Dockerfile_dev

FROM nvidia/cuda:12.8.1-devel-ubuntu22.04 AS cu12.8

# environment variables
ENV DEBIAN_FRONTEND=noninteractive \
    TZ=Etc/UTC \
    PATH=/opt/py3/bin:/root/.local/bin:${PATH} \
    TRITON_PTXAS_PATH=/usr/local/cuda/bin/ptxas

# Install dependencies and create python virtual environment
RUN --mount=type=cache,target=/var/cache/apt \
    --mount=type=cache,target=/root/.cache \
    sed -i 's|http://archive.ubuntu.com|http://azure.archive.ubuntu.com|g' /etc/apt/sources.list && \
    apt-get update -y && \
    apt-get install -y --no-install-recommends \
        tzdata wget curl openssh-server ssh sudo git-core \
        libibverbs1 ibverbs-providers ibverbs-utils librdmacm1 \
        libibverbs-dev rdma-core libmlx5-1 libssl-dev pkg-config \
        vim rapidjson-dev libgoogle-glog-dev gdb cmake build-essential \
        python3-dev ninja-build htop tree jq unzip && \
    apt-get clean -y && \
    rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/* && \
    # install UV
    wget -qO- https://astral.sh/uv/install.sh | sh && \
    # create Python virtual environment
    uv venv -p python3.12 --seed /opt/py3

# Should be in the lmdeploy root directory when building docker image
COPY . /opt/lmdeploy

WORKDIR /opt/lmdeploy

# install lmdeploy and its dependencies
RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install -r requirements_cuda.txt --extra-index-url https://download.pytorch.org/whl/cu128 && \
    uv pip install -e .

# install flash_attn
RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install https://github.com/Dao-AILab/flash-attention/releases/download/v2.8.3/flash_attn-2.8.3+cu12torch2.8cxx11abiTRUE-cp312-cp312-linux_x86_64.whl

RUN uv cache clean