ARG CUDA_VERSION=12.1
ARG PYTHON_VERSION=3.10
ARG GET_PIP_URL="https://bootstrap.pypa.io/get-pip.py"

ARG BUILD_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04
ARG FINAL_BASE_IMAGE=nvidia/cuda:${CUDA_VERSION}-devel-ubuntu22.04

#################### BASE BUILD IMAGE ####################
# prepare basic build environment
FROM ${BUILD_BASE_IMAGE} AS base
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG TARGETPLATFORM
ARG INSTALL_KV_CONNECTORS=false
ENV DEBIAN_FRONTEND=noninteractive

ARG DEADSNAKES_MIRROR_URL
ARG DEADSNAKES_GPGKEY_URL
ARG GET_PIP_URL


# Install Python and other dependencies
RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
    && echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
    && apt-get update -y \
    && apt-get install -y ccache software-properties-common git curl sudo \
                           python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
    && update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
    && update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
    && ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
    && curl -sSf ${GET_PIP_URL} | python3 \
    && python3 --version && python3 -m pip --version


ARG PIP_INDEX_URL UV_INDEX_URL
ARG PIP_EXTRA_INDEX_URL UV_EXTRA_INDEX_URL
ARG PYTORCH_CUDA_INDEX_BASE_URL
ARG PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL
ARG PIP_KEYRING_PROVIDER UV_KEYRING_PROVIDER

# Install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/uv \
    python3 -m pip install uv

ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"

RUN apt-get install -y gcc-10 g++-10
RUN update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-10 110 --slave /usr/bin/g++ g++ /usr/bin/g++-10
RUN <<EOF
gcc --version
EOF


RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/

WORKDIR /workspace

# install build and runtime dependencies

RUN --mount=type=cache,target=/root/.cache/uv \
    if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
        uv pip install --system \
            --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') \
            "torch==2.8.0.dev20250318+cu128" "torchvision==0.22.0.dev20250319";  \
        uv pip install --system \
            --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') \
            --pre pytorch_triton==3.3.0+gitab727c40; \
    fi

COPY ./vllm_v0.10.0/requirements/common.txt requirements/common.txt
COPY ./vllm_v0.10.0/requirements/cuda.txt requirements/cuda.txt
RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install --system -r requirements/cuda.txt \
    --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')

ARG torch_cuda_arch_list='7.0 7.5 8.0 8.6 8.9 9.0 10.0 12.0'
ENV TORCH_CUDA_ARCH_LIST=${torch_cuda_arch_list}
# Override the arch list for flash-attn to reduce the binary size
ARG vllm_fa_cmake_gpu_arches='70-real;75-real;80-real;86-real;89-real;90-real;100-real;120-real'
ENV VLLM_FA_CMAKE_GPU_ARCHES=${vllm_fa_cmake_gpu_arches}
#################### BASE BUILD IMAGE ####################

#################### WHEEL BUILD IMAGE ####################
FROM base AS build

RUN curl -L -o sccache.tar.gz https://github.com/mozilla/sccache/releases/download/v0.8.1/sccache-v0.8.1-x86_64-unknown-linux-musl.tar.gz && \
    tar -xzf sccache.tar.gz && mv sccache-*/sccache /usr/local/bin/sccache && rm -rf sccache*

ARG TARGETPLATFORM

ARG PIP_INDEX_URL UV_INDEX_URL
ARG PIP_EXTRA_INDEX_URL UV_EXTRA_INDEX_URL
ARG PYTORCH_CUDA_INDEX_BASE_URL

# Set version for setuptools-scm
ENV SETUPTOOLS_SCM_PRETEND_VERSION=0.10.0

# install build dependencies
COPY ./vllm_v0.10.0/requirements/build.txt requirements/build.txt

ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"

RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install --system -r requirements/build.txt \
    --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')

COPY ./vllm_v0.10.0 /workspace

# max jobs used by Ninja to build extensions
ARG max_jobs=96
ENV MAX_JOBS=${max_jobs}
# number of threads used by nvcc
ARG nvcc_threads=8
ENV NVCC_THREADS=$nvcc_threads


# Flag to control whether to use pre-built vLLM wheels
ARG VLLM_USE_PRECOMPILED
# TODO: in setup.py VLLM_USE_PRECOMPILED is sensitive to truthiness, it will take =0 as "true", this should be fixed
ENV VLLM_USE_PRECOMPILED=""
RUN if [ "${VLLM_USE_PRECOMPILED}" = "1" ]; then \
        export VLLM_USE_PRECOMPILED=1 && \
        echo "Using precompiled wheels"; \
    else \
        unset VLLM_USE_PRECOMPILED && \
        echo "Leaving VLLM_USE_PRECOMPILED unset to build wheels from source"; \
    fi

# if USE_SCCACHE is set, use sccache to speed up compilation
RUN --mount=type=cache,target=/root/.cache/uv \
    --mount=type=cache,target=/root/.cache/torch_extensions \
    # --mount=type=bind,source=.git,target=.git \
    if [ "$USE_SCCACHE" = "1" ]; then \
        echo "Installing sccache..." \
        && curl -L -o sccache.tar.gz ${SCCACHE_DOWNLOAD_URL} \
        && tar -xzf sccache.tar.gz \
        && sudo mv sccache-v0.8.1-x86_64-unknown-linux-musl/sccache /usr/bin/sccache \
        && rm -rf sccache.tar.gz sccache-v0.8.1-x86_64-unknown-linux-musl \
        && if [ ! -z ${SCCACHE_ENDPOINT} ] ; then export SCCACHE_ENDPOINT=${SCCACHE_ENDPOINT} ; fi \
        && export SCCACHE_BUCKET=${SCCACHE_BUCKET_NAME} \
        && export SCCACHE_REGION=${SCCACHE_REGION_NAME} \
        && export SCCACHE_S3_NO_CREDENTIALS=${SCCACHE_S3_NO_CREDENTIALS} \
        && export SCCACHE_IDLE_TIMEOUT=0 \
        && export CMAKE_BUILD_TYPE=Release \
        && sccache --show-stats \
        && python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38 \
        && sccache --show-stats; \
    fi

ENV CCACHE_DIR=/root/.cache/ccache
RUN --mount=type=cache,target=/root/.cache/ccache \
    --mount=type=cache,target=/root/.cache/uv \
    # --mount=type=bind,source=.git,target=.git  \
    if [ "$USE_SCCACHE" != "1" ]; then \
        # Clean any existing CMake artifacts
        rm -rf .deps && \
        mkdir -p .deps && \
        python3 setup.py bdist_wheel --dist-dir=dist --py-limited-api=cp38; \
    fi

# Check the size of the wheel if RUN_WHEEL_CHECK is true
COPY ./vllm_v0.10.0/.buildkite/check-wheel-size.py check-wheel-size.py
# sync the default value with .buildkite/check-wheel-size.py
ARG VLLM_MAX_SIZE_MB=40000
ENV VLLM_MAX_SIZE_MB=$VLLM_MAX_SIZE_MB
ARG RUN_WHEEL_CHECK=true
RUN if [ "$RUN_WHEEL_CHECK" = "true" ]; then \
        python3 check-wheel-size.py dist; \
    else \
        echo "Skipping wheel size check."; \
    fi
#################### EXTENSION Build IMAGE ####################

#################### vLLM installation IMAGE ####################
FROM ${FINAL_BASE_IMAGE} AS vllm-base
ARG CUDA_VERSION
ARG PYTHON_VERSION
ARG INSTALL_KV_CONNECTORS=false
WORKDIR /vllm-workspace
ENV DEBIAN_FRONTEND=noninteractive
ARG TARGETPLATFORM

SHELL ["/bin/bash", "-c"]

ARG DEADSNAKES_MIRROR_URL
ARG DEADSNAKES_GPGKEY_URL
ARG GET_PIP_URL

RUN PYTHON_VERSION_STR=$(echo ${PYTHON_VERSION} | sed 's/\.//g') && \
    echo "export PYTHON_VERSION_STR=${PYTHON_VERSION_STR}" >> /etc/environment

# Install Python and other dependencies
RUN echo 'tzdata tzdata/Areas select America' | debconf-set-selections \
    && echo 'tzdata tzdata/Zones/America select Los_Angeles' | debconf-set-selections \
    && apt-get update -y \
    && apt-get install -y ccache software-properties-common git curl wget sudo vim \
                           ffmpeg libsm6 libxext6 libgl1 \
                           python${PYTHON_VERSION} python${PYTHON_VERSION}-dev python${PYTHON_VERSION}-venv \
    && update-alternatives --install /usr/bin/python3 python3 /usr/bin/python${PYTHON_VERSION} 1 \
    && update-alternatives --set python3 /usr/bin/python${PYTHON_VERSION} \
    && ln -sf /usr/bin/python${PYTHON_VERSION}-config /usr/bin/python3-config \
    && curl -sSf ${GET_PIP_URL} | python3 \
    && python3 --version && python3 -m pip --version


ARG PIP_INDEX_URL UV_INDEX_URL
ARG PIP_EXTRA_INDEX_URL UV_EXTRA_INDEX_URL
ARG PYTORCH_CUDA_INDEX_BASE_URL
ARG PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL
ARG PIP_KEYRING_PROVIDER UV_KEYRING_PROVIDER

# Install uv for faster pip installs
RUN --mount=type=cache,target=/root/.cache/uv \
    python3 -m pip install uv

# This timeout (in seconds) is necessary when installing some dependencies via uv since it's likely to time out
# Reference: https://github.com/astral-sh/uv/pull/1694
ENV UV_HTTP_TIMEOUT=500
ENV UV_INDEX_STRATEGY="unsafe-best-match"

RUN ldconfig /usr/local/cuda-$(echo $CUDA_VERSION | cut -d. -f1,2)/compat/

RUN --mount=type=cache,target=/root/.cache/uv \
    if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
        uv pip install --system \
            --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') \
            "torch==2.8.0.dev20250318+cu128" "torchvision==0.22.0.dev20250319" ; \
        uv pip install --system \
            --index-url ${PYTORCH_CUDA_NIGHTLY_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.') \
            --pre pytorch_triton==3.3.0+gitab727c40 ; \
    fi

# Install vllm wheel first, so that torch etc will be installed.
RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist \
    --mount=type=cache,target=/root/.cache/uv \
    uv pip install --system dist/*.whl --verbose \
        --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')

# Install FlashInfer from source
ARG FLASHINFER_GIT_REPO="https://github.com/flashinfer-ai/flashinfer.git"
ARG FLASHINFER_GIT_REF="v0.2.8rc1"
RUN --mount=type=cache,target=/root/.cache/uv bash - <<'BASH'
  . /etc/environment
    git clone --depth 1 --recursive --shallow-submodules \
        --branch ${FLASHINFER_GIT_REF} \
        ${FLASHINFER_GIT_REPO} flashinfer
    # Exclude CUDA arches for older versions (11.x and 12.0-12.7)
    # TODO: Update this to allow setting TORCH_CUDA_ARCH_LIST as a build arg.
    if [[ "${CUDA_VERSION}" == 11.* ]]; then
        FI_TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9"
    elif [[ "${CUDA_VERSION}" == 12.[0-7]* ]]; then
        FI_TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0a"
    else
        # CUDA 12.8+ supports 10.0a and 12.0
        FI_TORCH_CUDA_ARCH_LIST="7.0 7.5 8.0 8.6 8.9 9.0a 10.0a 12.0"

    fi
    echo "🏗️  Building FlashInfer for arches: ${FI_TORCH_CUDA_ARCH_LIST}"
    # Needed to build AOT kernels
    pushd flashinfer
        TORCH_CUDA_ARCH_LIST="${FI_TORCH_CUDA_ARCH_LIST}" \
            python3 -m flashinfer.aot
        TORCH_CUDA_ARCH_LIST="${FI_TORCH_CUDA_ARCH_LIST}" \
            uv pip install --system --no-build-isolation .
    popd
    rm -rf flashinfer \
           ~/.cache/flashinfer/aot/*/unused*

BASH
COPY ./vllm_v0.10.0/examples examples
COPY ./vllm_v0.10.0/benchmarks benchmarks
COPY ./vllm_v0.10.0/vllm/collect_env.py .

RUN --mount=type=cache,target=/root/.cache/uv \
. /etc/environment && \
uv pip list


COPY ./vllm_v0.10.0/requirements/build.txt requirements/build.txt
RUN --mount=type=cache,target=/root/.cache/uv \
    uv pip install --system -r requirements/build.txt \
        --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')

#################### vLLM installation IMAGE ####################


#################### OPENAI API SERVER ####################
# base openai image with additional requirements, for any subsequent openai-style images
FROM vllm-base AS vllm-openai-base
ARG TARGETPLATFORM
ARG INSTALL_KV_CONNECTORS=false

# ---- Add Tini as the container init process
ENV TINI_VERSION=v0.19.0
ADD https://github.com/krallin/tini/releases/download/${TINI_VERSION}/tini /tini
RUN chmod +x /tini
ENTRYPOINT ["/tini", "--"]

ARG PIP_INDEX_URL UV_INDEX_URL
ARG PIP_EXTRA_INDEX_URL UV_EXTRA_INDEX_URL

# This timeout (in seconds) is necessary when installing some dependencies via uv since it's likely to time out
# Reference: https://github.com/astral-sh/uv/pull/1694
ENV UV_HTTP_TIMEOUT=500

COPY ./vllm_v0.10.0/requirements/kv_connectors.txt requirements/kv_connectors.txt

# install additional dependencies for openai api server
RUN --mount=type=cache,target=/root/.cache/uv \
    if [ "$INSTALL_KV_CONNECTORS" = "true" ]; then \
        uv pip install --system -r ./vllm_v0.10.0/requirements/kv_connectors.txt; \
    fi; \
    if [ "$TARGETPLATFORM" = "linux/arm64" ]; then \
        BITSANDBYTES_VERSION="0.42.0"; \
    else \
        BITSANDBYTES_VERSION="0.46.1"; \
    fi; \
    uv pip install --system accelerate hf_transfer modelscope "bitsandbytes>=${BITSANDBYTES_VERSION}" 'timm==0.9.10' boto3 runai-model-streamer runai-model-streamer[s3] gradio==5.38.2

ENV VLLM_USAGE_SOURCE production-docker-image

# ---- Install supervisord ----
RUN apt-get update && apt-get install -y supervisor && mkdir -p /etc/supervisor/conf.d

# ---- Copy UI and supervisor config ----
COPY ./meta_ui.py /app/meta_ui.py
COPY ./supervisord.conf /etc/supervisor/supervisord.conf
# COPY ./Alibaba/Qwen3-30B-A3B /root/.cradle/Alibaba/Qwen3-30B-A3B
COPY ./Alibaba/Qwen3-4B /root/.cradle/Alibaba/Qwen3-4B
FROM vllm-openai-base AS vllm-openai

# ---- 暴露端口 ----
EXPOSE 30000 30001


CMD ["/usr/bin/supervisord", "-c", "/etc/supervisor/supervisord.conf"]
#################### OPENAI API SERVER ####################