[build-system]
requires = ["setuptools>=61.0", "wheel"]
build-backend = "setuptools.build_meta"

[tool.uv]
index-strategy = "unsafe-best-match"
required-environments = [
    "sys_platform == 'win32' and platform_machine == 'AMD64'",
    "sys_platform == 'linux' and platform_machine == 'x86_64'",
    "sys_platform == 'darwin' and platform_machine == 'arm64'",
]
override-dependencies = [
    "nvidia-nccl-cu12; sys_platform == 'linux'",
]
# uv mặc định cài nhóm `dev`; đặt rỗng để `uv sync` chỉ cài core torch-free.
# Muốn dev/test: `uv sync --group dev`. Muốn dev GPU đầy đủ: `uv sync --group gpu`
default-groups = []

[[tool.uv.index]]
name = "pytorch"
url = "https://download.pytorch.org/whl/cu128"
explicit = true


[[tool.uv.index]]
name = "pypi"
url = "https://pypi.org/simple"

[[tool.uv.index]]
name = "llama-cpp-metal"
url = "https://abetlen.github.io/llama-cpp-python/whl/metal/"
explicit = true

[project]
name = "vieneu"
version = "3.8.3"
description = "Advanced on-device Vietnamese TTS with instant voice cloning"
readme = "README_PYPI.md"
license = { file = "LICENSE" }
classifiers = [
    "Development Status :: 4 - Beta",
    "Intended Audience :: Developers",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Topic :: Multimedia :: Sound/Audio :: Speech",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
    "Operating System :: OS Independent",
]
keywords = [
    "text-to-speech",
    "tts",
    "vietnamese",
    "voice-cloning",
    "speech-synthesis",
    "real-time",
    "on-device"
]
authors = [
    { name = "Phạm Nguyễn Ngọc Bảo", email = "pnnbao@gmail.com" }
]
requires-python = ">=3.10"
# Minimal, TORCH-FREE core. `pip install vieneu` runs VieNeu-TTS v3 Turbo on CPU
# via ONNX Runtime. GPU (v3 Turbo PyTorch backend): `pip install vieneu[cuda]`;
# legacy backends (llama-cpp, lmdeploy, librosa, neucodec) live in the [legacy] extra.
dependencies = [
    "sea-g2p>=0.9.1", # phonemizer (Rust, torch-free) — cần hàm punc_norm() (>=0.7.11)
    "onnxruntime>=1.20.0", # runs the v3 transformers + MOSS codec
    "numpy",
    "soundfile", # audio I/O
    "soxr", # lightweight resampling for voice cloning
    "kaldi-native-fbank>=1.20", # speaker-encoder fbank front-end (torch-free voice cloning)
    "tokenizers>=0.20", # phoneme tokenizer (torch-free)
    "huggingface_hub", # fetch ONNX / config / tokenizer / voices
    "PyYAML", # gradio config.yaml
    "gradio>=5.49.1", # web UI (vieneu-web)
    "librosa>=0.11.0",
    # NOTE: audio watermarking is opt-in via `pip install vieneu[watermark]` (resemble-perth,
    # needs torch/torchaudio). The PyPI package literally named `perth` is an unrelated
    # threading helper and must NOT be listed here (issue #191).
]

[project.urls]
"Homepage" = "https://github.com/pnnbao97/VieNeu-TTS"
"Repository" = "https://github.com/pnnbao97/VieNeu-TTS"
"Bug Tracker" = "https://github.com/pnnbao97/VieNeu-TTS/issues"
"Documentation" = "https://github.com/pnnbao97/VieNeu-TTS/blob/main/README.md"
"Source Code" = "https://github.com/pnnbao97/VieNeu-TTS"
"Changelog" = "https://github.com/pnnbao97/VieNeu-TTS/releases"

[project.optional-dependencies]
legacy = [
    "torch",
    "torchaudio",
    "transformers",
    "neucodec>=0.0.4",  
    "accelerate; sys_platform == 'darwin'",
]

# PDF text extraction. Separate from core to keep the minimal install torch-free.
# Install with: pip install vieneu[pdf]
pdf = [
    "PyMuPDF>=1.25.0",
]

# Optional Resemble Perth audio watermark (needs torch + torchaudio; Perth runs at 32 kHz,
# so 48 kHz v3 output is resampled 48k→32k→48k around the watermark step).
# Install with: pip install vieneu[watermark]
watermark = [
    "resemble-perth>=1.0.1",
]

# v3 Turbo on CUDA (PyTorch backend) — what the docker/Dockerfile.gpu image installs.
# Install with: uv sync --extra cuda   (or: pip install vieneu[cuda])
cuda = [
    "transformers",
    "safetensors",
    "torch==2.8.0",
    "torchaudio==2.8.0",
]

# LoRA fine-tuning of v3 Turbo (finetune/): GPU only.
# Install with: uv sync --extra finetune   (or: pip install vieneu[finetune])
finetune = [
    "torch",
    "transformers",
    "peft>=0.13",
    "accelerate",
    "safetensors",
    "pyarrow",
]

[dependency-groups]
dev = [
    "pytest",
    "pytest-asyncio",
    # Test-only deps for the GPU/standard/xpu backend tests (NOT in the runtime
    # install — `pip install vieneu` stays minimal/torch-free). CI installs the dev
    # group, so these tests can import librosa/transformers/neucodec-based engines.
    "librosa>=0.11.0",
    "transformers",
    "neucodec>=0.0.4",
]
gpu = [
    "neucodec>=0.0.4",
    "torch==2.8.0",
    "torchaudio==2.8.0",
    "datasets>=3.2.0",
    "transformers; sys_platform == 'darwin'",
    "accelerate; sys_platform == 'darwin'",
    "trafilatura>=2.0.0",
]

[tool.pytest.ini_options]
testpaths = ["tests"]   # finetune/tests runs in its own process (see tests/test_finetune_lora.py)
pythonpath = ["src"]

[project.scripts]
vieneu-web = "apps.gradio_main:main"
vieneu-stream = "apps.web_stream:main"

[tool.setuptools]
package-dir = {"" = "src", "apps" = "apps", "examples" = "examples"}

[tool.setuptools.packages.find]
where = ["src", "."]
include = ["vieneu*", "vieneu_utils*", "apps*", "examples*"]

[tool.setuptools.package-data]
vieneu = ["assets/*.json", "assets/samples/*"]
examples = ["audio_ref/*.wav", "srt/*.srt"]  # samples the Gradio app (vieneu-web) offers

[tool.uv.sources]
torch = [
    { index = "pytorch", marker = "sys_platform != 'darwin'" },
    { index = "pypi", marker = "sys_platform == 'darwin'" }
]
torchaudio = [
    { index = "pytorch", marker = "sys_platform != 'darwin'" },
    { index = "pypi", marker = "sys_platform == 'darwin'" }
]