Add GPU-enabled Dockerfile for Spark

- Create docker/Dockerfile.spark using pytorch/pytorch CUDA base image
- Update compose.spark.yml to use Spark-specific Dockerfile
- Fixes CUDA not available issue on DGX Spark

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

docker/Dockerfile.spark

@@ -0,0 +1,32 @@
+# GPU-enabled Dockerfile for DGX Spark deployment
+FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    curl \
+    build-essential \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+WORKDIR /app
+
+# Copy and install Python requirements
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy backend code
+COPY backend/ ./backend/
+COPY app.py .
+
+# Create runs directory
+RUN mkdir -p /app/runs
+
+# Health check (uses configurable port via environment)
+HEALTHCHECK --interval=30s --timeout=3s --start-period=60s --retries=3 \
+    CMD curl -f http://localhost:${PORT:-8000}/health || exit 1
+
+# Expose configurable port
+EXPOSE ${PORT:-8000}
+
+# Default command (overridden by compose.spark.yml)
+CMD ["uvicorn", "backend.model_service:app", "--host", "0.0.0.0", "--port", "8000"]

docker/compose.spark.yml

@@ -10,7 +10,7 @@ services:
   visualisable-ai-backend:
     build:
       context: ..
-      dockerfile: Dockerfile
+      dockerfile: docker/Dockerfile.spark
     ports:
       - "${PORT:-8000}:${PORT:-8000}"
     environment: