Embeddings

The Embeddings API supports both OpenAI-compatible and Gemini-native vector generation for retrieval, clustering, and semantic similarity workloads.

Native OpenAI Format

Use the OpenAI-compatible embeddings endpoint when you want simple SDK-based integration and broad ecosystem support.

POST

https://api.dgrid.ai

POST/v1/embeddings

Authorization

Authorization: Bearer <DGRID_API_KEY>

Request

application/json

Response

200 · application/json

Request Body

Field	Type	Required	Default	Description
input	string or array	Yes	-	Input text or text array.
model	string	Yes	-	Embedding model ID.
encoding_format	string	No	float	float or base64.
dimensions	integer	No	-	Output vector dimensions.
user	string	No	-	End-user identifier.

Response Body

Field	Type	Description
object	string	Always list.
data	array	Embedding results.
data[].object	string	Always embedding.
data[].embedding	array	Embedding vector.
data[].index	integer	Embedding index.
model	string	Model used for the request.
usage	object	Token usage summary.

Request Example

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 Response

application/json

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

Legacy Engine Embeddings Format

Use the engine-based embeddings request shown in the code example when you need the legacy path format.

POST

https://api.dgrid.ai

POST/v1/engines/{engine}/embeddings

Authorization

Authorization: Bearer <DGRID_API_KEY>

Request

application/json

Response

200 · application/json

Path Parameters

Parameter	Type	Required	Description
engine	string	Yes	Engine identifier used in the request path, such as string.

Request Body

Field	Type	Required	Description
model	string	Yes	Embedding model ID used in the JSON body.
input	string	Yes	Input text to embed.

Response Body

Field	Type	Description
object	string	Always list.
data	array	Embedding results.
data[].object	string	Always embedding.
data[].embedding	array	Embedding vector.
data[].index	integer	Embedding index.
model	string	Model used for the request.
usage	object	Token usage summary.

Request Example

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 Response

application/json

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