Spaces:
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74c6d68 0353241 74c6d68 0353241 74c6d68 0353241 74c6d68 0353241 8890033 74c6d68 0353241 8890033 74c6d68 8890033 74c6d68 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | # ─── Dockerfile for Predictive Maintenance Streamlit App ───
# Build: docker build -t predictive-maintenance-app .
# Run: docker run -p 8501:8501 predictive-maintenance-app
# Optional: mount a local model for offline use:
# docker run -p 8501:8501 -v $(pwd)/models:/app/models predictive-maintenance-app
FROM python:3.11-slim
WORKDIR /app
# System deps: build-essential for any pip wheels, curl for HEALTHCHECK
RUN apt-get update && apt-get install -y --no-install-recommends \
build-essential \
curl \
&& rm -rf /var/lib/apt/lists/*
COPY requirements.txt .
RUN pip install --no-cache-dir --upgrade pip && \
pip install --no-cache-dir -r requirements.txt
COPY app.py .
# Optional: copy local model so the app can run without Hugging Face at runtime
# Uncomment and ensure models/ exists when building with a pre-downloaded model:
# COPY models/best_random_forest.pkl models/
# HF Spaces Docker default is app_port 7860; proxy forwards to this port
EXPOSE 7860
HEALTHCHECK --interval=30s --timeout=5s --start-period=10s --retries=3 \
CMD curl -f http://localhost:7860/_stcore/health || exit 1
CMD ["streamlit", "run", "app.py", \
"--server.port=7860", \
"--server.address=0.0.0.0", \
"--server.headless=true"]
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