Files
LocalAI/backend/python/vllm/install.sh
Ettore Di Giacinto 66963f49db refactor(vllm): retire l4t13 pyproject.toml in favor of requirements-*.txt
pyproject.toml only existed because uv pip install -r requirements.txt
doesn't honor [tool.uv.sources]. The previous commit dropped [tool.uv.
sources] (PyPI now serves the aarch64 + cu130 wheels directly), so the
file no longer carries any logic the requirements-*.txt path can't.

Replace with the same two-file pattern every other build profile uses:

  - requirements-l4t13.txt       (accelerate / torch / transformers /
                                  bitsandbytes - matches cublas13's split)
  - requirements-l4t13-after.txt (vllm; runs after the base resolve so
                                  the cu130 torch wheel lands first)

install.sh's whole l4t13 elif branch goes away; libbackend.sh's
installRequirements already handles the requirements-install.txt build-
deps pass, the C_INCLUDE_PATH export for PORTABLE_PYTHON, and the
runProtogen call, so falling through to the standard else: branch
produces identical install behavior with less surface area.

No functional change at install time - same wheels, same order.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-22 19:46:13 +00:00

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#!/bin/bash
set -e
EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
# Avoid to overcommit the CPU during build
# https://github.com/vllm-project/vllm/issues/20079
# https://docs.vllm.ai/en/v0.8.3/serving/env_vars.html
# https://docs.redhat.com/it/documentation/red_hat_ai_inference_server/3.0/html/vllm_server_arguments/environment_variables-server-arguments
export NVCC_THREADS=2
export MAX_JOBS=1
backend_dir=$(dirname $0)
if [ -d $backend_dir/common ]; then
source $backend_dir/common/libbackend.sh
else
source $backend_dir/../common/libbackend.sh
fi
# Intel XPU: torch==2.11.0+xpu lives on the PyTorch XPU index, transitive
# deps on PyPI — unsafe-best-match lets uv mix both. vllm-xpu-kernels only
# ships a python3.12 wheel per upstream docs, so bump the portable Python
# before installRequirements (matches the l4t13 pattern below).
# https://github.com/vllm-project/vllm/blob/main/docs/getting_started/installation/gpu.xpu.inc.md
if [ "x${BUILD_PROFILE}" == "xintel" ]; then
PYTHON_VERSION="3.12"
PYTHON_PATCH="11"
EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
fi
# CPU builds need unsafe-best-match to pull torch==2.10.0+cpu from the
# pytorch test channel while still resolving transformers/vllm from pypi.
if [ "x${BUILD_PROFILE}" == "xcpu" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
fi
# cublas13 pulls the vLLM wheel from a per-tag cu130 index (PyPI's vllm wheel
# is built against CUDA 12 and won't load on cu130). uv's default per-package
# first-match strategy would still pick the PyPI wheel, so allow it to consult
# every configured index when resolving.
if [ "x${BUILD_PROFILE}" == "xcublas13" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
fi
# JetPack 7 / L4T arm64 vllm + torch wheels come straight from PyPI now
# (torch 2.11+ ships aarch64 + cu130 manylinux wheels and vllm 0.20+ ships
# an aarch64 wheel pinned to that torch). They're cp312-only, so bump the
# venv Python accordingly. JetPack 6 keeps cp310 + USE_PIP=true.
# https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/
if [ "x${BUILD_PROFILE}" == "xl4t12" ]; then
USE_PIP=true
fi
if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
PYTHON_VERSION="3.12"
PYTHON_PATCH="12"
PY_STANDALONE_TAG="20251120"
fi
# Intel XPU has no upstream-published vllm wheels, so we always build vllm
# from source against torch-xpu and replace the default triton with
# triton-xpu (matching torch 2.11). Mirrors the upstream procedure:
# https://github.com/vllm-project/vllm/blob/main/docs/getting_started/installation/gpu.xpu.inc.md
if [ "x${BUILD_TYPE}" == "xintel" ]; then
# Hide requirements-intel-after.txt so installRequirements doesn't
# try `pip install vllm` (would either fail or grab a non-XPU wheel).
_intel_after="${backend_dir}/requirements-intel-after.txt"
_intel_after_bak=""
if [ -f "${_intel_after}" ]; then
_intel_after_bak="${_intel_after}.xpu.bak"
mv "${_intel_after}" "${_intel_after_bak}"
fi
installRequirements
if [ -n "${_intel_after_bak}" ]; then
mv "${_intel_after_bak}" "${_intel_after}"
fi
# vllm's CMake build needs the Intel oneAPI dpcpp/sycl compiler — the
# base image (intel/oneapi-basekit) has it but the env isn't sourced.
if [ -f /opt/intel/oneapi/setvars.sh ]; then
set +u
source /opt/intel/oneapi/setvars.sh --force
set -u
fi
_vllm_src=$(mktemp -d)
trap 'rm -rf "${_vllm_src}"' EXIT
git clone --depth 1 https://github.com/vllm-project/vllm "${_vllm_src}/vllm"
pushd "${_vllm_src}/vllm"
# Install vllm's own runtime deps (torch-xpu, vllm_xpu_kernels,
# pydantic, fastapi, …) from upstream's requirements/xpu.txt — the
# canonical source of truth. Avoids re-pinning everything ourselves.
uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} -r requirements/xpu.txt
# Stock triton (NVIDIA-only) may have come in transitively; replace
# with triton-xpu==3.7.0 which matches torch 2.11.
uv pip uninstall triton triton-xpu 2>/dev/null || true
uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} \
--extra-index-url https://download.pytorch.org/whl/xpu \
triton-xpu==3.7.0
export CMAKE_PREFIX_PATH="$(python -c 'import site; print(site.getsitepackages()[0])'):${CMAKE_PREFIX_PATH:-}"
VLLM_TARGET_DEVICE=xpu uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps .
popd
# FROM_SOURCE=true on a CPU build skips the prebuilt vllm wheel in
# requirements-cpu-after.txt and compiles vllm locally against the host's
# actual CPU. Not used by default because it takes ~30-40 minutes, but
# kept here for hosts where the prebuilt wheel SIGILLs (CPU without the
# required SIMD baseline, e.g. AVX-512 VNNI/BF16). Default CI uses a
# bigger-runner with compatible hardware instead.
elif [ "x${BUILD_TYPE}" == "x" ] && [ "x${FROM_SOURCE:-}" == "xtrue" ]; then
# Temporarily hide the prebuilt wheel so installRequirements doesn't
# pull it — the rest of the requirements files (base deps, torch,
# transformers) are still installed normally.
_cpu_after="${backend_dir}/requirements-cpu-after.txt"
_cpu_after_bak=""
if [ -f "${_cpu_after}" ]; then
_cpu_after_bak="${_cpu_after}.from-source.bak"
mv "${_cpu_after}" "${_cpu_after_bak}"
fi
installRequirements
if [ -n "${_cpu_after_bak}" ]; then
mv "${_cpu_after_bak}" "${_cpu_after}"
fi
# Build vllm from source against the installed torch.
# https://docs.vllm.ai/en/latest/getting_started/installation/cpu/
_vllm_src=$(mktemp -d)
trap 'rm -rf "${_vllm_src}"' EXIT
git clone --depth 1 https://github.com/vllm-project/vllm "${_vllm_src}/vllm"
pushd "${_vllm_src}/vllm"
uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} wheel packaging ninja "setuptools>=49.4.0" numpy typing-extensions pillow setuptools-scm
# Respect pre-installed torch version — skip vllm's own requirements-build.txt torch pin.
VLLM_TARGET_DEVICE=cpu uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} --no-deps .
popd
else
installRequirements
fi