update README

docs/vllm_deploy_guide.md

@@ -32,12 +32,12 @@ The following are recommended configurations; actual requirements should be adju
 
 It is recommended to use a virtual environment (such as **venv**, **conda**, or **uv**) to avoid dependency conflicts. 
 
-We recommend installing vLLM in a fresh Python environment. Since it has not been released yet, you need to manually build it from the source code:
+We recommend installing vLLM in a fresh Python environment:
 
 ```bash
-git clone https://github.com/vllm-project/vllm.git
-cd vllm
-uv pip install . --torch-backend=auto
+uv venv
+source .venv/bin/activate
+uv pip install vllm --extra-index-url https://wheels.vllm.ai/nightly
 ```
 
 Run the following command to start the vLLM server. vLLM will automatically download and cache the MiniMax-M2 model from Hugging Face.

docs/vllm_deploy_guide_cn.md

@@ -32,11 +32,11 @@
 
 建议使用虚拟环境（如 **venv**、**conda**、**uv**）以避免依赖冲突。
 
-建议在全新的 Python 环境中安装 vLLM。由于尚未 release，需要从源码手动编译：
+建议在全新的 Python 环境中安装 vLLM：
 ```bash
-git clone https://github.com/vllm-project/vllm.git
-cd vllm
-uv pip install . --torch-backend=auto
+uv venv
+source .venv/bin/activate
+uv pip install vllm --extra-index-url https://wheels.vllm.ai/nightly
 ```
 
 运行如下命令启动 vLLM 服务器，vLLM 会自动从 Huggingface 下载并缓存 MiniMax-M2 模型。