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https://github.com/khoj-ai/khoj.git
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5f3f6b7c61
- Add a productionized setup for the Khoj server using `gunicorn` with multiple workers for handling requests - Add a new Dockerfile meant for production config at `ghcr.io/khoj-ai/khoj:prod`; the existing Docker config should remain the same
30 lines
902 B
Docker
30 lines
902 B
Docker
# Use Nvidia's latest Ubuntu 22.04 image as the base image
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FROM nvidia/cuda:12.2.0-devel-ubuntu22.04
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LABEL org.opencontainers.image.source https://github.com/khoj-ai/khoj
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# Install System Dependencies
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RUN apt update -y && apt -y install python3-pip git
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WORKDIR /app
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# Install Application
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COPY pyproject.toml .
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COPY README.md .
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RUN sed -i 's/dynamic = \["version"\]/version = "0.0.0"/' pyproject.toml && \
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TMPDIR=/home/cache/ pip install --cache-dir=/home/cache/ -e .
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# Copy Source Code
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COPY . .
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RUN apt install vim -y
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# Set the PYTHONPATH environment variable in order for it to find the Django app.
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ENV PYTHONPATH=/app/src:$PYTHONPATH
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# Run the Application
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# There are more arguments required for the application to run,
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# but these should be passed in through the docker-compose.yml file.
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ARG PORT
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EXPOSE ${PORT}
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ENTRYPOINT [ "gunicorn", "-c", "gunicorn-config.py", "src.khoj.main:app" ]
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