diff --git a/docker/Dockerfile.cuda b/docker/Dockerfile.cuda index 6c94689e6..21098db20 100644 --- a/docker/Dockerfile.cuda +++ b/docker/Dockerfile.cuda @@ -1,4 +1,4 @@ -ARG BASE_IMAGE=vllm/vllm-openai:v0.21.0 +ARG BASE_IMAGE=vllm/vllm-openai:v0.22.0 FROM ${BASE_IMAGE} ARG COMMON_WORKDIR=/app diff --git a/docker/Dockerfile.rocm b/docker/Dockerfile.rocm index ac86f7a15..5b0fa35cf 100644 --- a/docker/Dockerfile.rocm +++ b/docker/Dockerfile.rocm @@ -1,4 +1,4 @@ -ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.21.0 +ARG BASE_IMAGE=vllm/vllm-openai-rocm:v0.22.0 FROM ${BASE_IMAGE} AS base # Declare a variable to know if we want to use the nightly build or the stable build. diff --git a/docker/Dockerfile.xpu b/docker/Dockerfile.xpu index 01459e813..8d5d34f0f 100644 --- a/docker/Dockerfile.xpu +++ b/docker/Dockerfile.xpu @@ -88,7 +88,7 @@ ENV UV_EXTRA_INDEX_URL=${PIP_EXTRA_INDEX_URL} ENV UV_INDEX_STRATEGY="unsafe-best-match" ENV UV_LINK_MODE="copy" -ARG VLLM_VERSION=v0.21.0 +ARG VLLM_VERSION=v0.22.0 RUN git clone -b ${VLLM_VERSION} https://github.com/vllm-project/vllm WORKDIR /workspace/vllm diff --git a/docs/getting_started/installation/gpu.md b/docs/getting_started/installation/gpu.md index e78f3d797..b35cc69c5 100644 --- a/docs/getting_started/installation/gpu.md +++ b/docs/getting_started/installation/gpu.md @@ -34,7 +34,7 @@ vLLM-Omni is a Python library that supports the following GPU variants. The libr ### Pre-built wheels -Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, and 0.21.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source). +Note: Pre-built wheels are currently available for vLLM-Omni 0.11.0rc1, 0.12.0rc1, 0.14.0rc1, 0.14.0, 0.16.0, 0.18.0, 0.20.0, 0.21.0, and 0.22.0. If you need a newer unreleased revision, please [build from source](https://docs.vllm.ai/projects/vllm-omni/en/latest/getting_started/installation/gpu/#build-wheel-from-source). === "NVIDIA CUDA" diff --git a/docs/getting_started/installation/gpu/cuda.inc.md b/docs/getting_started/installation/gpu/cuda.inc.md index 9f3c86843..7f7607c82 100644 --- a/docs/getting_started/installation/gpu/cuda.inc.md +++ b/docs/getting_started/installation/gpu/cuda.inc.md @@ -20,7 +20,7 @@ Therefore, it is recommended to install vLLM and vLLM-Omni with a **fresh new** vLLM-Omni is built based on vLLM. Please install it with command below. ```bash -uv pip install vllm==0.21.0 --torch-backend=auto +uv pip install vllm==0.22.0 --torch-backend=auto ``` #### Installation of vLLM-Omni @@ -39,13 +39,13 @@ uv pip install 'vllm-omni[demo]' # --8<-- [start:build-wheel-from-source] #### Installation of vLLM -If you do not need to modify source code of vLLM, you can directly install the stable 0.21.0 release version of the library +If you do not need to modify source code of vLLM, you can directly install the stable 0.22.0 release version of the library ```bash -uv pip install vllm==0.21.0 --torch-backend=auto +uv pip install vllm==0.22.0 --torch-backend=auto ``` -The 0.21.0 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. +The 0.22.0 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. #### Installation of vLLM-Omni Since vllm-omni is rapidly evolving, it's recommended to install it from source @@ -66,12 +66,12 @@ If you want to check, modify or debug with source code of vLLM, install the libr ```bash git clone https://github.com/vllm-project/vllm.git cd vllm -git checkout v0.21.0 +git checkout v0.22.0 ``` 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. ```bash -#For CUDA 13.0 (the default for v0.21.0; the wheel filename has no `+cu130` suffix) -export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.21.0/vllm-0.21.0-cp38-abi3-manylinux_2_35_x86_64.whl +#For CUDA 13.0 (the default for v0.22.0; the wheel filename has no `+cu130` suffix) +export VLLM_PRECOMPILED_WHEEL_LOCATION=https://github.com/vllm-project/vllm/releases/download/v0.22.0/vllm-0.22.0-cp38-abi3-manylinux_2_35_x86_64.whl ``` Install vllm with command below (If you have no existing PyTorch). ```bash @@ -102,7 +102,7 @@ docker run --runtime nvidia --gpus 2 \ --env "HF_TOKEN=$HF_TOKEN" \ -p 8091:8091 \ --ipc=host \ - vllm/vllm-omni:v0.21.0 \ + vllm/vllm-omni:v0.22.0 \ vllm serve Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 ``` diff --git a/docs/getting_started/installation/gpu/rocm.inc.md b/docs/getting_started/installation/gpu/rocm.inc.md index f563f2f11..3912edb0e 100644 --- a/docs/getting_started/installation/gpu/rocm.inc.md +++ b/docs/getting_started/installation/gpu/rocm.inc.md @@ -13,7 +13,7 @@ vLLM-Omni current recommends the steps in under setup through Docker Images. vLLM-Omni is built based on vLLM. Please install it with command below. ```bash -uv pip install vllm==0.21.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm722 +uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm722 ``` #### Installation of vLLM-Omni @@ -34,13 +34,13 @@ uv pip install onnxruntime-rocm # --8<-- [start:build-wheel-from-source] #### Installation of vLLM -If you do not need to modify source code of vLLM, you can directly install the stable 0.21.0 release version of the library +If you do not need to modify source code of vLLM, you can directly install the stable 0.22.0 release version of the library ```bash -uv pip install vllm==0.21.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm722 +uv pip install vllm==0.22.0+rocm722 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm722 ``` -The pre-built 0.21.0 vLLM wheel targets ROCm 7.2.2. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead. +The pre-built 0.22.0 vLLM wheel targets ROCm 7.2.2. If you need a different ROCm stack or want to reuse an existing PyTorch installation, build vLLM from source instead. #### Installation of vLLM-Omni Since vllm-omni is rapidly evolving, it's recommended to install it from source @@ -58,7 +58,7 @@ If you want to check, modify or debug with source code of vLLM, install the libr ```bash git clone https://github.com/vllm-project/vllm.git cd vllm -git checkout v0.21.0 +git checkout v0.22.0 python3 -m pip install -r requirements/rocm.txt python3 setup.py develop ``` @@ -130,7 +130,7 @@ docker run --rm \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=$HF_TOKEN" \ -p 8091:8091 \ - vllm/vllm-omni-rocm:v0.21.0 \ + vllm/vllm-omni-rocm:v0.22.0 \ --model Qwen/Qwen3-Omni-30B-A3B-Instruct --omni --port 8091 ``` @@ -149,7 +149,7 @@ docker run --rm -it \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=$HF_TOKEN" \ --entrypoint bash \ - vllm/vllm-omni-rocm:v0.21.0 + vllm/vllm-omni-rocm:v0.22.0 ``` # --8<-- [end:pre-built-images] diff --git a/docs/getting_started/quickstart.md b/docs/getting_started/quickstart.md index 10665f2c2..4e3021f92 100644 --- a/docs/getting_started/quickstart.md +++ b/docs/getting_started/quickstart.md @@ -19,10 +19,10 @@ uv venv --python 3.12 --seed source .venv/bin/activate # On CUDA -uv pip install vllm==0.21.0 --torch-backend=auto +uv pip install vllm==0.22.0 --torch-backend=auto # On ROCm -uv pip install vllm==0.21.0+rocm721 --extra-index-url https://wheels.vllm.ai/rocm/0.21.0/rocm721 +uv pip install vllm==0.22.0+rocm721 --extra-index-url https://wheels.vllm.ai/rocm/0.22.0/rocm721 git clone https://github.com/vllm-project/vllm-omni.git cd vllm-omni @@ -35,7 +35,7 @@ For additional installation methods — please see the [installation guide](inst !!! note It is important to install the same major & minor version of vLLM and vLLM Omni, otherwise things may not work as expected. If the versions are misaligned, you will see a warning when you import vLLM Omni. - If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.21.0` and vLLM Omni `0.21.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue. + If you are seeing strange behavior with the `vllm` command not handling the `--omni` flag correctly, you most likely have a version mismatch with vLLM < `0.22.0` and vLLM Omni `0.22.0`, as vLLM Omni no longer hijacks the vLLM entrypoint. Updating vLLM should resolve this issue. ## Offline Inference