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d5d0624311
* Use multi stage build to slim down ML image size
* Use gunicorn as WSGI server in ML image
* Configure gunicorn server for ML use case
* Use requirements.txt file to install python dependencies in ML image
* Make ML listen IP configurable
* Revert "Use requirements.txt file to install python dependencies in ML image"
This reverts commit 32e706c7f3.
* Separate out pip installs in ML builder image
26 lines
682 B
Docker
26 lines
682 B
Docker
FROM python:3.10 as builder
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ENV PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PIP_NO_CACHE_DIR=true
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RUN python -m venv /opt/venv
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RUN /opt/venv/bin/pip install --pre torch -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
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RUN /opt/venv/bin/pip install transformers tqdm numpy scikit-learn scipy nltk sentencepiece flask Pillow gunicorn
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RUN /opt/venv/bin/pip install --no-deps sentence-transformers
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FROM python:3.10-slim
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COPY --from=builder /opt/venv /opt/venv
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ENV TRANSFORMERS_CACHE=/cache \
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PATH="/opt/venv/bin:$PATH"
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WORKDIR /usr/src/app
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COPY . .
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CMD ["gunicorn", "src.main:server"]
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