# syntax=docker/dockerfile:1.6

FROM nvidia/cuda:13.1.1-devel-ubuntu24.04

ENV DEBIAN_FRONTEND=noninteractive
ENV PIP_BREAK_SYSTEM_PACKAGES=1
ENV VLLM_BASE_DIR=/workspace/vllm

# Just in case if some JIT compilation happens during runtime
# Limit build parallelism to reduce OOM situations
ARG BUILD_JOBS=16
ENV MAX_JOBS=${BUILD_JOBS}
ENV CMAKE_BUILD_PARALLEL_LEVEL=${BUILD_JOBS}
ENV NINJAFLAGS="-j${BUILD_JOBS}"
ENV MAKEFLAGS="-j${BUILD_JOBS}"

# Set pip cache directory
ENV PIP_CACHE_DIR=/root/.cache/pip
ENV UV_CACHE_DIR=/root/.cache/uv
ENV UV_SYSTEM_PYTHON=1
ENV UV_LINK_MODE=copy
ENV UV_BREAK_SYSTEM_PACKAGES=1

# Install minimal runtime dependencies (NCCL, Python)
# Note: "devel" tools like cmake/gcc are NOT installed here to save space
RUN apt update && apt upgrade -y \
    && apt install -y --allow-change-held-packages --no-install-recommends \
    python3 python3-pip python3-dev vim curl git wget jq \
    libcudnn9-cuda-13 \
    libnccl-dev libnccl2 libibverbs1 libibverbs-dev rdma-core \
    libxcb1 \
    && rm -rf /var/lib/apt/lists/* \
    && pip install uv

# Set final working directory
WORKDIR $VLLM_BASE_DIR

# Download Tiktoken files
RUN mkdir -p tiktoken_encodings && \
    wget -O tiktoken_encodings/o200k_base.tiktoken "https://openaipublic.blob.core.windows.net/encodings/o200k_base.tiktoken" && \
    wget -O tiktoken_encodings/cl100k_base.tiktoken "https://openaipublic.blob.core.windows.net/encodings/cl100k_base.tiktoken"

# Cache TEMPORARY PATCH for fastsafetensors loading in cluster setup - tracking https://github.com/vllm-project/vllm/issues/34180
# COPY fastsafetensors.patch .

# Install fastsafetensors
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
    uv pip install -U fastsafetensors

# --- VLLM SOURCE CACHE BUSTER ---
# Change THIS argument to force a fresh git clone and rebuild of vLLM
# without re-installing the dependencies above.
ARG CACHEBUST_VLLM=1
ARG WHEELS_FROM_GITHUB_RELEASE=0

# Install vLLM
# If INSTALL_FROM_GITHUB_RELEASE is 1, install from GitHub releases (specific for aarch64/cu130 as requested)
# Otherwise, install from nightly wheels
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
    if [ "$WHEELS_FROM_GITHUB_RELEASE" = "1" ]; then \
        export VLLM_VERSION=$(curl -s https://api.github.com/repos/vllm-project/vllm/releases/latest | jq -r .tag_name | sed 's/^v//') && \
        uv pip install -U https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu130-cp38-abi3-manylinux_2_35_aarch64.whl --torch-backend=auto; \
    else \
        uv pip install -U vllm \
        --torch-backend=auto \
        --extra-index-url https://wheels.vllm.ai/nightly/cu130; \
    fi

# Apply TEMPORARY PATCH for fastsafetensors loading in cluster setup - tracking https://github.com/vllm-project/vllm/issues/34180
# Apply in site-packages
# RUN if patch -p1 --dry-run --reverse -d /usr/local/lib/python3.12/dist-packages < ${VLLM_BASE_DIR}/fastsafetensors.patch &>/dev/null; then \
#         echo "PR #34180 is already applied"; \
#     else \
#         patch -p1 -d /usr/local/lib/python3.12/dist-packages < ${VLLM_BASE_DIR}/fastsafetensors.patch; \
#     fi

ARG FLASHINFER_PRE=""

# Install flashinfer helper packages
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
    uv pip install ${FLASHINFER_PRE} flashinfer-python -U --no-deps --index-url https://flashinfer.ai/whl && \
    uv pip install ${FLASHINFER_PRE} flashinfer-cubin --index-url https://flashinfer.ai/whl && \
    uv pip install ${FLASHINFER_PRE} flashinfer-jit-cache --index-url https://flashinfer.ai/whl/cu130

ARG PRE_TRANSFORMERS=0
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
    if [ "$PRE_TRANSFORMERS" = "1" ]; then \
        uv pip install -U transformers --pre; \
        uv pip install numpy==2.2.6; \
    fi

# Setup Env for Runtime
ENV TORCH_CUDA_ARCH_LIST=12.1a
ENV TRITON_PTXAS_PATH=/usr/local/cuda/bin/ptxas
ENV TIKTOKEN_ENCODINGS_BASE=$VLLM_BASE_DIR/tiktoken_encodings

# Copy scripts
COPY run-cluster-node.sh $VLLM_BASE_DIR/
RUN chmod +x $VLLM_BASE_DIR/run-cluster-node.sh

# Final extra deps
RUN --mount=type=cache,id=uv-cache,target=/root/.cache/uv \
    uv pip install ray[default]