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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>
137 lines
6.1 KiB
Bash
Executable File
137 lines
6.1 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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# 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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# 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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if [ "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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