嵌入

嵌入 API 同時支援 OpenAI 相容與 Gemini 原生向量生成，可用於檢索、分群與語意相似度應用。

原生 OpenAI 格式

若您希望以簡單 SDK 方式整合，並取得最廣泛的生態相容性，請使用 OpenAI 相容 embeddings 端點。

POST

https://api.dgrid.ai

POST/v1/embeddings

Authorization

Authorization: Bearer <DGRID_API_KEY>

Request

application/json

Response

200 · application/json

請求體

欄位	型別	必填	預設值	說明
input	string 或 array	是	-	輸入文字或文字陣列。
model	string	是	-	嵌入模型 ID。
encoding_format	string	否	float	float 或 base64。
dimensions	integer	否	-	輸出維度。
user	string	否	-	終端使用者識別。

回應體

欄位	型別	說明
object	string	固定為 list。
data	array	嵌入結果陣列。
data[].object	string	固定為 embedding。
data[].embedding	array	嵌入向量。
data[].index	integer	向量索引。
model	string	實際使用的模型。
usage	object	Token 使用摘要。

請求範例

cURL / JavaScript / Go / Python / Java / C#

cURL

curl -X POST "https://api.dgrid.ai/v1/embeddings" \
  -H "Authorization: Bearer " \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-ada-002",
    "input": "string"
  }'

JavaScript

const body = JSON.stringify({
  "model": "text-embedding-ada-002",
  "input": "string"
})

fetch("https://api.dgrid.ai/v1/embeddings", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer "
  },
  body
})

Go

package main

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

func main() {
  url := "https://api.dgrid.ai/v1/embeddings"
  body := strings.NewReader(`{
    "model": "text-embedding-ada-002",
    "input": "string"
  }`)
  req, _ := http.NewRequest("POST", url, body)
  req.Header.Add("Authorization", "Bearer ")
  req.Header.Add("Content-Type", "application/json")
  res, _ := http.DefaultClient.Do(req)
  defer res.Body.Close()
  body, _ := ioutil.ReadAll(res.Body)

  fmt.Println(res)
  fmt.Println(string(body))
}

Python

import requests

url = "https://api.dgrid.ai/v1/embeddings"
body = """{
  "model": "text-embedding-ada-002",
  "input": "string"
}"""
response = requests.request("POST", url, data = body, headers = {
  "Content-Type": "application/json", 
  "Authorization": "Bearer "
})

print(response.text)

Java

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.http.HttpResponse.BodyHandlers;
import java.time.Duration;
import java.net.http.HttpRequest.BodyPublishers;

var body = BodyPublishers.ofString("""{
  "model": "text-embedding-ada-002",
  "input": "string"
}""");
HttpClient client = HttpClient.newBuilder()
  .connectTimeout(Duration.ofSeconds(10))
  .build();

HttpRequest.Builder requestBuilder = HttpRequest.newBuilder()
  .uri(URI.create("https://api.dgrid.ai/v1/embeddings"))
  .header("Authorization", "Bearer ")
  .header("Content-Type", "application/json")
  .POST(body)
  .build();

try {
  HttpResponse<String> response = client.send(requestBuilder.build(), BodyHandlers.ofString());
  System.out.println("Status code: " + response.statusCode());
  System.out.println("Response body: " + response.body());
} catch (Exception e) {
  e.printStackTrace();
}

C#

using System;
using System.Net.Http;
using System.Text;

var body = new StringContent("""
{
  "model": "text-embedding-ada-002",
  "input": "string"
}
""", Encoding.UTF8, "application/json");

var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer ");
var response = await client.PostAsync("https://api.dgrid.ai/v1/embeddings", body);
var responseBody = await response.Content.ReadAsStringAsync();

200 回應

application/json

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0
      ]
    }
  ],
  "model": "string",
  "usage": {
    "prompt_tokens": 0,
    "total_tokens": 0
  }
}

舊版 Engine Embeddings 格式

目前範例使用 engine 路徑的舊版嵌入介面，並在請求體中傳送 model 與 input。

POST

https://api.dgrid.ai

POST/v1/engines/{engine}/embeddings

Authorization

Authorization: Bearer <DGRID_API_KEY>

Request

application/json

Response

200 · application/json

路徑參數

參數	型別	必填	說明
engine	string	是	engine ID，例如 text-embedding-ada-002。

請求體

欄位	型別	必填	說明
model	string	是	請求體中的模型名稱。
input	string	是	要嵌入的輸入字串。

回應體

欄位	型別	說明
object	string	最上層物件型別。
data	array	嵌入結果陣列。
data[].object	string	各項目的物件型別。
data[].embedding	array	嵌入向量值。
data[].index	integer	結果索引。
model	string	回應中的模型名稱。
usage	object	Token 使用資訊。

請求範例

cURL / JavaScript / Go / Python / Java / C#

cURL

curl -X POST "https://api.dgrid.ai/v1/engines/string/embeddings" \
  -H "Authorization: Bearer " \
  -H "Content-Type: application/json" \
  -d '{
    "model": "text-embedding-ada-002",
    "input": "string"
  }'

JavaScript

const body = JSON.stringify({
  "model": "text-embedding-ada-002",
  "input": "string"
})

fetch("https://api.dgrid.ai/v1/engines/string/embeddings", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer "
  },
  body
})

Go

package main

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

func main() {
  url := "https://api.dgrid.ai/v1/engines/string/embeddings"
  body := strings.NewReader(`{
    "model": "text-embedding-ada-002",
    "input": "string"
  }`)
  req, _ := http.NewRequest("POST", url, body)
  req.Header.Add("Authorization", "Bearer ")
  req.Header.Add("Content-Type", "application/json")
  res, _ := http.DefaultClient.Do(req)
  defer res.Body.Close()
  body, _ := ioutil.ReadAll(res.Body)

  fmt.Println(res)
  fmt.Println(string(body))
}

Python

import requests

url = "https://api.dgrid.ai/v1/engines/string/embeddings"
body = """{
  "model": "text-embedding-ada-002",
  "input": "string"
}"""
response = requests.request("POST", url, data = body, headers = {
  "Content-Type": "application/json", 
  "Authorization": "Bearer "
})

print(response.text)

Java

import java.net.URI;
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.http.HttpResponse.BodyHandlers;
import java.time.Duration;
import java.net.http.HttpRequest.BodyPublishers;

var body = BodyPublishers.ofString("""{
  "model": "text-embedding-ada-002",
  "input": "string"
}""");
HttpClient client = HttpClient.newBuilder()
  .connectTimeout(Duration.ofSeconds(10))
  .build();

HttpRequest.Builder requestBuilder = HttpRequest.newBuilder()
  .uri(URI.create("https://api.dgrid.ai/v1/engines/string/embeddings"))
  .header("Authorization", "Bearer ")
  .header("Content-Type", "application/json")
  .POST(body)
  .build();

try {
  HttpResponse<String> response = client.send(requestBuilder.build(), BodyHandlers.ofString());
  System.out.println("Status code: " + response.statusCode());
  System.out.println("Response body: " + response.body());
} catch (Exception e) {
  e.printStackTrace();
}

C#

using System;
using System.Net.Http;
using System.Text;

var body = new StringContent("""
{
  "model": "text-embedding-ada-002",
  "input": "string"
}
""", Encoding.UTF8, "application/json");

var client = new HttpClient();
client.DefaultRequestHeaders.Add("Authorization", "Bearer ");
var response = await client.PostAsync("https://api.dgrid.ai/v1/engines/string/embeddings", body);
var responseBody = await response.Content.ReadAsStringAsync();

200 回應

application/json

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0
      ]
    }
  ],
  "model": "string",
  "usage": {
    "prompt_tokens": 0,
    "total_tokens": 0
  }
}