# DiagraMine — Streamlit demo + FastAPI image for the Hugging Face Space.
#
# Same as the repo's Dockerfile, plus what a Space needs: Hugging Face runs
# the container as user 1000, so the app lives in that user's home (PaddleOCR
# caches its models under ~/.paddleocr); torch comes from the CPU-only index
# (the default wheels pull in CUDA, several GB); and the OCR models are fetched
# at build time so the first /extract after a cold start doesn't download them.
# nginx puts both apps on the one public port: the demo at /, the API at
# /extract, /health and /docs (see nginx.conf and start.sh).

FROM python:3.11-slim

ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=1 \
    DEBIAN_FRONTEND=noninteractive

# OS libs: OpenCV needs libGL + libglib; matplotlib needs libfreetype/libpng;
# paddlepaddle's CPU build links the OpenMP runtime (libgomp).
RUN apt-get update && apt-get install -y --no-install-recommends \
        libgomp1 \
        libgl1 \
        libglib2.0-0 \
        libsm6 \
        libxext6 \
        libxrender1 \
        libfreetype6 \
        libpng16-16 \
        nginx \
    && rm -rf /var/lib/apt/lists/*

RUN useradd -m -u 1000 user
USER user
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH \
    MPLCONFIGDIR=/home/user/.config/matplotlib
WORKDIR /home/user/app

# Install Python deps first for cacheability.
COPY --chown=user requirements.txt ./
RUN pip install --user --upgrade pip \
    && pip install --user --extra-index-url https://download.pytorch.org/whl/cpu -r requirements.txt

# Source.
COPY --chown=user src/ ./src/
COPY --chown=user diagram_analysis.py ./
COPY --chown=user data/icon_templates/ ./data/icon_templates/
COPY --chown=user app.py ui_theme.py search_interview_test.png ./
COPY --chown=user .streamlit/ ./.streamlit/
COPY --chown=user data/eval/ ./data/eval/
COPY --chown=user nginx.conf start.sh ./

# PaddleOCR's English det/rec/cls models (~15 MB), fetched now rather than on
# the first request. torch first, as in src/text_detection/paddle_detector.py.
RUN python -c "import torch; from paddleocr import PaddleOCR; PaddleOCR(use_angle_cls=True, lang='en', show_log=False)"

EXPOSE 8000

CMD ["bash", "start.sh"]