ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.27.0 FROM ${BASE_IMAGE} AS base # Declare a variable to know if we want to use the nightly build or the stable build. # NOTE: REMINDER to vLLM-Omni rebase maintainer # Remember to set `USE_NIGHTLY_BUILD` to 0, when switching back to stable vLLM docker image # 1. If vLLM-omni maintainer is forced to use custom commits # during rebasing, they can change the two variables # 2. Whenever vLLM upstream has released a stable version, # we should swap over to use stable release ASAP. # We should avoid relying on custom commits. ARG USE_NIGHTLY_BUILD=0 ARG VLLM_VERSION_OR_COMMIT_HASH=v0.27.0 ARG ARG_PYTORCH_ROCM_ARCH ENV PYTORCH_ROCM_ARCH=${ARG_PYTORCH_ROCM_ARCH:-${PYTORCH_ROCM_ARCH}} ARG COMMON_WORKDIR=/app WORKDIR ${COMMON_WORKDIR} # Step 1: Setup - Install system dependencies. # Need to include ffmpeg because vllm rocm upstream docker image # does not include it. RUN apt-get update && \ apt-get install -y espeak-ng ffmpeg git jq && \ apt-get clean && \ rm -rf /var/lib/apt/lists/* # Step 2: Conditionally reinstall vllm from source for nightly builds RUN if [ "${USE_NIGHTLY_BUILD}" = "1" ]; then \ python3 -m pip uninstall -y vllm && rm -rf vllm && \ git clone https://github.com/vllm-project/vllm.git && \ cd vllm && \ git checkout ${VLLM_VERSION_OR_COMMIT_HASH} && \ python3 -m pip install -r requirements/rocm.txt && \ python3 setup.py clean --all && \ PYTORCH_ROCM_ARCH=${PYTORCH_ROCM_ARCH} python3 setup.py develop && \ cd ../ && \ rm -rf vllm/.git; \ fi # Build TorchCodec after any optional nightly vLLM reinstall so it targets the # final torch/ROCm ABI. Keep this layer before COPY . so source changes do not # invalidate the expensive native build. FFmpeg development headers are # removed after the wheel is built. COPY tools/install_torchcodec_rocm.sh /tmp/install_torchcodec_rocm.sh RUN --mount=type=cache,target=/root/.cache/pip \ --mount=type=cache,target=/root/.cache/torchcodec-wheels \ apt-get update && \ apt-get install -y --no-install-recommends \ pkg-config \ libavcodec-dev libavformat-dev libavutil-dev \ libswscale-dev libavdevice-dev libavfilter-dev libswresample-dev && \ bash /tmp/install_torchcodec_rocm.sh && \ apt-get purge -y \ libavcodec-dev libavformat-dev libavutil-dev \ libswscale-dev libavdevice-dev libavfilter-dev libswresample-dev && \ rm -f /tmp/install_torchcodec_rocm.sh && \ apt-get clean && \ rm -rf /var/lib/apt/lists/* # Step 3: Copy vllm-omni code and install without uv RUN mkdir -p ${COMMON_WORKDIR}/vllm-omni COPY . ${COMMON_WORKDIR}/vllm-omni # This is a workaround to ensure pytest exits with the correct status code in CI tests. RUN printf '%s\n' \ 'import os' \ '' \ '_exit_code = 1' \ '' \ 'def pytest_sessionfinish(session, exitstatus):' \ ' global _exit_code' \ ' _exit_code = int(exitstatus)' \ '' \ 'def pytest_unconfigure(config):' \ ' import sys' \ ' sys.stdout.flush()' \ ' sys.stderr.flush()' \ ' os._exit(_exit_code)' \ > ${COMMON_WORKDIR}/vllm-omni/conftest.py # Some optional dependencies pull in the CPU ONNX Runtime distribution. The # CPU and ROCm wheels own the same import path and cannot coexist, so remove # the CPU wheel and reinstall the ROCm wheel after dependency resolution. RUN cd ${COMMON_WORKDIR}/vllm-omni && \ uv pip install --python "$(python3 -c 'import sys; print(sys.executable)')" \ --no-cache-dir ".[dev]" --no-build-isolation && \ python3 -m pip uninstall -y onnxruntime && \ python3 -m pip install --no-cache-dir --force-reinstall --no-deps \ "onnxruntime-rocm>=1.22.2" && \ python3 -c "import importlib.metadata as m; import onnxruntime as ort; assert 'ROCMExecutionProvider' in ort.get_available_providers(), ort.get_available_providers(); assert m.version('onnxruntime-rocm'); assert not any(d.metadata['Name'] == 'onnxruntime' for d in m.distributions())" && \ python3 -c "from torchcodec.decoders import VideoDecoder" RUN ln -sf /usr/bin/python3 /usr/bin/python FROM base AS test CMD ["/bin/bash"] ENTRYPOINT [] # Set entrypoint for vllm-openai official images FROM base AS vllm-openai ENTRYPOINT ["vllm", "serve", "--omni"]