文本嵌入

使用 GLM Embedding 系列模型将文本转换为高维向量表示，用于语义相似性和搜索。点击 Try it 按钮可快速试用。

POST /paas/v4/embeddings

文本嵌入

cURL

curl --request POST \
  --url https://open.bigmodel.cn/api/paas/v4/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "embedding-3",
  "input": "你好，今天天气怎么样.",
  "dimensions": 2
}
'

import requests

url = "https://open.bigmodel.cn/api/paas/v4/embeddings"

payload = {
    "model": "embedding-3",
    "input": "你好，今天天气怎么样.",
    "dimensions": 2
}
headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.text)

const options = {
  method: 'POST',
  headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
  body: JSON.stringify({model: 'embedding-3', input: '你好，今天天气怎么样.', dimensions: 2})
};

fetch('https://open.bigmodel.cn/api/paas/v4/embeddings', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

HttpResponse<String> response = Unirest.post("https://open.bigmodel.cn/api/paas/v4/embeddings")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"embedding-3\",\n  \"input\": \"你好，今天天气怎么样.\",\n  \"dimensions\": 2\n}")
  .asString();

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://open.bigmodel.cn/api/paas/v4/embeddings"

	payload := strings.NewReader("{\n  \"model\": \"embedding-3\",\n  \"input\": \"你好，今天天气怎么样.\",\n  \"dimensions\": 2\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Authorization", "Bearer <token>")
	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://open.bigmodel.cn/api/paas/v4/embeddings",
  CURLOPT_RETURNTRANSFER => true,
  CURLOPT_ENCODING => "",
  CURLOPT_MAXREDIRS => 10,
  CURLOPT_TIMEOUT => 30,
  CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
  CURLOPT_CUSTOMREQUEST => "POST",
  CURLOPT_POSTFIELDS => json_encode([
    'model' => 'embedding-3',
    'input' => '你好，今天天气怎么样.',
    'dimensions' => 2
  ]),
  CURLOPT_HTTPHEADER => [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
  ],
]);

$response = curl_exec($curl);
$err = curl_error($curl);

curl_close($curl);

if ($err) {
  echo "cURL Error #:" . $err;
} else {
  echo $response;
}

200

{
  "model": "<string>",
  "object": "list",
  "data": [
    {
      "index": 123,
      "object": "embedding",
      "embedding": [
        123
      ]
    }
  ],
  "usage": {
    "prompt_tokens": 123,
    "completion_tokens": 123,
    "total_tokens": 123
  }
}

{
  "error": {
    "code": "<string>",
    "message": "<string>"
  }
}

Authorizations

Authorization · string · header · required

标准的 HTTP Bearer 认证方式，在 API Keys 页面获取密钥。

Body

application/json

model · enum<string> · required

嵌入模型名称，如 embedding-3、embedding-2

Available options: embedding-3, embedding-2

input · string string[] · required

输入文本，支持字符串或字符串数组。

• embedding-2 的单条请求最多支持 512 个Tokens，数组总长度不得超过8K
• embedding-3 的单条请求最多支持 3072 个Tokens，且数组最大不得超过 64 条

dimensions · enum<integer>

输出向量维度，Embedding-3 默认 2048，Embedding-2 固定 1024。Embedding-3 支持自定义，可选值：256、512、1024或2048。

Available options: 2048, 1024, 512, 256

Required range: x >= 1

Response

200

application/json

业务处理成功

文本嵌入响应对象，包含嵌入向量结果、模型信息和 tokens 统计。

model · string

模型编码。

object · enum<string>

结果类型，目前为 list。

Available options: list

data · object[]

模型生成的数组结果。每个元素为单条文本的嵌入结果对象。

Show child attributes

usage · object

本次模型调用的 tokens 数量统计。

Show child attributes