Dockerfile

# Multi-stage Dockerfile for Edge Anomaly Detection
# Optimized for production deployment

# Stage 1: Base image with Python and dependencies
FROM python:3.10-slim as base

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=1 \
    PIP_DISABLE_PIP_VERSION_CHECK=1

WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    git \
    wget \
    && rm -rf /var/lib/apt/lists/*

# Stage 2: Build dependencies
FROM base as builder

# Copy requirements
COPY requirements.txt .

# Install Python dependencies
RUN pip install --user --no-warn-script-location -r requirements.txt

# Stage 3: Runtime image
FROM base as runtime

# Copy Python dependencies from builder
COPY --from=builder /root/.local /root/.local

# Make sure scripts in .local are usable
ENV PATH=/root/.local/bin:$PATH

# Copy application code
COPY . /app

# Install package
RUN pip install --no-deps -e .

# Create necessary directories
RUN mkdir -p /app/data /app/exports /app/checkpoints /app/logs

# Expose ports
EXPOSE 8000
EXPOSE 9090

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD python -c "import requests; requests.get('http://localhost:8000/health')" || exit 1

# Default command (can be overridden)
CMD ["python", "api/app.py"]

# Alternative commands for different services:
# Training: CMD ["python", "train.py"]
# Inference: CMD ["python", "inference.py", "--model", "exports/model.onnx", "--backend", "onnx"]