# Remote WebGPU Clustering Service Dockerfile
# Based on NVIDIA PyTorch Geometric container which includes cuGraph/RAPIDS for GPU acceleration

FROM nvcr.io/nvidia/pyg:25.05-py3

# Set working directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    curl \
    wget \
    git \
    build-essential \
    && rm -rf /var/lib/apt/lists/*

# Install Python dependencies for remote WebGPU service
COPY requirements-remote-webgpu.txt .
RUN pip install --no-cache-dir -r requirements-remote-webgpu.txt

# Install additional dependencies for WebRTC streaming
RUN pip install --no-cache-dir \
    opencv-python-headless \
    plotly \
    kaleido \
    Pillow \
    redis

# Copy service files
COPY remote_webgpu_clustering_service.py .
COPY unified_gpu_service.py .
COPY local_gpu_viz_service.py .
COPY simple_webgpu_test.py .

# Create directories for temporary files
RUN mkdir -p /tmp/webrtc_frames

# Set environment variables
ENV PYTHONPATH=/app
ENV CUDA_VISIBLE_DEVICES=0

# Expose port
EXPOSE 8083

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:8083/health || exit 1

# Start the main remote WebGPU clustering service
CMD ["python", "remote_webgpu_clustering_service.py"]