respeak-ai 0.1.2

Modules required for conversation, released as a Python SDK.

respeak

Provides the modules required for conversation and is released as a Python SDK.

Install

pip install respeak

# local development
pip install -e .

Optional extras:

pip install "respeak[vad]"
pip install "respeak[tts]"
pip install "respeak[llm]"
pip install "respeak[dev]"

Usage

from respeak import StreamingParaformerAsr, CosyVoice3Tts, SileroVad, Qwen3LLM

# ASR
asr = StreamingParaformerAsr.from_pretrained(asr="path/or/model_id", punc_model="path/or/model_id")
text = asr.generate(input=audio_chunk, is_final=False, cache={})

# CosyVoice3 TTS (vLLM)
tts = CosyVoice3Tts.from_pretrained(
    model_dir="path/to/TTS_Model",
    prompt_text="...",
    prompt_wav="path/to/prompt.wav",
    load_vllm=True,
)
for wav in tts.generate("你好，欢迎使用本系统。", stream=True):
    ...

# VAD
vad = SileroVad.from_pretrained()
speech_prob = vad.generate(audio_chunk)

# LLM sentence-level streaming
llm = Qwen3LLM.from_pretrained(
    "path/to/LLM_Model_ft",
    base_prompt_file="path/to/base_prompt.md",
    persona_setting="你叫小睿，是一个温和的中文助手。",
    strategy_prompt="回答要简洁自然。",
)
for sentence in llm.generate("你好，介绍一下你自己。", stream=True):
    ...

New model types should live under src/respeak/models/<name>/ (subclass BaseModel, expose from_pretrained / generate). Add matching tests under tests/models/<name>/.

Examples

# ASR
python examples/paraformer_asr_streaming.py \
  --asr path/to/ASR_Model \
  --punc path/to/PUNC_Model \
  --audio path/to/test.wav

# TTS (requires .[tts])
python examples/cosyvoice3_tts_streaming.py \
  --model-dir path/to/Fun-CosyVoice3 \
  --prompt-wav path/to/prompt.wav \
  --prompt-text "..." \
  --text "你好，欢迎使用本系统。" \
  --output output.wav

# VAD (requires .[vad])
python examples/silerovad_real_inference.py \
  --audio path/to/test.wav \
  --threshold 0.5

# LLM (requires .[llm])
python examples/qwen3_llm_streaming.py \
  --model-path path/to/LLM_Model_ft \
  --base-prompt path/to/base_prompt.md \
  --text "你好，介绍一下你自己。"

Tests

pip install -e ".[dev]"
pytest tests/models -q

Publish to PyPI

CI runs on every push/PR to main. Publishing is triggered by pushing a version tag.

One-time PyPI setup

1. Create a project on PyPI named respeak.
2. In PyPI → Publishing → Add a new pending publisher:
   • Owner: shanguanma
   • Repository: respeak
   • Workflow: publish-pypi.yml
   • Environment: pypi

Release flow

# 1. Bump version in pyproject.toml
# 2. Commit and tag
git tag v0.1.1
git push origin main
git push origin v0.1.1

The tag must match pyproject.toml (v0.1.1 ↔ version = "0.1.1").