Files
encoach_backend/Dockerfile

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1.5 KiB
Docker

FROM python:3.11-slim as requirements-stage
WORKDIR /tmp
RUN pip install poetry
COPY pyproject.toml ./poetry.lock* /tmp/
# https://python-poetry.org/docs/cli#export
RUN poetry self add poetry-plugin-export
RUN poetry export -f requirements.txt --output requirements.txt --without-hashes
FROM python:3.11-slim
# Allow statements and log messages to immediately appear in the logs
ENV PYTHONUNBUFFERED True
# Copy local code to the container image.
ENV APP_HOME /app
WORKDIR $APP_HOME
COPY . ./
COPY --from=requirements-stage /tmp/requirements.txt /app/requirements.txt
RUN apt update && apt install -y \
ffmpeg \
poppler-utils \
texlive-latex-base \
texlive-fonts-recommended \
texlive-latex-extra \
texlive-xetex \
pandoc \
librsvg2-bin \
curl \
&& rm -rf /var/lib/apt/lists/*
RUN curl -sL https://deb.nodesource.com/setup_20.x | bash - \
&& apt-get install -y nodejs
RUN npm install -g firebase-tools
RUN pip install --no-cache-dir -r /app/requirements.txt
EXPOSE 8000
# Run the web service on container startup. Here we use the gunicorn
# webserver, with one worker process and 8 threads.
# For environments with multiple CPU cores, increase the number of workers
# to be equal to the cores available.
# Timeout is set to 0 to disable the timeouts of the workers to allow Cloud Run to handle instance scaling.
ENTRYPOINT ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "1", "--threads", "8", "--timeout", "0", "-k", "uvicorn.workers.UvicornWorker", "ielts_be:app"]