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# syntax=docker/dockerfile:1
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# Comments are provided throughout this file to help you get started.
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# If you need more help, visit the Dockerfile reference guide at
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# https://docs.docker.com/go/dockerfile-reference/
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# Want to help us make this template better? Share your feedback here: https://forms.gle/ybq9Krt8jtBL3iCk7
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ARG PYTHON_VERSION=3.11.9
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FROM python:${PYTHON_VERSION}-slim as base
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# Prevents Python from writing pyc files.
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ENV PYTHONDONTWRITEBYTECODE=1
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# Keeps Python from buffering stdout and stderr to avoid situations where
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# the application crashes without emitting any logs due to buffering.
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ENV PYTHONUNBUFFERED=1
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WORKDIR /app
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# Create a non-privileged user that the app will run under.
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# See https://docs.docker.com/go/dockerfile-user-best-practices/
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ARG UID=10001
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RUN adduser \
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--disabled-password \
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--gecos "" \
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--home "/nonexistent" \
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--shell "/sbin/nologin" \
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--no-create-home \
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--uid "${UID}" \
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appuser
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# Download dependencies as a separate step to take advantage of Docker's caching.
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# Leverage a cache mount to /root/.cache/pip to speed up subsequent builds.
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# Leverage a bind mount to requirements.txt to avoid having to copy them into
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# into this layer.
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RUN --mount=type=cache,target=/root/.cache/pip \
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--mount=type=bind,source=requirements.txt,target=requirements.txt \
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python -m pip install -r requirements.txt
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# Switch to the non-privileged user to run the application.
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USER appuser
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# Set the TRANSFORMERS_CACHE environment variable
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ENV TRANSFORMERS_CACHE=/tmp/.cache/huggingface
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# Create the cache folder with appropriate permissions
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RUN mkdir -p $TRANSFORMERS_CACHE && chmod -R 777 $TRANSFORMERS_CACHE
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# Set NLTK data directory
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ENV NLTK_DATA=/tmp/nltk_data
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# Create the NLTK data directory with appropriate permissions
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RUN mkdir -p $NLTK_DATA && chmod -R 777 $NLTK_DATA
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# Copy the source code into the container.
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COPY . .
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# Expose the port that the application listens on.
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EXPOSE 8000
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# Run the application.
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CMD uvicorn 'app:app' --host=0.0.0.0 --port=8000
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