Files
LocalAI/backend/python/sglang/install.sh
LocalAI [bot] 5cda4f1ccf fix(L4T13 backends): switch vllm/sglang/vllm-omni to PyPI aarch64+cu130 wheels (#9950)
* fix(vllm): switch L4T13 backend to PyPI aarch64+cu130 wheels

The L4T13 vllm backend pulled torch / torchvision / torchaudio / vllm from
pypi.jetson-ai-lab.io's sbsa/cu130 mirror via [tool.uv.sources] with no
version pins. That mirror started shipping torch 2.11.0 next to a
vllm-0.20.0+cu130 wheel that was still compiled against torch 2.10's c10
ABI, so uv landed on the mismatched pair and vllm crashed at import:

  ImportError: vllm/_C.abi3.so: undefined symbol:
  _ZN3c1013MessageLoggerC1EPKciib

(c10::MessageLogger's constructor signature changed between torch 2.10 and
2.11; the vllm wheel referenced the 2.10 form, the installed libc10.so
exported only the 2.11 form.)

Since torch 2.11 (April 2026) PyPI publishes its own aarch64 + cu130
manylinux wheels, and vllm 0.20.0 ships an aarch64 wheel whose Requires-
Dist locks torch==2.11.0 / torchvision==0.26.0 / torchaudio==2.11.0. That
makes uv's resolver produce an ABI-consistent set automatically, so the
mirror and the [tool.uv.sources] pinning are no longer needed.

flash-attn is dropped from the dep list: PyPI has no aarch64 wheel, but
vLLM 0.20+ already bundles its own vllm_flash_attn (fa2 + fa3) inside the
main wheel, so the Dao-AILab package isn't required at runtime.

Reference: https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] [WebFetch]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* 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>

* fix(sglang,vllm-omni): switch L4T13 backends to PyPI aarch64+cu130 wheels

Same root cause and same fix as the vllm backend in the previous commits:
the L4T13 sglang and vllm-omni backends both pulled their accelerator
stack from pypi.jetson-ai-lab.io's sbsa/cu130 mirror with no version
pins, so they would silently land on the same torch 2.11 vs cu130-built
wheel ABI mismatch the moment the mirror published an out-of-sync pair.

sglang
------

- Drop pyproject.toml + [tool.uv.sources]. The historical comment said
  the [all] extra was unsafe on aarch64 because of decord, but sglang
  0.5.x now uses `decord2` on aarch64/arm/armv7l (which ships cp312
  aarch64 wheels), so we can match cublas13's sglang[all]>=0.5.11 pin
  and stop being capped at the 0.5.1.post2 the L4T mirror shipped.
  That unblocks Gemma 4 / MTP recipes on Jetson Thor.
- New requirements-l4t13.txt mirrors the cublas13 split (accelerate /
  torch / torchvision / torchaudio / transformers), requirements-l4t13-
  after.txt carries sglang[all]>=0.5.11.
- install.sh's l4t13 elif branch goes away; falls through to the
  standard installRequirements path.

vllm-omni
---------

- requirements-l4t13.txt drops --extra-index-url to jetson-ai-lab and
  drops flash-attn (PyPI has no aarch64 wheel, vLLM 0.20+ bundles its
  own vllm_flash_attn fa2 + fa3 internally).
- install.sh's l4t13 vllm-install branch collapses into the cublas13
  branch since both now just run `pip install vllm --torch-backend=auto`
  against PyPI.
- --index-strategy=unsafe-best-match is dropped from the top-level
  l4t13 guard; without the L4T mirror in the picture it had no purpose.

The from-source vllm-omni install on top still keeps its existing
`sed -i '/^fa3-fwd[[:space:]]*==/d' requirements/cuda.txt` workaround -
fa3-fwd has no aarch64 wheel and no sdist, unrelated to flash-attn.

Reference: https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash] [WebFetch]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* fix(sglang): drop [all] extra on l4t13 - xatlas has no aarch64 wheel

CI revealed that sglang[all]==0.5.12 transitively pulls xatlas via the
[diffusion] sub-extra, and xatlas ships no aarch64 wheel. Its sdist
depends on scikit_build_core without declaring it in build-system.
requires, so under --no-build-isolation uv can't build it from source:

    × Failed to build `xatlas==0.0.11`
    ├─▶ The build backend returned an error
    ╰─▶ Call to `scikit_build_core.build.build_wheel` failed (exit status: 1)
        ModuleNotFoundError: No module named 'scikit_build_core'
    help: `xatlas` (v0.0.11) was included because `sglang[all]` (v0.5.12)
          depends on `xatlas`

Upstream sglang explicitly gates st_attn and vsa on
`platform_machine != aarch64` inside the same [diffusion] extra but
forgot xatlas - same class of bug that bit the old decord pin.

Use plain `sglang>=0.5.11` on l4t13. backend.py imports only base
sglang.srt symbols (Engine, ServerArgs, FunctionCallParser,
ReasoningParser); the [all] extras are optional accelerators not
required at import time. cublas13 (x86_64) keeps [all] because xatlas
has x86_64 wheels there.

Assisted-by: Claude:claude-opus-4-7 [Read] [Edit] [Write] [Bash]
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-05-22 23:01:22 +02:00

112 lines
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Executable File

#!/bin/bash
set -e
EXTRA_PIP_INSTALL_FLAGS="--no-build-isolation"
# Avoid overcommitting the CPU during builds that compile native code.
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 $backend_dir/../common/libbackend.sh
fi
if [ "x${BUILD_PROFILE}" == "xintel" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --upgrade --index-strategy=unsafe-first-match"
fi
if [ "x${BUILD_PROFILE}" == "xcpu" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
fi
# cublas12 needs a cu128 torch index (see requirements-cublas12.txt) — without
# unsafe-best-match uv falls through to default PyPI's cu130 torch wheel and
# the resulting sgl-kernel can't load on our cu12 host libs.
if [ "x${BUILD_PROFILE}" == "xcublas12" ]; then
EXTRA_PIP_INSTALL_FLAGS+=" --index-strategy=unsafe-best-match"
fi
# sglang 0.5.11 (Gemma 4 support) declares flash-attn-4 as a hard dep, but
# upstream only publishes pre-release wheels (4.0.0b*). uv rejects
# pre-releases by default — opt in for sglang specifically. Drop this once
# flash-attn-4 4.0 stable lands.
EXTRA_PIP_INSTALL_FLAGS+=" --prerelease=allow"
# JetPack 7 / L4T arm64 sglang + torch wheels come straight from PyPI now
# (torch 2.11+ ships aarch64 + cu130 manylinux wheels and sglang 0.5.11+
# ships a cp312 aarch64 wheel pinned to that torch). They're cp312-only,
# so bump the venv Python accordingly.
# https://pytorch.org/blog/vllm-and-pytorch-work-together-to-improve-the-developer-experience-on-aarch64/
if [ "x${BUILD_PROFILE}" == "xl4t13" ]; then
PYTHON_VERSION="3.12"
PYTHON_PATCH="12"
PY_STANDALONE_TAG="20251120"
fi
# sglang's CPU path has no prebuilt wheel on PyPI — upstream publishes
# a separate pyproject_cpu.toml that must be swapped in before `pip install`.
# Reference: docker/xeon.Dockerfile in the sglang upstream repo.
#
# When BUILD_TYPE is empty (CPU profile) or FROM_SOURCE=true is forced,
# install torch/transformers/etc from requirements-cpu.txt, then clone
# sglang and install its python/ and sgl-kernel/ packages from source
# using the CPU pyproject.
if [ "x${BUILD_TYPE}" == "x" ] || [ "x${FROM_SOURCE:-}" == "xtrue" ]; then
# sgl-kernel's CPU build links against libnuma and libtbb. Install
# them here (Docker builder stage) before running the source build.
# Harmless no-op on runs outside the docker build since installRequirements
# below still needs them only if we reach the source build branch.
if command -v apt-get >/dev/null 2>&1 && [ "$(id -u)" = "0" ]; then
apt-get update
DEBIAN_FRONTEND=noninteractive apt-get install -y --no-install-recommends \
libnuma-dev numactl libtbb-dev libgomp1 libomp-dev google-perftools \
build-essential cmake ninja-build
fi
installRequirements
# sgl-kernel's pyproject_cpu.toml uses scikit-build-core as its build
# backend. With --no-build-isolation, that (and ninja/cmake) must be
# present in the venv before we build from source.
uv pip install --no-build-isolation "scikit-build-core>=0.10" ninja cmake
# sgl-kernel's CPU shm.cpp uses __m512 AVX-512 intrinsics unconditionally.
# csrc/cpu/CMakeLists.txt hard-codes add_compile_options(-march=native),
# which on runners without AVX-512 in /proc/cpuinfo fails with
# "__m512 return without 'avx512f' enabled changes the ABI".
# CXXFLAGS alone is insufficient because CMake's add_compile_options()
# appends -march=native *after* CXXFLAGS, overriding it.
# We therefore patch the CMakeLists.txt to replace -march=native with
# -march=sapphirerapids so the flag is consistent throughout the build.
# The resulting binary still requires an AVX-512 capable CPU at runtime,
# same constraint sglang upstream documents in docker/xeon.Dockerfile.
_sgl_src=$(mktemp -d)
trap 'rm -rf "${_sgl_src}"' EXIT
git clone --depth 1 https://github.com/sgl-project/sglang "${_sgl_src}/sglang"
# Patch -march=native → -march=sapphirerapids in the CPU kernel CMakeLists
sed -i 's/-march=native/-march=sapphirerapids/g' \
"${_sgl_src}/sglang/sgl-kernel/csrc/cpu/CMakeLists.txt"
pushd "${_sgl_src}/sglang/sgl-kernel"
if [ -f pyproject_cpu.toml ]; then
cp pyproject_cpu.toml pyproject.toml
fi
uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} .
popd
pushd "${_sgl_src}/sglang/python"
if [ -f pyproject_cpu.toml ]; then
cp pyproject_cpu.toml pyproject.toml
fi
uv pip install ${EXTRA_PIP_INSTALL_FLAGS:-} .
popd
else
installRequirements
fi