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add CUDA Dockerfile and .dockerignore
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* | ||
!*.py | ||
!requirements.txt | ||
!SOURCE_DOCUMENTS |
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# syntax=docker/dockerfile:1 | ||
# Build as `docker build . -t localgpt`, requires BuildKit. | ||
# Run as `docker run -it --mount src="$HOME/.cache",target=/root/.cache,type=bind --gpus=all localgpt`, requires Nvidia container toolkit. | ||
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FROM nvidia/cuda:11.7.1-runtime-ubuntu22.04 | ||
RUN apt-get update && apt-get install -y software-properties-common | ||
RUN apt-get install -y g++-11 make python3 python-is-python3 pip | ||
# only copy what's needed at every step to optimize layer cache | ||
COPY ./requirements.txt . | ||
# use BuildKit cache mount to drastically reduce redownloading from pip on repeated builds | ||
RUN --mount=type=cache,target=/root/.cache pip install --timeout 100 -r requirements.txt | ||
RUN --mount=type=cache,target=/root/.cache CMAKE_ARGS="-DLLAMA_CUBLAS=on" FORCE_CMAKE=1 pip install --upgrade --force-reinstall llama-cpp-python | ||
COPY SOURCE_DOCUMENTS ./SOURCE_DOCUMENTS | ||
COPY ingest.py constants.py ./ | ||
# Docker BuildKit does not support GPU during *docker build* time right now, only during *docker run*. | ||
# See <https://github.com/moby/buildkit/issues/1436>. | ||
# If this changes in the future you can `docker build --build-arg device_type=cuda . -t localgpt` (+GPU argument to be determined). | ||
ARG device_type=cpu | ||
RUN --mount=type=cache,target=/root/.cache python ingest.py --device_type $device_type | ||
COPY . . | ||
ENV device_type=cuda | ||
CMD python run_localGPT.py --device_type $device_type |
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