Smaller docker image CUDA example

Look at the existing Dockerfiles in the repository, likely in a docker/ directory or referenced in the README. Compare the provided multi-stage Dockerfile to the current approach. Test building the image to verify the size reduction and that GPU support works. The goal is to integrate this improved Dockerfile into the project's documentation or examples.

ive been struggling some with a Cuda dockerfile sinze the devel image was so large the build ended up at almost 8gb, i came up with this. just wanted to share it:

FROM nvidia/cuda:12.1.1-devel-ubuntu22.04 AS builder

RUN apt-get update && apt-get upgrade -y \
    && apt-get install -y git build-essential \
    python3 python3-pip gcc wget \
    ocl-icd-opencl-dev opencl-headers clinfo \
    libclblast-dev libopenblas-dev \
    && mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd

# setting build related env vars
ENV CUDA_DOCKER_ARCH=all
ENV LLAMA_CUBLAS=1

# Install depencencies
RUN python3 -m pip install --user --upgrade pip pytest cmake scikit-build setuptools fastapi uvicorn sse-starlette pydantic-settings starlette-context

# Install llama-cpp-python (build with cuda)
RUN CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install --user llama-cpp-python

FROM nvidia/cuda:12.1.1-runtime-ubuntu22.04

RUN apt-get update && apt-get upgrade -y \
    && apt-get install -y git build-essential \
    python3 python3-pip gcc wget \
    ocl-icd-opencl-dev opencl-headers clinfo \
    libclblast-dev libopenblas-dev \
    && mkdir -p /etc/OpenCL/vendors && echo "libnvidia-opencl.so.1" > /etc/OpenCL/vendors/nvidia.icd

# Copy libraries from build local path
COPY --from=builder /root/.local /root/.local
COPY --from=builder /tmp/*.txt /tmp/
ENV PATH=/root/.local:$PATH

the final image ended up att aroung 2gb and GPU support is working as expected..