mirror of
https://github.com/Purple-Horizons/openclaw-voice.git
synced 2026-08-14 00:58:01 +00:00
gianni-dalerta
ca620b4a83
New features: - VAD integration in WebSocket flow (sends speech_detected status) - Streaming response module (sentence-by-sentence TTS) - Dockerfile with NVIDIA GPU support (CUDA 12.1) - docker-compose.yml (GPU + CPU profiles) - React component package (@openclaw/voice-widget-react) Roadmap progress: ✅ VAD ✅ Streaming responses ✅ Docker GPU support ✅ React component ✅ API key auth ✅ Continuous mode Remaining: - WebRTC - Vue component - Kubernetes Helm - RunPod template Tests: 25 passing
63 lines
1.7 KiB
Docker
63 lines
1.7 KiB
Docker
# OpenClaw Voice - GPU-enabled Docker image
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# Supports NVIDIA GPUs for fast Whisper + TTS inference
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FROM nvidia/cuda:12.1-cudnn8-runtime-ubuntu22.04
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# Prevent interactive prompts
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ENV DEBIAN_FRONTEND=noninteractive
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# Install Python and dependencies
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RUN apt-get update && apt-get install -y \
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python3.11 \
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python3.11-venv \
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python3-pip \
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ffmpeg \
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libsndfile1 \
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git \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# Set Python 3.11 as default
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RUN update-alternatives --install /usr/bin/python python /usr/bin/python3.11 1 \
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&& update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1
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# Create app directory
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WORKDIR /app
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# Install uv for fast package management
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RUN curl -LsSf https://astral.sh/uv/install.sh | sh
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ENV PATH="/root/.cargo/bin:$PATH"
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# Copy requirements first for caching
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COPY requirements.txt pyproject.toml ./
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# Create venv and install dependencies
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RUN uv venv && \
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. .venv/bin/activate && \
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uv pip install -e ".[stt]" && \
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uv pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu121
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# Copy application code
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COPY src/ ./src/
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COPY .env.example ./.env.example
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# Create directories for models (will be mounted or downloaded)
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RUN mkdir -p /app/models /app/voices
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# Environment variables
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ENV OPENCLAW_HOST=0.0.0.0
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ENV OPENCLAW_PORT=8765
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ENV OPENCLAW_STT_MODEL=large-v3-turbo
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ENV OPENCLAW_STT_DEVICE=cuda
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ENV OPENCLAW_REQUIRE_AUTH=true
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# Expose port
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EXPOSE 8765
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# Health check
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HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
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CMD curl -f http://localhost:8765/ || exit 1
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# Run server
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CMD [".venv/bin/python", "-m", "uvicorn", "src.server.main:app", "--host", "0.0.0.0", "--port", "8765"]
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