
        '--hidden-import', 'backend.cuda_download',
        '--hidden-import', 'torch',
        '--hidden-import', 'transformers',
        '--hidden-import', 'fastapi',
        '--hidden-import', 'uvicorn',
        '--hidden-import', 'sqlalchemy',
        '--hidden-import', 'librosa',
        '--hidden-import', 'soundfile',
        '--hidden-import', 'qwen_tts',
        '--hidden-import', 'qwen_tts.inference',
        '--hidden-import', 'qwen_tts.inference.qwen3_tts_model',
        '--hidden-import', 'qwen_tts.inference.qwen3_tts_tokenizer',
        '--hidden-import', 'qwen_tts.core',
        '--hidden-import', 'qwen_tts.cli',
        '--copy-metadata', 'qwen-tts',
        '--collect-submodules', 'qwen_tts',
        '--collect-data', 'qwen_tts',
        # Fix for pkg_resources and jaraco namespace packages
        '--hidden-import', 'pkg_resources.extern',
        '--collect-submodules', 'jaraco',
    ])

    # Add CUDA-specific hidden imports
    if cuda:
        print("Building with CUDA support")
        args.extend([
            '--hidden-import', 'torch.cuda',
            '--hidden-import', 'torch.backends.cudnn',
        ])
    else:
        # Exclude NVIDIA CUDA packages from CPU-only builds to keep binary under 4GB.
        # On Linux, pip may pull CUDA-enabled PyTorch by default which includes ~3GB
        # of NVIDIA shared libraries that PyInstaller would bundle.
        nvidia_packages = [
            'nvidia', 'nvidia.cublas', 'nvidia.cuda_cupti', 'nvidia.cuda_nvrtc',
            'nvidia.cuda_runtime', 'nvidia.cudnn', 'nvidia.cufft', 'nvidia.curand',
            'nvidia.cusolver', 'nvidia.cusparse', 'nvidia.nccl', 'nvidia.nvjitlink',
            'nvidia.nvtx',
        ]
        for pkg in nvidia_packages:
            args.extend(['--exclude-module', pkg])

    # Add MLX-specific imports if building on Apple Silicon (never for CUDA builds)
    if is_apple_silicon() and not cuda:
        print("Building for Apple Silicon - including MLX dependencies")
        args.extend([
            '--hidden-import', 'backend.backends.mlx_backend',
            '--hidden-import', 'mlx',
            '--hidden-import', 'mlx.core',
            '--hidden-import', 'mlx.nn',
            '--hidden-import', 'mlx_audio',
            '--hidden-import', 'mlx_audio.tts',
            '--hidden-import', 'mlx_audio.stt',
            '--collect-submodules', 'mlx',
            '--collect-submodules', 'mlx_audio',
            # Use --collect-all so PyInstaller bundles both data files AND
            # native shared libraries (.dylib, .metallib) for MLX.
            # Previously only --collect-data was used, which caused MLX to
            # raise OSError at runtime inside the bundled binary because
            # the Metal shader libraries were missing.
            '--collect-all', 'mlx',
            '--collect-all', 'mlx_audio',
        ])
    elif not cuda:
        print("Building for non-Apple Silicon platform - PyTorch only")

    args.extend([
        '--noconfirm',
        '--clean',
    ])

    # Change to backend directory
    os.chdir(backend_dir)
    
    # Run PyInstaller
    PyInstaller.__main__.run(args)
    
    print(f"Binary built in {backend_dir / 'dist' / binary_name}")


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description="Build voicebox-server binary")
    parser.add_argument(
        '--cuda',
        action='store_true',
        help="Build CUDA-enabled binary (voicebox-server-cuda)",
    )
    cli_args = parser.parse_args()
    build_server(cuda=cli_args.cuda)