Files
tts/pyproject.toml
kadirnar 32a8596aeb refactor: optimize inference backends with vLLM/SGLang support and fast-snac integration
- Add base class for all inference engines (shared config, SNAC decode, token processing)
- Replace HQQ backend with SGLang backend
- Fix vLLM to use prompt_token_ids (avoids special token loss in decode/re-encode)
- Enable CUDA graphs by default in vLLM (3.4x throughput improvement)
- Set default config to qwen3.yaml
- Add codebook clamp in SNAC decode for robustness
- Switch SNAC dependency to fast-snac
- Add pyproject.toml with optional deps: pip install vyvotts[vllm] / vyvotts[sglang]
- Clean up README
2026-04-02 08:08:32 +00:00

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TOML

[build-system]
requires = ["setuptools>=64"]
build-backend = "setuptools.build_meta"
[project]
name = "vyvotts"
version = "0.1.0"
description = "LLM-Based Text-to-Speech Training and Inference Framework"
readme = "README.md"
license = {text = "MIT"}
requires-python = ">=3.10"
dependencies = [
"transformers",
"datasets>=3.4",
"accelerate",
"snac @ git+https://github.com/kadirnar/fast-snac.git",
"soundfile",
"librosa",
"torchaudio",
]
[project.optional-dependencies]
vllm = ["vllm>=0.18"]
sglang = ["sglang[all]", "sgl-kernel"]
train = ["unsloth", "wandb", "trl", "kernels", "liger_kernel"]
[tool.setuptools.packages.find]
include = ["vyvotts*"]