Release 0.4.1.post3 - upload the config.json to PyPI (#2647)

benchmark/deepseek_v3/README.md

-# SGLang v0.4.1 - DeepSeek V3 Support
+# DeepSeek V3 Support
 
-We're excited to announce [SGLang v0.4.1](https://github.com/sgl-project/sglang/releases/tag/v0.4.1), which now supports [DeepSeek V3](https://huggingface.co/deepseek-ai/DeepSeek-V3-Base) - currently the strongest open-source LLM, even surpassing GPT-4o.
-
-The SGLang and DeepSeek teams worked together to get DeepSeek V3 FP8 running on NVIDIA and AMD GPU **from day one**. We've also supported MLA optimization and DP attention before, making SGLang one of the best open-source LLM engines for running DeepSeek models.
+The SGLang and DeepSeek teams worked together to get DeepSeek V3 FP8 running on NVIDIA and AMD GPUs **from day one**. SGLang also has supported [MLA optimization](https://lmsys.org/blog/2024-09-04-sglang-v0-3/#deepseek-multi-head-latent-attention-mla-throughput-optimizations) and [DP attention](https://lmsys.org/blog/2024-12-04-sglang-v0-4/#data-parallelism-attention-for-deepseek-models), making SGLang one of the best open-source LLM engines for running DeepSeek models.
 
 Special thanks to Meituan's Search & Recommend Platform Team and Baseten's Model Performance Team for implementing the model, and DataCrunch for providing GPU resources.
 
@@ -20,17 +18,20 @@ If you encounter errors when starting the server, ensure the weights have finish
 docker run --gpus all --shm-size 32g -p 30000:30000 -v ~/.cache/huggingface:/root/.cache/huggingface --ipc=host lmsysorg/sglang:latest \
     python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code --port 30000
 ```
+
 For high QPS scenarios, add the `--enable-dp-attention` argument to boost throughput.
 
 ### Using pip
 ```bash
 # Installation
-pip install "sglang[all]==0.4.1.post2" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer
+pip install "sglang[all]>=0.4.1.post3" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer
 
 # Launch
 python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3 --tp 8 --trust-remote-code
 ```
 
+For high QPS scenarios, add the `--enable-dp-attention` argument to boost throughput.
+
 ### Example with OpenAI API
 
 ```python3

docker/Dockerfile.rocm

 # Usage (to build SGLang ROCm docker image):
-#   docker build --build-arg SGL_BRANCH=v0.4.1.post2 -t v0.4.1.post2-rocm620 -f Dockerfile.rocm .
+#   docker build --build-arg SGL_BRANCH=v0.4.1.post3 -t v0.4.1.post3-rocm620 -f Dockerfile.rocm .
 
 # default base image
 ARG BASE_IMAGE="rocm/vllm-dev:20241022"

docs/developer/setup_github_runner.md

@@ -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:v0.4.1.post2-rocm620 /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:v0.4.1.post3-rocm620 /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:v0.4.1.post2-rocm620 /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:v0.4.1.post3-rocm620 /bin/bash
 ```
 
 ### Step 2: Configure the runner by `config.sh`

docs/start/install.md

@@ -13,7 +13,7 @@ Note: Please check the [FlashInfer installation doc](https://docs.flashinfer.ai/
 ## Method 2: From source
 ```
 # Use the last release branch
-git clone -b v0.4.1.post2 https://github.com/sgl-project/sglang.git
+git clone -b v0.4.1.post3 https://github.com/sgl-project/sglang.git
 cd sglang
 
 pip install --upgrade pip
@@ -26,7 +26,7 @@ Note: To AMD ROCm system with Instinct/MI GPUs, do following instead:
 
 ```
 # Use the last release branch
-git clone -b v0.4.1.post2 https://github.com/sgl-project/sglang.git
+git clone -b v0.4.1.post3 https://github.com/sgl-project/sglang.git
 cd sglang
 
 pip install --upgrade pip
@@ -51,7 +51,7 @@ docker run --gpus all \
 Note: To 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=v0.4.1.post2 -t v0.4.1.post2-rocm620 -f Dockerfile.rocm .
+docker build --build-arg SGL_BRANCH=v0.4.1.post3 -t v0.4.1.post3-rocm620 -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 \
@@ -60,11 +60,11 @@ 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>" \
-    v0.4.1.post2-rocm620 \
+    v0.4.1.post3-rocm620 \
     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 v0.4.1.post2-rocm620 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 v0.4.1.post3-rocm620 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

python/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sglang"
-version = "0.4.1.post2"
+version = "0.4.1.post3"
 description = "SGLang is yet another fast serving framework for large language models and vision language models."
 readme = "README.md"
 requires-python = ">=3.8"
@@ -61,7 +61,7 @@ dev_hpu = ["sglang[all_hpu]", "sglang[test]"]
 "Bug Tracker" = "https://github.com/sgl-project/sglang/issues"
 
 [tool.setuptools.package-data]
-"sglang" = ["srt/layers/fused_moe_triton/configs/*.json"]
+"sglang" = ["srt/layers/moe/fused_moe_triton/configs/*.json", "srt/layers/quantization/configs/*.json"]
 
 [tool.setuptools.packages.find]
 exclude = [

python/sglang/version.py

-__version__ = "0.4.1.post2"
+__version__ = "0.4.1.post3"