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feat: run goose in a docker-style sandbox #44
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# Use an official Python runtime as a parent image | ||
FROM python:3.10-slim | ||
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# Set the working directory in the container | ||
WORKDIR /app | ||
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# Install SSL certificates, update certifi, install pipx and move to path | ||
RUN apt-get update && apt-get install -y ca-certificates git curl make \ | ||
&& pip install --upgrade certifi \ | ||
&& pip install pipx \ | ||
&& pipx ensurepath | ||
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# Install goose-ai CLI using pipx | ||
RUN pipx install goose-ai | ||
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# Make sure the PATH is updated | ||
ENV PATH="/root/.local/bin:${PATH}" | ||
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# Run an infinite loop to keep the container running for testing | ||
ENTRYPOINT ["goose", "session", "start"] | ||
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# once built, you can run this with something like: | ||
# docker run -it --env OPENAI_API_KEY goose-ai | ||
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# | ||
# To use goose in a docker style sandbox for experimenting. |
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If the image was built before and this layer is cached, the user won't have the latest
goose-ai
if there is a new release.We could either to disable the cache of this layer or the user can install the latest in the docker container
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@lifeizhou-ap what about if this instead was built as part of the py release workflow - and pushed as a versioned image to the GH docker registry - would that be suitable?