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# Define the image argument and provide a default value |
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#ARG IMAGE=python:3-slim-bullseye |
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# Use the image as specified |
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#FROM ${IMAGE} |
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# Re-declare the ARG after FROM |
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#ARG IMAGE |
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# Update and upgrade the existing packages |
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#RUN apt-get update && apt-get upgrade -y && apt-get install -y --no-install-recommends \ |
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#RUN mkdir /app |
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#WORKDIR /app |
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#COPY . . |
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#RUN python3 -m pip install --upgrade pip |
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#RUN make deps && make build && make clean |
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# Set environment variable for the host |
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#ENV HOST=0.0.0.0 |
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#ENV PORT=7860 |
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#ENV ORIGINS=* |
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# Install requirements.txt |
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#RUN pip install --no-cache-dir --upgrade -r requirements.txt |
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# Set up a new user named "user" with user ID 1000 |
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#RUN useradd -m -u 1000 user |
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# Switch to the "user" user |
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#USER user |
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# Set home to the user's home directory |
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#ENV HOME=/home/user \ |
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# PATH=/home/user/.local/bin:$PATH |
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# Set the working directory to the user's home directory |
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# WORKDIR $HOME/app |
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# Copy the current directory contents into the container at $HOME/app setting the owner to the user |
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#COPY --chown=user . $HOME |
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# Start the FastAPI app on port 7860, the default port expected by Spaces |
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#CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"] |
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#ENTRYPOINT ["python3"] |
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#ENTRYPOINT ["python3", "-m", "llama_cpp.server", "--hf_model_repo_id", "Qwen/Qwen1.5-0.5B-Chat-GGUF", "--model", "*q4_0.gguf", "--host", "0.0.0.0"] |
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FROM python:3-slim-bullseye |
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# It's not at all clear why the image published by the llama-cpp-python author doesn't work, |
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# but it can't find the llama libraries, soI had to re-build the docker container |
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# We need to set the host to 0.0.0.0 to allow outside access |
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ENV HOST 0.0.0.0 |
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COPY . . |
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# Install the package |
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RUN apt update && apt install -y libopenblas-dev ninja-build build-essential pkg-config |
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RUN python -m pip install --upgrade pip pytest cmake scikit-build setuptools fastapi uvicorn sse-starlette pydantic-settings starlette-context |
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RUN CMAKE_ARGS="-DLLAMA_BLAS=ON -DLLAMA_BLAS_VENDOR=OpenBLAS" pip install llama_cpp_python --verbose |
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# Run the server |
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CMD python3 -m llama_cpp.server --model $MODEL --n_gpu_layers $N_GPU_LAYERS --n_batch $N_BATCH |
