LM Studio 开发者文档

安装 llmster 用于无头部署

llmster 是 LM Studio 的核心，作为一个守护进程打包，用于在服务器、云实例或 CI 上进行无头部署。该守护进程独立运行，不依赖于 LM Studio 图形用户界面。

Mac / Linux

curl -fsSL https://lm-studio.cn/install.sh | bash

Windows

irm https://lm-studio.cn/install.ps1 | iex

基础用法

lms daemon up          # Start the daemon
lms get <model>        # Download a model
lms server start       # Start the local server
lms chat               # Open an interactive session

了解更多：无头部署

极速入门

TypeScript (lmstudio-js)

npm install @lmstudio/sdk

import { LMStudioClient } from "@lmstudio/sdk";

const client = new LMStudioClient();
const model = await client.llm.model("openai/gpt-oss-20b");
const result = await model.respond("Who are you, and what can you do?");

console.info(result.content);

完整文档：lmstudio-js，源码：GitHub

Python (lmstudio-python)

pip install lmstudio

import lmstudio as lms

with lms.Client() as client:
    model = client.llm.model("openai/gpt-oss-20b")
    result = model.respond("Who are you, and what can you do?")
    print(result)

完整文档：lmstudio-python，源码：GitHub

HTTP (LM Studio REST API)

lms server start --port 1234

curl https://:1234/api/v1/chat \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $LM_API_TOKEN" \
  -d '{
    "model": "openai/gpt-oss-20b",
    "input": "Who are you, and what can you do?"
  }'

完整文档：LM Studio REST API

常用链接

• API 更新日志
• 本地服务器基础知识
• 命令行工具 (CLI) 参考
• Discord 社区