4dd3c7600e
- Remove torch/torchaudio/torchvision from requirements.txt (installed separately in Docker) - Use >= instead of == for most packages to avoid version conflicts - Install numpy before other requirements - Add setuptools and wheel to pip upgrade step
56 lines
1.6 KiB
Docker
56 lines
1.6 KiB
Docker
FROM python:3.11-slim
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# Set working directory
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WORKDIR /app
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# Install system dependencies including CUDA-related packages
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RUN apt-get update && apt-get install -y \
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ffmpeg \
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git \
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wget \
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curl \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# Copy requirements first for better Docker layer caching
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COPY requirements.txt .
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# Upgrade pip and install build tools
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RUN pip install --upgrade pip setuptools wheel
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# Install CUDA-optimized PyTorch FIRST (before other requirements)
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# Using latest versions from cu118 index for SpeechBrain 1.0 / pyannote diarization compatibility
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RUN pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
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# Install numpy first as many packages depend on it
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RUN pip install --no-cache-dir "numpy>=1.24.0"
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# Install remaining dependencies from requirements.txt
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RUN pip install --no-cache-dir -r requirements.txt
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# Copy application code
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COPY . .
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# Create directories for mounted volumes
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RUN mkdir -p /app/data/videos /app/data/outputs /app/data/cache
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# Set environment variables
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ENV STREAMLIT_SERVER_PORT=8501
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ENV STREAMLIT_SERVER_ADDRESS=0.0.0.0
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ENV STREAMLIT_SERVER_HEADLESS=true
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ENV STREAMLIT_BROWSER_GATHER_USAGE_STATS=false
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# GPU-specific environment variables
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ENV CUDA_VISIBLE_DEVICES=0
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ENV NVIDIA_VISIBLE_DEVICES=all
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ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# Expose Streamlit port
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EXPOSE 8501
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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:8501/_stcore/health || exit 1
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# Start the application
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CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"] |