[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>

docs/getting_started/installation/gpu/cuda.inc.md

@@ -5,7 +5,7 @@
 # --8<-- [end:requirements]
 # --8<-- [start:set-up-using-python]
 
-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.
+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.
 
 !!! note
     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.
@@ -18,7 +18,7 @@ Therefore, it is recommended to install vLLM and vLLM-Omni with a **fresh new**
 
 #### Installation of vLLM
 
-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.
+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.
 
 vLLM-Omni is built based on vLLM. Please install it with command below.
 ```bash
@@ -41,13 +41,13 @@ uv pip install 'vllm-omni[demo]==0.28.0'
 # --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 0.29.0 release version of the library
+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
 
 ```bash
-uv pip install vllm==0.29.0 --torch-backend=auto
+uv pip install vllm==0.30.0 --torch-backend=auto
 ```
 
-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.
+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.
 
 #### Installation of vLLM-Omni
 Since vllm-omni is rapidly evolving, it's recommended to install it from source
@@ -68,12 +68,12 @@ 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 v0.29.0
+git checkout v0.30.0
 ```
 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 v0.29.0; the wheel filename has no `+cu130` suffix)
-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
+#For CUDA 13.0 (the default for v0.30.0; the wheel filename has no `+cu130` suffix)
+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
 ```
 Install vllm with command below (If you have no existing PyTorch).
 ```bash
@@ -133,7 +133,7 @@ If you want to specify the base vLLM version:
 ```bash
 DOCKER_BUILDKIT=1 docker build \
   -f docker/Dockerfile.cuda \
-  --build-arg BASE_IMAGE=vllm/vllm-openai:v0.29.0 \
+  --build-arg BASE_IMAGE=vllm/vllm-openai:v0.30.0 \
   -t vllm-omni-cuda .
 ```