Dockerfile.sglang

# SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

# Note: This Dockerfile will be deprecated in favor of Dockerfile.sglang-wideep soon. Please build the container with that Dockerfile instead.

ARG BASE_IMAGE="nvcr.io/nvidia/cuda-dl-base"
# TODO OPS-612: NCCL will hang with 25.03, so use 25.01 for now
# Please check https://github.com/ai-dynamo/dynamo/pull/1065
# for details and reproducer to manually test if the image
# can be updated to later versions.
ARG BASE_IMAGE_TAG="25.01-cuda12.8-devel-ubuntu24.04"
ARG RUNTIME_IMAGE="nvcr.io/nvidia/cuda"
ARG RUNTIME_IMAGE_TAG="12.8.1-runtime-ubuntu24.04"

# Make sure to update the dependency version in pyproject.toml when updating this
ARG SGLANG_VERSION="0.5.3.post2"


# Define general architecture ARGs for supporting both x86 and aarch64 builds.
#   ARCH: Used for package suffixes (e.g., amd64, arm64)
#   ARCH_ALT: Used for Rust targets, manylinux suffix (e.g., x86_64, aarch64)
#
# Default values are for x86/amd64:
#   --build-arg ARCH=amd64 --build-arg ARCH_ALT=x86_64
#
# For arm64/aarch64, build with:
#   --build-arg ARCH=arm64 --build-arg ARCH_ALT=aarch64
#
# NOTE: There isn't an easy way to define one of these values based on the other value
# without adding if statements everywhere, so just define both as ARGs for now.
ARG ARCH=amd64
ARG ARCH_ALT=x86_64
# Python configuration
ARG PYTHON_VERSION=3.12

ARG DYNAMO_BASE_IMAGE="dynamo:latest-none"
FROM ${DYNAMO_BASE_IMAGE} AS dynamo_base

########################################################
########## Framework Development Image ################
########################################################
#
# PURPOSE: Framework development and SGLang compilation
#
# This stage builds and compiles framework dependencies including:
# - SGLang inference engine with CUDA support
# - All necessary build tools and compilation dependencies
# - Framework-level Python packages and extensions
#
# Use this stage when you need to:
# - Build SGLang from source with custom modifications
# - Develop or debug framework-level components
# - Create custom builds with specific optimization flags
#

# Use dynamo base image (see /container/Dockerfile for more details)
FROM ${BASE_IMAGE}:${BASE_IMAGE_TAG} AS framework

ARG PYTHON_VERSION

RUN apt-get update -y \
    && DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
        # Python runtime - CRITICAL for virtual environment to work
        python${PYTHON_VERSION}-dev \
        build-essential \
        git \
        git-lfs \
        # SGLang build dependencies
        cmake \
        ibverbs-providers \
        ibverbs-utils \
        libibumad-dev \
        libibverbs-dev \
        libnuma-dev \
        librdmacm-dev \
        rdma-core \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/*

### VIRTUAL ENVIRONMENT SETUP ###

COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
ARG PYTHON_VERSION
# Create virtual environment
RUN mkdir -p /opt/dynamo/venv && \
    uv venv /opt/dynamo/venv --python $PYTHON_VERSION

# Activate virtual environment
ENV VIRTUAL_ENV=/opt/dynamo/venv \
    PATH="/opt/dynamo/venv/bin:${PATH}"

ARG ARCH
# Redeclare ARCH and ARCH_ALT so they're available in this stage
ARG ARCH_ALT


WORKDIR /workspace
# Install SGLang and related dependencies
ARG SGLANG_VERSION
RUN --mount=type=cache,target=/root/.cache/uv \
    cd /opt && \
    git clone https://github.com/sgl-project/sglang.git && \
    cd sglang && \
    git checkout v${SGLANG_VERSION} && \
    # Install in editable mode for development
    uv pip install --prerelease=allow -e "python[all]"

# Set env var that allows for forceful shutdown of inflight requests in SGL's TokenizerManager
ENV SGL_FORCE_SHUTDOWN=1

##################################################
########## Runtime Image ########################
##################################################
#
# PURPOSE: Production runtime environment
#
# This stage creates a lightweight production-ready image containing:
# - Pre-compiled SGLang and framework dependencies
# - Dynamo runtime libraries and Python packages
# - Essential runtime dependencies and configurations
# - Optimized for inference workloads and deployment
#
# Use this stage when you need:
# - Production deployment of Dynamo with SGLang
# - Minimal runtime footprint without build tools
# - Ready-to-run inference server environment
# - Base for custom application containers
#

FROM ${RUNTIME_IMAGE}:${RUNTIME_IMAGE_TAG} AS runtime

WORKDIR /workspace
ENV DYNAMO_HOME=/opt/dynamo
ENV VIRTUAL_ENV=/opt/dynamo/venv
ENV PATH="${VIRTUAL_ENV}/bin:${PATH}"

ARG ARCH_ALT
ARG PYTHON_VERSION
ENV NIXL_PREFIX=/opt/nvidia/nvda_nixl
ENV NIXL_LIB_DIR=$NIXL_PREFIX/lib/${ARCH_ALT}-linux-gnu
ENV NIXL_PLUGIN_DIR=$NIXL_LIB_DIR/plugins

# Install Python, build-essential and python3-dev as apt dependencies
RUN apt-get update && \
    DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
        # Python runtime - CRITICAL for virtual environment to work
        python${PYTHON_VERSION}-dev \
        build-essential \
        # jq and curl for polling various endpoints and health checks
        jq \
        git \
        git-lfs \
        curl \
        # Libraries required by UCX to find RDMA devices
        libibverbs1 rdma-core ibverbs-utils libibumad3 \
        libnuma1 librdmacm1 ibverbs-providers \
        # JIT Kernel Compilation, flashinfer
        ninja-build \
        g++ \
        # prometheus dependencies
        ca-certificates && \
    rm -rf /var/lib/apt/lists/*

# Copy CUDA development tools (nvcc, headers, dependencies, etc.) from framework devel image
COPY --from=framework /usr/local/cuda/bin/nvcc /usr/local/cuda/bin/nvcc
COPY --from=framework /usr/local/cuda/bin/cudafe++ /usr/local/cuda/bin/cudafe++
COPY --from=framework /usr/local/cuda/bin/ptxas /usr/local/cuda/bin/ptxas
COPY --from=framework /usr/local/cuda/bin/fatbinary /usr/local/cuda/bin/fatbinary
COPY --from=framework /usr/local/cuda/include/ /usr/local/cuda/include/
COPY --from=framework /usr/local/cuda/nvvm /usr/local/cuda/nvvm
COPY --from=framework /usr/local/cuda/lib64/libcudart.so* /usr/local/cuda/lib64/

### COPY NATS & ETCD ###
# Copy nats and etcd from dynamo_base image
COPY --from=dynamo_base /usr/bin/nats-server /usr/bin/nats-server
COPY --from=dynamo_base /usr/local/bin/etcd/ /usr/local/bin/etcd/
# Add ETCD and CUDA binaries to PATH so cicc and other CUDA tools are accessible
ENV PATH=/usr/local/bin/etcd/:/usr/local/cuda/nvvm/bin:$PATH

# Copy UCX from framework image as plugin for NIXL
# Copy NIXL source from framework image
# Copy dynamo wheels for gitlab artifacts
COPY --from=dynamo_base /usr/local/ucx /usr/local/ucx
COPY --from=dynamo_base $NIXL_PREFIX $NIXL_PREFIX

# Copies sglang repo (editable install)
COPY --from=framework /opt/sglang /opt/sglang

ENV LD_LIBRARY_PATH=\
$NIXL_LIB_DIR:\
$NIXL_PLUGIN_DIR:\
/usr/local/ucx/lib:\
/usr/local/ucx/lib/ucx:\
$LD_LIBRARY_PATH

### VIRTUAL ENVIRONMENT SETUP ###

# Copy uv and entire virtual environment from framework container
COPY --from=framework /bin/uv /bin/uvx /bin/
COPY --from=framework ${VIRTUAL_ENV} ${VIRTUAL_ENV}

# Install dynamo, NIXL, and dynamo-specific dependencies
COPY benchmarks/ /opt/dynamo/benchmarks/
COPY --from=dynamo_base /opt/dynamo/wheelhouse/ /opt/dynamo/wheelhouse/
RUN uv pip install \
    /opt/dynamo/wheelhouse/ai_dynamo_runtime*.whl \
    /opt/dynamo/wheelhouse/ai_dynamo*any.whl \
    /opt/dynamo/wheelhouse/nixl/nixl*.whl \
    && cd /opt/dynamo/benchmarks \
    && UV_GIT_LFS=1 uv pip install --no-cache . \
    && cd - \
    && rm -rf /opt/dynamo/benchmarks

# Install common and test dependencies
RUN --mount=type=bind,source=./container/deps/requirements.txt,target=/tmp/requirements.txt \
    --mount=type=bind,source=./container/deps/requirements.test.txt,target=/tmp/requirements.test.txt \
    UV_GIT_LFS=1 uv pip install \
        --no-cache \
        --requirement /tmp/requirements.txt \
        --requirement /tmp/requirements.test.txt

# Copy launch banner
RUN --mount=type=bind,source=./container/launch_message.txt,target=/workspace/launch_message.txt \
    sed '/^#\s/d' /workspace/launch_message.txt > ~/.launch_screen && \
    echo "cat ~/.launch_screen" >> ~/.bashrc

# Copy tests, benchmarks, deploy and components for CI
COPY tests /workspace/tests
COPY benchmarks /workspace/benchmarks
COPY examples /workspace/examples
COPY deploy /workspace/deploy
COPY components/ /workspace/components/

# Copy attribution files
COPY ATTRIBUTION* LICENSE /workspace/

ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
CMD []

###########################################################
########## Development (run.sh, runs as root user) ########
###########################################################
#
# PURPOSE: Local development environment for use with run.sh (not Dev Container plug-in)
#
# This stage runs as root and provides:
# - Development tools and utilities for local debugging
# - Support for vscode/cursor development outside the Dev Container plug-in
#
# Use this stage if you need a full-featured development environment with extra tools,
# but do not use it with the Dev Container plug-in.

FROM runtime AS dev

# Don't want ubuntu to be editable, just change uid and gid.
ARG WORKSPACE_DIR=/workspace

# Install utilities as root
RUN apt-get update -y && \
    apt-get install -y --no-install-recommends  \
    # Install utilities
    nvtop \
    wget \
    tmux \
    vim \
    git \
    openssh-client \
    iproute2 \
    rsync \
    zip \
    unzip \
    htop \
    # Build Dependencies
    autoconf \
    automake \
    cmake \
    libtool \
    meson \
    net-tools \
    pybind11-dev \
    # Rust build dependencies
    clang \
    libclang-dev \
    protobuf-compiler && \
    rm -rf /var/lib/apt/lists/*

# Set workspace directory variable
ENV WORKSPACE_DIR=${WORKSPACE_DIR} \
    DYNAMO_HOME=${WORKSPACE_DIR} \
    RUSTUP_HOME=/usr/local/rustup \
    CARGO_HOME=/usr/local/cargo \
    CARGO_TARGET_DIR=/workspace/target \
    VIRTUAL_ENV=/opt/dynamo/venv \
    PATH=/usr/local/cargo/bin:$PATH

COPY --from=dynamo_base /usr/local/rustup /usr/local/rustup
COPY --from=dynamo_base /usr/local/cargo /usr/local/cargo

# Install maturin, for maturin develop
RUN uv pip install maturin[patchelf]

# Editable install of dynamo
COPY pyproject.toml README.md hatch_build.py /workspace/
RUN uv pip install --no-deps -e .

ENTRYPOINT ["/opt/nvidia/nvidia_entrypoint.sh"]
CMD []