59 lines
1.6 KiB
Docker
59 lines
1.6 KiB
Docker
# RealtimeSTT Container
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# Uses Faster-Whisper with CUDA for GPU-accelerated inference
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# Includes dual VAD (WebRTC + Silero) for robust voice detection
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FROM nvidia/cuda:12.6.2-cudnn-runtime-ubuntu22.04
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# Prevent interactive prompts during build
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ENV DEBIAN_FRONTEND=noninteractive
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ENV PYTHONUNBUFFERED=1
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# Set working directory
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WORKDIR /app
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# Install system 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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python3.11-dev \
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python3-pip \
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build-essential \
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ffmpeg \
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libsndfile1 \
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libportaudio2 \
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portaudio19-dev \
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git \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# Upgrade pip
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RUN python3.11 -m pip install --upgrade pip
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# Copy requirements first (for Docker layer caching)
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COPY requirements.txt .
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# Install Python dependencies
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RUN python3.11 -m pip install --no-cache-dir -r requirements.txt
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# Install PyTorch with CUDA 12.1 support (compatible with CUDA 12.6)
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RUN python3.11 -m pip install --no-cache-dir \
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torch==2.5.1+cu121 \
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torchaudio==2.5.1+cu121 \
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--index-url https://download.pytorch.org/whl/cu121
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# Copy application code
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COPY stt_server.py .
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# Create models directory (models will be downloaded on first run)
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RUN mkdir -p /root/.cache/huggingface
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# Expose WebSocket port
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EXPOSE 8766
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# Health check - use netcat to check if port is listening
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HEALTHCHECK --interval=30s --timeout=10s --start-period=120s --retries=3 \
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CMD python3.11 -c "import socket; s=socket.socket(); s.settimeout(2); s.connect(('localhost', 8766)); s.close()" || exit 1
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# Run the server
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CMD ["python3.11", "stt_server.py"]
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