Dockerfile

FROM python:3.11-slim

WORKDIR /app

# Install system deps
RUN apt-get update && apt-get install -y --no-install-recommends \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install CPU-only PyTorch first (much smaller than full CUDA build)
RUN pip install --no-cache-dir \
    torch==2.2.2+cpu \
    torchvision==0.17.2+cpu \
    --index-url https://download.pytorch.org/whl/cpu

# Install remaining dependencies
COPY requirements-deploy.txt .
RUN pip install --no-cache-dir -r requirements-deploy.txt

# Download model weights at build time from Hugging Face
RUN mkdir -p weights && \
    curl -L -o weights/advanced_model_best.pth \
    https://huggingface.co/Aredeksu/SensiNet-Mammography/resolve/main/advanced_model_best.pth

# Copy application code
COPY app/ app/

# Hugging Face Spaces expects port 7860
ENV MODEL_MODE=real \
    MODEL_VERSION=sensinet-v1 \
    PORT=7860

EXPOSE 7860

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]