API

LM Studio REST API (beta)

实验性

需要 LM Studio 0.3.6 或更高版本。仍在开发中，端点可能会更改。

LM Studio 现在除了 OpenAI 兼容模式（了解更多）外，还拥有自己的 REST API。

REST API 包括增强的统计数据，如每秒Token数 (Token / Second) 和首次Token生成时间 (Time To First Token, TTFT)，以及关于模型的丰富信息，如已加载与未加载、最大上下文、量化等。

支持的 API 端点

• GET /api/v0/models - 列出可用模型
• GET /api/v0/models/{model} - 获取特定模型的信息
• POST /api/v0/chat/completions - 聊天补全（消息 → 助手回复）
• POST /api/v0/completions - 文本补全（提示 → 补全）
• POST /api/v0/embeddings - 文本嵌入（文本 → 嵌入）

🚧 我们正在开发此接口。请通过 Github 或 电子邮件 告知我们您认为重要的内容。

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启动 REST API 服务器

要启动服务器，请运行以下命令

lms server start

端点

GET /api/v0/models

列出所有已加载和已下载的模型

示例请求

curl https://:1234/api/v0/models

响应格式

{
  "object": "list",
  "data": [
    {
      "id": "qwen2-vl-7b-instruct",
      "object": "model",
      "type": "vlm",
      "publisher": "mlx-community",
      "arch": "qwen2_vl",
      "compatibility_type": "mlx",
      "quantization": "4bit",
      "state": "not-loaded",
      "max_context_length": 32768
    },
    {
      "id": "meta-llama-3.1-8b-instruct",
      "object": "model",
      "type": "llm",
      "publisher": "lmstudio-community",
      "arch": "llama",
      "compatibility_type": "gguf",
      "quantization": "Q4_K_M",
      "state": "not-loaded",
      "max_context_length": 131072
    },
    {
      "id": "text-embedding-nomic-embed-text-v1.5",
      "object": "model",
      "type": "embeddings",
      "publisher": "nomic-ai",
      "arch": "nomic-bert",
      "compatibility_type": "gguf",
      "quantization": "Q4_0",
      "state": "not-loaded",
      "max_context_length": 2048
    }
  ]
}

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GET /api/v0/models/{model}

获取有关特定模型的信息

示例请求

curl https://:1234/api/v0/models/qwen2-vl-7b-instruct

响应格式

{
  "id": "qwen2-vl-7b-instruct",
  "object": "model",
  "type": "vlm",
  "publisher": "mlx-community",
  "arch": "qwen2_vl",
  "compatibility_type": "mlx",
  "quantization": "4bit",
  "state": "not-loaded",
  "max_context_length": 32768
}

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POST /api/v0/chat/completions

聊天补全 API。您提供一个消息数组，并接收聊天中的下一个助手回复。

示例请求

curl https://:1234/api/v0/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "granite-3.0-2b-instruct",
    "messages": [
      { "role": "system", "content": "Always answer in rhymes." },
      { "role": "user", "content": "Introduce yourself." }
    ],
    "temperature": 0.7,
    "max_tokens": -1,
    "stream": false
  }'

响应格式

{
  "id": "chatcmpl-i3gkjwthhw96whukek9tz",
  "object": "chat.completion",
  "created": 1731990317,
  "model": "granite-3.0-2b-instruct",
  "choices": [
    {
      "index": 0,
      "logprobs": null,
      "finish_reason": "stop",
      "message": {
        "role": "assistant",
        "content": "Greetings, I'm a helpful AI, here to assist,\nIn providing answers, with no distress.\nI'll keep it short and sweet, in rhyme you'll find,\nA friendly companion, all day long you'll bind."
      }
    }
  ],
  "usage": {
    "prompt_tokens": 24,
    "completion_tokens": 53,
    "total_tokens": 77
  },
  "stats": {
    "tokens_per_second": 51.43709529007664,
    "time_to_first_token": 0.111,
    "generation_time": 0.954,
    "stop_reason": "eosFound"
  },
  "model_info": {
    "arch": "granite",
    "quant": "Q4_K_M",
    "format": "gguf",
    "context_length": 4096
  },
  "runtime": {
    "name": "llama.cpp-mac-arm64-apple-metal-advsimd",
    "version": "1.3.0",
    "supported_formats": ["gguf"]
  }
}

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POST /api/v0/completions

文本补全 API。您提供一个提示并接收一个补全。

示例请求

curl https://:1234/api/v0/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "granite-3.0-2b-instruct",
    "prompt": "the meaning of life is",
    "temperature": 0.7,
    "max_tokens": 10,
    "stream": false,
    "stop": "\n"
  }'

响应格式

{
  "id": "cmpl-p9rtxv6fky2v9k8jrd8cc",
  "object": "text_completion",
  "created": 1731990488,
  "model": "granite-3.0-2b-instruct",
  "choices": [
    {
      "index": 0,
      "text": " to find your purpose, and once you have",
      "logprobs": null,
      "finish_reason": "length"
    }
  ],
  "usage": {
    "prompt_tokens": 5,
    "completion_tokens": 9,
    "total_tokens": 14
  },
  "stats": {
    "tokens_per_second": 57.69230769230769,
    "time_to_first_token": 0.299,
    "generation_time": 0.156,
    "stop_reason": "maxPredictedTokensReached"
  },
  "model_info": {
    "arch": "granite",
    "quant": "Q4_K_M",
    "format": "gguf",
    "context_length": 4096
  },
  "runtime": {
    "name": "llama.cpp-mac-arm64-apple-metal-advsimd",
    "version": "1.3.0",
    "supported_formats": ["gguf"]
  }
}

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POST /api/v0/embeddings

文本嵌入 API。您提供一段文本，并返回该文本的嵌入向量表示。

示例请求

curl http://127.0.0.1:1234/api/v0/embeddings \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-nomic-embed-text-v1.5",
    "input": "Some text to embed"
  }

示例响应

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "embedding": [
        -0.016731496900320053,
        0.028460891917347908,
        -0.1407836228609085,
        ... (truncated for brevity) ...,
        0.02505224384367466,
        -0.0037634256295859814,
        -0.04341062530875206
      ],
      "index": 0
    }
  ],
  "model": "text-embedding-nomic-embed-text-v1.5@q4_k_m",
  "usage": {
    "prompt_tokens": 0,
    "total_tokens": 0
  }
}

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请在 Github 上提交问题以报告错误。