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Jul 9, 2025
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chore: bump v0.4.9.post1 #7882

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2 changes: 1 addition & 1 deletion benchmark/deepseek_v3/README.md
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Expand Up @@ -33,7 +33,7 @@ Add [performance optimization options](#performance-optimization-options) as nee

```bash
# Installation
pip install "sglang[all]>=0.4.9"
pip install "sglang[all]>=0.4.9.post1"

# Launch
python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code
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2 changes: 1 addition & 1 deletion docker/Dockerfile.rocm
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@@ -1,5 +1,5 @@
# Usage (to build SGLang ROCm docker image):
# docker build --build-arg SGL_BRANCH=v0.4.9 -t v0.4.9-rocm630 -f Dockerfile.rocm .
# docker build --build-arg SGL_BRANCH=v0.4.9.post1 -t v0.4.9.post1-rocm630 -f Dockerfile.rocm .

# default base image
ARG BASE_IMAGE="rocm/sgl-dev:vllm20250114"
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4 changes: 2 additions & 2 deletions docs/references/setup_github_runner.md
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Expand Up @@ -11,9 +11,9 @@ docker pull nvidia/cuda:12.1.1-devel-ubuntu22.04
# Nvidia
docker run --shm-size 128g -it -v /tmp/huggingface:/hf_home --gpus all nvidia/cuda:12.1.1-devel-ubuntu22.04 /bin/bash
# AMD
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.9-rocm630 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.9.post1-rocm630 /bin/bash
# AMD just the last 2 GPUs
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.9-rocm630 /bin/bash
docker run --rm --device=/dev/kfd --device=/dev/dri/renderD176 --device=/dev/dri/renderD184 --group-add video --shm-size 128g -it -v /tmp/huggingface:/hf_home lmsysorg/sglang:v0.4.9.post1-rocm630 /bin/bash
```

### Step 2: Configure the runner by `config.sh`
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12 changes: 6 additions & 6 deletions docs/start/install.md
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Expand Up @@ -11,7 +11,7 @@ It is recommended to use uv to install the dependencies for faster installation:
```bash
pip install --upgrade pip
pip install uv
uv pip install "sglang[all]>=0.4.9"
uv pip install "sglang[all]>=0.4.9.post1"
```

**Quick Fixes to Common Problems**
Expand All @@ -27,7 +27,7 @@ uv pip install "sglang[all]>=0.4.9"

```bash
# Use the last release branch
git clone -b v0.4.9 https://github.com/sgl-project/sglang.git
git clone -b v0.4.9.post1 https://github.com/sgl-project/sglang.git
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@gemini-code-assist gemini-code-assist bot Jul 9, 2025

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medium

The comment on the preceding line, # Use the last release branch, could be misleading. After the release is complete, v0.4.9.post1 will be a tag, not a branch. To prevent user confusion, update the comment to reflect the state of the repository after a release.

Suggested change
git clone -b v0.4.9.post1 https://github.com/sgl-project/sglang.git
# Use the last release tag

cd sglang

pip install --upgrade pip
Expand All @@ -42,7 +42,7 @@ Note: For AMD ROCm system with Instinct/MI GPUs, do following instead:

```bash
# Use the last release branch
git clone -b v0.4.9 https://github.com/sgl-project/sglang.git
git clone -b v0.4.9.post1 https://github.com/sgl-project/sglang.git
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@gemini-code-assist gemini-code-assist bot Jul 9, 2025

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medium

The comment # Use the last release branch is misleading because the release process converts this into a tag. Update it for clarity and consistency.

Suggested change
git clone -b v0.4.9.post1 https://github.com/sgl-project/sglang.git
# Use the last release tag

cd sglang

pip install --upgrade pip
Expand Down Expand Up @@ -71,7 +71,7 @@ docker run --gpus all \
Note: For AMD ROCm system with Instinct/MI GPUs, it is recommended to use `docker/Dockerfile.rocm` to build images, example and usage as below:

```bash
docker build --build-arg SGL_BRANCH=v0.4.9 -t v0.4.9-rocm630 -f Dockerfile.rocm .
docker build --build-arg SGL_BRANCH=v0.4.9.post1 -t v0.4.9.post1-rocm630 -f Dockerfile.rocm .

alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/dri --ipc=host \
--shm-size 16G --group-add video --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
Expand All @@ -80,11 +80,11 @@ alias drun='docker run -it --rm --network=host --device=/dev/kfd --device=/dev/d
drun -p 30000:30000 \
-v ~/.cache/huggingface:/root/.cache/huggingface \
--env "HF_TOKEN=<secret>" \
v0.4.9-rocm630 \
v0.4.9.post1-rocm630 \
python3 -m sglang.launch_server --model-path meta-llama/Llama-3.1-8B-Instruct --host 0.0.0.0 --port 30000

# Till flashinfer backend available, --attention-backend triton --sampling-backend pytorch are set by default
drun v0.4.9-rocm630 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
drun v0.4.9.post1-rocm630 python3 -m sglang.bench_one_batch --batch-size 32 --input 1024 --output 128 --model amd/Meta-Llama-3.1-8B-Instruct-FP8-KV --tp 8 --quantization fp8
```

## Method 4: Using docker compose
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2 changes: 1 addition & 1 deletion python/pyproject.toml
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Expand Up @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"

[project]
name = "sglang"
version = "0.4.9"
version = "0.4.9.post1"
description = "SGLang is yet another fast serving framework for large language models and vision language models."
readme = "README.md"
requires-python = ">=3.8"
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2 changes: 1 addition & 1 deletion python/sglang/version.py
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@@ -1 +1 @@
__version__ = "0.4.9"
__version__ = "0.4.9.post1"
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