realtimetts-qwen-native-cpu

realtimetts-qwen-native-cpu is the CPU-only native binding used by the RealtimeTTS Qwen CPU server. The distribution name is realtimetts-qwen-native-cpu; the Python import is qwentts_cpp_cpu, so it can be installed beside the CUDA package without an import collision.

Version 0.4.1 bundles the qualified qwentts.cpp CPU implementation at commit 791d7df22afc408b3786fbe694c421ce055ae5d5 (C ABI v5), including the parked worker pool, strict affinity handling, onset-silence profiles, and CPU recovery path. Model weights and voice references are not included.

CPU scheduling

Pass cpu_codec_threads with a positive worker count to overlap audio decoding with code generation. cpu_stream_frames=2 selects 160 ms delivery chunks; zero retains the native default. Optional cpu_affinity and cpu_codec_affinity are logical-CPU masks; zero leaves scheduling to the OS. Defaults remain serial.

Set QWENTTS_CPU_STARTUP_PRIORITY=second_chunk before constructing a CPU context to prioritize the second decode block; unset/off preserves normal overlap. Requires overlap and a two/four-frame cadence, and is not a quality or sampling setting. See CHANGELOG.md for measurements and limitations.

Install

In a fresh virtual environment, install the matching wheel from PyPI:

python -m pip install --upgrade pip
python -m pip install "realtimetts-qwen-native-cpu==0.4.1"
python -c "import qwentts_cpp_cpu as q; print(q.__version__, q.QT_ABI_VERSION, q.CPU_ONLY)"

The release provides these CPU wheels:

The native payload has no CUDA, Metal, Vulkan, OpenMP, or BLAS dependency. The x86_64 builds use GGML_NATIVE=OFF with a fixed AVX2/FMA/F16C/BMI2 kernel baseline; they require a CPU with those features. The macOS arm64 wheel is built separately for Apple Silicon. There is no runtime CPU dispatcher or generic x86 fallback.

Only the four platform families above have bundled native wheels. On another platform, do not rely on an automatic source fallback: the sdist intentionally refuses to create a wheel without the pinned native library and a qualified qwentts.cpp checkout.

Use

from qwentts_cpp_cpu import QwenLibrary, QwenTTS

library = QwenLibrary()
assert library.cpu_only()
print(library.version())

Model files can be resolved from the configured Hugging Face repository:

from qwentts_cpp_cpu import resolve_gguf_paths

talker, codec = resolve_gguf_paths(
    "Qwen/Qwen3-TTS-12Hz-0.6B-Base", quant="Q8_0"
)

The full RealtimeTTS CPU server supplies HTTP streaming, segmentation, language detection, and recovery behavior on top of this binding.

Build from source

Clone this repository and the pinned native source, then build the wheel and sdist:

# Requires CMake, a C++ compiler, and the platform's native build tools.
git clone --branch codex/qwen-cpu-public-release https://github.com/KoljaB/realtimetts-qwen-native.git
cd realtimetts-qwen-native
git clone https://github.com/KoljaB/qwentts.cpp.git third_party/qwentts.cpp
git -C third_party/qwentts.cpp checkout 791d7df22afc408b3786fbe694c421ce055ae5d5
git -C third_party/qwentts.cpp submodule update --init --recursive
python -m pip install --upgrade build
python scripts/build_native.py --source third_party/qwentts.cpp --backend cpu --clean
python -m build --sdist --wheel

The build helper verifies the native revision and ABI before configuring CMake. The wheel bundles only qwen, ggml, ggml-base, and ggml-cpu shared libraries with an origin-relative runtime path; it refuses a build with no native payload.