[Rebase] Rebase to vLLM 0.30.0 (#7820)
Signed-off-by: tzhouam <tzhouam@connect.ust.hk> Signed-off-by: Gao Han <hgaoaf@connect.ust.hk> Co-authored-by: Claude Opus 5 (1M context) <noreply@anthropic.com> Co-authored-by: Gao Han <hgaoaf@connect.ust.hk>
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@@ -5,7 +5,7 @@
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# --8<-- [end:requirements]
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# --8<-- [start:set-up-using-python]
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vLLM-Omni depends on the matching major/minor release of vLLM. The 0.29 development line uses vLLM 0.29.x. Published 0.28.0 wheels and images use vLLM 0.28.x.
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vLLM-Omni depends on the matching major/minor release of vLLM. The 0.30 development line uses vLLM 0.30.x. Published 0.28.0 wheels and images use vLLM 0.28.x.
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!!! note
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PyTorch installed via `conda` will statically link `NCCL` library, which can cause issues when vLLM tries to use `NCCL`. See <gh-issue:8420> for more details.
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@@ -18,7 +18,7 @@ Therefore, it is recommended to install vLLM and vLLM-Omni with a **fresh new**
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#### Installation of vLLM
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These pre-built wheel instructions install the published vLLM-Omni 0.28.0 release. For the 0.29 development line, use the source-install instructions below.
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These pre-built wheel instructions install the published vLLM-Omni 0.28.0 release. For the 0.30 development line, use the source-install instructions below.
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vLLM-Omni is built based on vLLM. Please install it with command below.
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```bash
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@@ -41,13 +41,13 @@ uv pip install 'vllm-omni[demo]==0.28.0'
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# --8<-- [start:build-wheel-from-source]
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.29.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.30.0 release version of the library
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```bash
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uv pip install vllm==0.29.0 --torch-backend=auto
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uv pip install vllm==0.30.0 --torch-backend=auto
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```
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The 0.29.0 release of vLLM ships CUDA 13.0-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead.
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The 0.30.0 release of vLLM ships CUDA 13.0-compatible binaries by default. If you need a different CUDA variant or want to reuse an existing PyTorch installation, build vLLM from source instead.
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#### Installation of vLLM-Omni
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Since vllm-omni is rapidly evolving, it's recommended to install it from source
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@@ -68,12 +68,12 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.29.0
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git checkout v0.30.0
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```
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Set up environment variables to get pre-built wheels. If there are internet problems, just download the whl file manually. And set `VLLM_PRECOMPILED_WHEEL_LOCATION` as your local absolute path of whl file.
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```bash
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#For CUDA 13.0 (the default for v0.29.0; the wheel filename has no `+cu130` suffix)
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.29.0/vllm-0.29.0-cp38-abi3-manylinux_2_28_x86_64.whl
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#For CUDA 13.0 (the default for v0.30.0; the wheel filename has no `+cu130` suffix)
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export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.30.0/vllm-0.30.0-cp38-abi3-manylinux_2_28_x86_64.whl
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```
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Install vllm with command below (If you have no existing PyTorch).
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```bash
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@@ -133,7 +133,7 @@ If you want to specify the base vLLM version:
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```bash
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DOCKER_BUILDKIT=1 docker build \
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-f docker/Dockerfile.cuda \
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--build-arg BASE_IMAGE=vllm/vllm-openai:v0.29.0 \
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--build-arg BASE_IMAGE=vllm/vllm-openai:v0.30.0 \
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-t vllm-omni-cuda .
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```
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@@ -10,8 +10,8 @@
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For ROCm, vLLM-Omni currently recommends the setup steps through Docker Images.
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vLLM-Omni depends on the matching major/minor release of vLLM. The 0.29
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development line uses vLLM 0.29.x. Published 0.28.0 wheels and images use vLLM
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vLLM-Omni depends on the matching major/minor release of vLLM. The 0.30
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development line uses vLLM 0.30.x. Published 0.28.0 wheels and images use vLLM
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0.28.x.
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The Dockerfile's `BASE_IMAGE` pin applies only to Docker builds. The
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@@ -23,7 +23,7 @@ installing vLLM-Omni, as shown below.
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#### Installation of vLLM
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These pre-built wheel instructions install the published vLLM-Omni 0.28.0 release. For the 0.29 development line, use the source-install instructions below.
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These pre-built wheel instructions install the published vLLM-Omni 0.28.0 release. For the 0.30 development line, use the source-install instructions below.
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vLLM-Omni is built based on vLLM. Please install it with command below.
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@@ -50,13 +50,13 @@ uv pip install onnxruntime-rocm
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#### Installation of vLLM
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If you do not need to modify source code of vLLM, you can directly install the stable 0.29.0 release version of the library
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If you do not need to modify source code of vLLM, you can directly install the stable 0.30.0 release version of the library
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```bash
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uv pip install vllm==0.29.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.29.0/rocm723
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uv pip install vllm==0.30.0+rocm723 --extra-index-url https://wheels.vllm.ai/rocm/0.30.0/rocm723
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```
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The pre-built 0.29.0 vLLM wheel targets ROCm 7.2.3. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead.
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The pre-built 0.30.0 vLLM wheel targets ROCm 7.2.3. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead.
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#### Installation of vLLM-Omni
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@@ -76,7 +76,7 @@ If you want to check, modify or debug with source code of vLLM, install the libr
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```bash
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git clone https://github.com/vllm-project/vllm.git
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cd vllm
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git checkout v0.29.0
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git checkout v0.30.0
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python3 -m pip install -r requirements/rocm.txt
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python3 setup.py develop
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```
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@@ -88,7 +88,7 @@ python3 setup.py develop
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#### Build docker image
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The source build defaults to the published upstream base image
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`vllm/vllm-openai-rocm:v0.29.0`, aligned with the vLLM release used by CI.
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`vllm/vllm-openai-rocm:v0.30.0`, aligned with the vLLM release used by CI.
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Older or custom bases must provide the vLLM APIs checked by the Dockerfile's
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image-build canary. This upstream base is distinct from the prebuilt
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`vllm/vllm-omni-rocm` images discussed below; their published-tag availability
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@@ -103,7 +103,7 @@ To select the upstream ROCm base explicitly, pass `BASE_IMAGE`:
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```bash
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DOCKER_BUILDKIT=1 docker build \
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-f docker/Dockerfile.rocm \
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--build-arg BASE_IMAGE=vllm/vllm-openai-rocm:v0.29.0 \
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--build-arg BASE_IMAGE=vllm/vllm-openai-rocm:v0.30.0 \
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-t vllm-omni-rocm .
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```
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@@ -24,7 +24,7 @@ DOCKER_BUILDKIT=1 docker build -f docker/Dockerfile.xpu -t vllm-omni-xpu --shm-s
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```
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This layers vLLM-Omni on top of the published `vllm/vllm-openai-xpu:<VLLM_VERSION>`
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base image, which Docker pulls automatically. To target a different vLLM release,
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base image (v0.30.0 by default), which Docker pulls automatically. To target a different vLLM release,
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pass `--build-arg VLLM_VERSION=<tag>`. If that tag has not been published yet, build
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the base from upstream's own Dockerfile first and point the build at it:
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