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bfb9a40d58
The darwin build resolved the wheel URL via api.github.com, whose unauthenticated rate limit (60/hr per IP) 403s on shared macOS runners (observed after the 9-min vLLM source build). Construct the release-asset download URL deterministically from the pinned tag and the cp312/arm64 wheel name instead - no API call, no rate limit. Verified the URL resolves (200). Signed-off-by: Ettore Di Giacinto <mudler@localai.io> Assisted-by: Claude:opus-4.8 [Claude Code]
231 lines
11 KiB
Bash
Executable File
231 lines
11 KiB
Bash
Executable File
#!/bin/bash
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set -e
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EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
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# Avoid to overcommit the CPU during build
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# https://github.com/vllm-project/vllm/issues/20079
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# https://docs.vllm.ai/en/v0.8.3/serving/env_vars.html
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# https://docs.redhat.com/it/documentation/red_hat_ai_inference_server/3.0/html/vllm_server_arguments/environment_variables-server-arguments
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export NVCC_THREADS=2
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export MAX_JOBS=1
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backend_dir=$(dirname $0)
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if [ -d $backend_dir/common ]; then
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source $backend_dir/common/libbackend.sh
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else
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source $backend_dir/../common/libbackend.sh
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fi
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# Intel XPU: torch==2.11.0+xpu lives on the PyTorch XPU index, transitive
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# deps on PyPI — unsafe-best-match lets uv mix both. vllm-xpu-kernels only
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# ships a python3.12 wheel per upstream docs, so bump the portable Python
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# before installRequirements (matches the l4t13 pattern below).
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# https://github.com/vllm-project/vllm/blob/main/docs/getting_started/installation/gpu.xpu.inc.md
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if [ "x${BUILD_PROFILE}" == "xintel" ]; then
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PYTHON_VERSION="3.12"
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PYTHON_PATCH="11"
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EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
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fi
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# CPU builds need unsafe-best-match to pull torch==2.10.0+cpu from the
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# pytorch test channel while still resolving transformers/vllm from pypi.
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if [ "x${BUILD_PROFILE}" == "xcpu" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
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fi
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# cublas13 pulls the vLLM wheel from a per-tag cu130 index (PyPI's vllm wheel
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# is built against CUDA 12 and won't load on cu130). uv's default per-package
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# first-match strategy would still pick the PyPI wheel, so allow it to consult
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# every configured index when resolving.
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if [ "x${BUILD_PROFILE}" == "xcublas13" ]; then
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EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
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fi
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# Apple Silicon (Metal/MLX) via vllm-metal.
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# vllm-metal (github.com/vllm-project/vllm-metal) brings vLLM to macOS on Apple
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# Silicon: it registers through vLLM's platform-plugin entry point
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# (metal -> vllm_metal:register), MetalPlatform activates, and the vLLM v1
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# AsyncLLM engine runs on the GPU through MLX. LocalAI's backend.py is UNCHANGED
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# on darwin — AsyncEngineArgs(...) -> AsyncLLMEngine.from_engine_args transparently
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# resolves to the MLX engine (proven on a real M4 / macOS 26.5 against Qwen3-0.6B).
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#
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# vllm-metal REQUIRES Python 3.12, so force the portable CPython before the venv
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# is created (ensureVenv reads PYTHON_VERSION/PYTHON_PATCH/PY_STANDALONE_TAG).
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# The patch + standalone tag mirror the l4t13 cp312 pin — a known-good
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# python-build-standalone release that also ships an aarch64-apple-darwin asset.
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if [ "$(uname -s)" = "Darwin" ]; then
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PYTHON_VERSION="3.12"
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PYTHON_PATCH="12"
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PY_STANDALONE_TAG="20251120"
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fi
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# JetPack 7 / L4T arm64 vllm + torch wheels come straight from PyPI now
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# (torch 2.11+ ships aarch64 + cu130 manylinux wheels and vllm 0.20+ ships
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# an aarch64 wheel pinned to that torch). They're cp312-only, so bump the
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# venv Python accordingly. JetPack 6 keeps cp310 + USE_PIP=true.
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# https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/
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if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
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USE_PIP=true
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fi
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if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
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PYTHON_VERSION="3.12"
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PYTHON_PATCH="12"
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PY_STANDALONE_TAG="20251120"
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fi
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# ===================== Apple Silicon (Metal/MLX) =====================
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# Reproduce vllm-metal's upstream installer
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# (curl -fsSL https://raw.githubusercontent.com/vllm-project/vllm-metal/main/install.sh)
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# but INTO LocalAI's managed venv (ensureVenv) instead of a throwaway
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# ~/.venv-vllm-metal, so the backend integrates with LocalAI's venv lifecycle
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# (portable CPython, _makeVenvPortable relocation, runtime activation). The
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# normal CUDA/CPU installRequirements is skipped on darwin — there is no
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# macOS/arm64 vLLM wheel on PyPI; vLLM is built from source and the MLX engine
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# is layered on by the vllm-metal wheel.
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if [ "$(uname -s)" = "Darwin" ]; then
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# Create/activate the portable 3.12 venv. On darwin USE_PIP=true and
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# PORTABLE_PYTHON=true (set by scripts/build/python-darwin.sh), so this is a
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# `python -m venv` based, relocatable venv.
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ensureVenv
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# vllm-metal's installer drives everything through `uv`: building vLLM from
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# the CPU requirements needs `--index-strategy unsafe-best-match` (mixes the
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# pytorch CPU channel with PyPI), a flag plain pip does not have. The darwin
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# venv is pip-based, so bootstrap uv into it. uv honours $VIRTUAL_ENV (set by
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# libbackend's _activateVenv) and installs into THIS venv — same pattern the
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# intel branch below relies on.
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pip install uv
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# The ONLY darwin version pin -- AUTO-BUMPED by .github/bump_vllm_metal.sh,
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# which tracks vllm-project/vllm-metal releases (NOT vllm/vllm latest). Keep
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# it as a plain double-quoted assignment on its own line so the bumper's sed
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# can rewrite it. Darwin therefore follows vllm-metal and can lag the Linux
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# vllm pin (requirements-cublas13-after.txt, bumped independently against
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# vllm/vllm) until vllm-metal supports a newer vLLM.
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VLLM_METAL_VERSION="v0.3.0.dev20260622062346"
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# The coupled vLLM source version is whatever this vllm-metal release builds
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# against -- it declares it in its own installer as `vllm_v=`. Derive it from
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# the PINNED tag rather than hardcoding a second value that could drift. The
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# tag is immutable, so this stays reproducible across rebuilds.
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VLLM_VERSION=$(curl -fsSL "https://raw.githubusercontent.com/vllm-project/vllm-metal/${VLLM_METAL_VERSION}/install.sh" \
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| grep -oE 'vllm_v="[0-9]+\.[0-9]+\.[0-9]+"' | head -n1 | cut -d'"' -f2)
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if [ -z "${VLLM_VERSION}" ]; then
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echo "ERROR: could not derive the vLLM version from vllm-metal ${VLLM_METAL_VERSION}" >&2
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exit 1
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fi
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echo "vllm-metal ${VLLM_METAL_VERSION} builds against vLLM ${VLLM_VERSION}"
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_vllm_src=$(mktemp -d)
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trap 'rm -rf "${_vllm_src}"' EXIT
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pushd "${_vllm_src}"
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# 1) Build vLLM ${VLLM_VERSION} from the release source tarball against
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# the CPU requirements. vllm-metal layers its MLX platform plugin on
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# top of this exact build.
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curl -fsSL -o "vllm-${VLLM_VERSION}.tar.gz" \
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"https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}.tar.gz"
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tar -xzf "vllm-${VLLM_VERSION}.tar.gz"
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pushd "vllm-${VLLM_VERSION}"
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uv pip install -r requirements/cpu.txt --index-strategy unsafe-best-match
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# -Wno-parentheses: clang on macOS treats one of vLLM's C++ warnings
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# as an error without it (matches the upstream installer's CXXFLAGS).
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CXXFLAGS="-Wno-parentheses" uv pip install .
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popd
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popd
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# 2) Install the prebuilt vllm-metal wheel for the PINNED release. It pulls
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# mlx / mlx-metal as deps and registers the `metal` platform plugin that
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# backend.py resolves to at engine-init time. Build the release-asset URL
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# deterministically (tag + the cp312/arm64 wheel name) rather than querying
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# api.github.com, whose unauthenticated rate limit (60/hr per IP) 403s on
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# shared CI runners. The wheel version is the tag without its leading 'v'.
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_metal_wheel="vllm_metal-${VLLM_METAL_VERSION#v}-cp312-cp312-macosx_11_0_arm64.whl"
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_metal_wheel_url="https://github.com/vllm-project/vllm-metal/releases/download/${VLLM_METAL_VERSION}/${_metal_wheel}"
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echo "Installing vllm-metal wheel: ${_metal_wheel_url}"
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uv pip install "${_metal_wheel_url}"
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# Generate the gRPC stubs (backend_pb2*). installRequirements normally does
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# this via runProtogen at the end; we skipped installRequirements on darwin,
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# so call it explicitly here.
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runProtogen
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# Intel XPU has no upstream-published vllm wheels, so we always build vllm
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# from source against torch-xpu and replace the default triton with
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# triton-xpu (matching torch 2.11). Mirrors the upstream procedure:
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# https://github.com/vllm-project/vllm/blob/main/docs/getting_started/installation/gpu.xpu.inc.md
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elif [ "x${BUILD_TYPE}" == "xintel" ]; then
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# Hide requirements-intel-after.txt so installRequirements doesn't
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# try `pip install vllm` (would either fail or grab a non-XPU wheel).
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_intel_after="${backend_dir}/requirements-intel-after.txt"
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_intel_after_bak=""
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if [ -f "${_intel_after}" ]; then
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_intel_after_bak="${_intel_after}.xpu.bak"
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mv "${_intel_after}" "${_intel_after_bak}"
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fi
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installRequirements
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if [ -n "${_intel_after_bak}" ]; then
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mv "${_intel_after_bak}" "${_intel_after}"
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fi
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# vllm's CMake build needs the Intel oneAPI dpcpp/sycl compiler — the
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# base image (intel/oneapi-basekit) has it but the env isn't sourced.
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if [ -f /opt/intel/oneapi/setvars.sh ]; then
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set +u
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source /opt/intel/oneapi/setvars.sh --force
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set -u
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fi
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_vllm_src=$(mktemp -d)
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trap 'rm -rf "${_vllm_src}"' EXIT
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git clone --depth 1 https://github.com/vllm-project/vllm "${_vllm_src}/vllm"
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pushd "${_vllm_src}/vllm"
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# Install vllm's own runtime deps (torch-xpu, vllm_xpu_kernels,
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# pydantic, fastapi, …) from upstream's requirements/xpu.txt — the
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# canonical source of truth. Avoids re-pinning everything ourselves.
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uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} -r requirements/xpu.txt
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# Stock triton (NVIDIA-only) may have come in transitively; replace
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# with triton-xpu==3.7.0 which matches torch 2.11.
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uv pip uninstall triton triton-xpu 2>/dev/null || true
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uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} \
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--extra-index-url https://download.pytorch.org/whl/xpu \
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triton-xpu==3.7.0
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export CMAKE_PREFIX_PATH="$(python -c 'import site; print(site.getsitepackages()[0])'):${CMAKE_PREFIX_PATH:-}"
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VLLM_TARGET_DEVICE=xpu uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps .
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popd
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# FROM_SOURCE=true on a CPU build skips the prebuilt vllm wheel in
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# requirements-cpu-after.txt and compiles vllm locally against the host's
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# actual CPU. Not used by default because it takes ~30-40 minutes, but
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# kept here for hosts where the prebuilt wheel SIGILLs (CPU without the
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# required SIMD baseline, e.g. AVX-512 VNNI/BF16). Default CI uses a
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# bigger-runner with compatible hardware instead.
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elif [ "x${BUILD_TYPE}" == "x" ] && [ "x${FROM_SOURCE:-}" == "xtrue" ]; then
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# Temporarily hide the prebuilt wheel so installRequirements doesn't
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# pull it — the rest of the requirements files (base deps, torch,
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# transformers) are still installed normally.
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_cpu_after="${backend_dir}/requirements-cpu-after.txt"
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_cpu_after_bak=""
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if [ -f "${_cpu_after}" ]; then
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_cpu_after_bak="${_cpu_after}.from-source.bak"
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mv "${_cpu_after}" "${_cpu_after_bak}"
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fi
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installRequirements
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if [ -n "${_cpu_after_bak}" ]; then
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mv "${_cpu_after_bak}" "${_cpu_after}"
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fi
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# Build vllm from source against the installed torch.
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# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/
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_vllm_src=$(mktemp -d)
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trap 'rm -rf "${_vllm_src}"' EXIT
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git clone --depth 1 https://github.com/vllm-project/vllm "${_vllm_src}/vllm"
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pushd "${_vllm_src}/vllm"
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uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm
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# Respect pre-installed torch version — skip vllm's own requirements-build.txt torch pin.
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VLLM_TARGET_DEVICE=cpu uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps .
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popd
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else
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installRequirements
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fi
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