48 lines
1.4 KiB
Docker
48 lines
1.4 KiB
Docker
# ==============================================================================
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# BETTING-ANALYTICS ML ENGINE - Python FastAPI Dockerfile
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# ==============================================================================
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# Multi-stage build for ML service with optional GPU support
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# ==============================================================================
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# Stage 1: Builder
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FROM python:3.11-slim AS builder
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WORKDIR /app
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# Install build dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# Install Python dependencies
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COPY requirements.txt .
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RUN pip install --no-cache-dir --user -r requirements.txt
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# Stage 2: Production
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FROM python:3.11-slim AS runner
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WORKDIR /app
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ENV PYTHONDONTWRITEBYTECODE=1
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ENV PYTHONUNBUFFERED=1
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ENV PATH="/home/appuser/.local/bin:$PATH"
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# Create non-root user
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RUN addgroup --system --gid 1001 appgroup
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RUN adduser --system --uid 1001 --gid 1001 appuser
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# Copy Python packages from builder
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COPY --from=builder /root/.local /home/appuser/.local
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# Copy application code
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COPY --chown=appuser:appgroup . .
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USER appuser
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EXPOSE 3093
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HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
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CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:3093/health')" || exit 1
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CMD ["uvicorn", "src.main:app", "--host", "0.0.0.0", "--port", "3093"]
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