Create embeddings

POST

openai

embeddings

JavaScript

import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});

const response = await client.ai.openai.embeddings.createEmbeddings({
  input: 'The quick brown fox jumps over the lazy dog',
  model: 'thenlper/gte-large',
});

console.log(response.data);

import os
from telnyx import Telnyx

client = Telnyx(
    api_key=os.environ.get("TELNYX_API_KEY"),  # This is the default and can be omitted
)
response = client.ai.openai.embeddings.create_embeddings(
    input="The quick brown fox jumps over the lazy dog",
    model="thenlper/gte-large",
)
print(response.data)

package main

import (
	"context"
	"fmt"

	"github.com/team-telnyx/telnyx-go"
	"github.com/team-telnyx/telnyx-go/option"
)

func main() {
	client := telnyx.NewClient(
		option.WithAPIKey("My API Key"),
	)
	response, err := client.AI.OpenAI.Embeddings.NewEmbeddings(context.TODO(), telnyx.AIOpenAIEmbeddingNewEmbeddingsParams{
		Input: telnyx.AIOpenAIEmbeddingNewEmbeddingsParamsInputUnion{
			OfString: telnyx.String("The quick brown fox jumps over the lazy dog"),
		},
		Model: "thenlper/gte-large",
	})
	if err != nil {
		panic(err.Error())
	}
	fmt.Printf("%+v\n", response.Data)
}

package com.telnyx.sdk.example;

import com.telnyx.sdk.client.TelnyxClient;
import com.telnyx.sdk.client.okhttp.TelnyxOkHttpClient;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsParams;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsResponse;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        TelnyxClient client = TelnyxOkHttpClient.fromEnv();

        EmbeddingCreateEmbeddingsParams params = EmbeddingCreateEmbeddingsParams.builder()
            .input("The quick brown fox jumps over the lazy dog")
            .model("thenlper/gte-large")
            .build();
        EmbeddingCreateEmbeddingsResponse response = client.ai().openai().embeddings().createEmbeddings(params);
    }
}

require "telnyx"

telnyx = Telnyx::Client.new(api_key: "My API Key")

response = telnyx.ai.openai.embeddings.create_embeddings(
  input: "The quick brown fox jumps over the lazy dog",
  model: "thenlper/gte-large"
)

puts(response)

<?php

require_once dirname(__DIR__) . '/vendor/autoload.php';

use Telnyx\Client;
use Telnyx\Core\Exceptions\APIException;

$client = new Client(apiKey: getenv('TELNYX_API_KEY') ?: 'My API Key');

try {
  $response = $client->ai->openai->embeddings->createEmbeddings(
    input: 'The quick brown fox jumps over the lazy dog',
    model: 'thenlper/gte-large',
    dimensions: 0,
    encodingFormat: 'float',
    user: 'user',
  );

  var_dump($response);
} catch (APIException $e) {
  echo $e->getMessage();
}

curl --request POST \
  --url https://api.telnyx.com/v2/ai/openai/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "The quick brown fox jumps over the lazy dog",
  "model": "thenlper/gte-large"
}
'

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

{
  "detail": [
    {
      "loc": [
        "body",
        "name"
      ],
      "msg": "Field required",
      "type": "missing"
    }
  ]
}

Authorizations

Authorization

string

header

required

Bearer authentication header of the form Bearer <token>, where <token> is your auth token.

Body

application/json

input

required

Input text to embed. Can be a string or array of strings.

model

string

required

ID of the model to use. Use the List embedding models endpoint to see available models.

Example:

"thenlper/gte-large"

encoding_format

enum<string>

default:float

The format to return the embeddings in.

Available options:

float,

base64

dimensions

integer

The number of dimensions the resulting output embeddings should have. Only supported in some models.

user

string

A unique identifier representing your end-user for monitoring and abuse detection.

Response

Successful Response

object

string

default:list

required

The object type, always 'list'

data

OpenAIEmbeddingData · object[]

required

List of embedding objects

Show child attributes

model

string

required

The model used for embedding

usage

OpenAIEmbeddingUsage · object

required

Show child attributes

⌘I

JavaScript

import Telnyx from 'telnyx';

const client = new Telnyx({
  apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted
});

const response = await client.ai.openai.embeddings.createEmbeddings({
  input: 'The quick brown fox jumps over the lazy dog',
  model: 'thenlper/gte-large',
});

console.log(response.data);

import os
from telnyx import Telnyx

client = Telnyx(
    api_key=os.environ.get("TELNYX_API_KEY"),  # This is the default and can be omitted
)
response = client.ai.openai.embeddings.create_embeddings(
    input="The quick brown fox jumps over the lazy dog",
    model="thenlper/gte-large",
)
print(response.data)

package main

import (
	"context"
	"fmt"

	"github.com/team-telnyx/telnyx-go"
	"github.com/team-telnyx/telnyx-go/option"
)

func main() {
	client := telnyx.NewClient(
		option.WithAPIKey("My API Key"),
	)
	response, err := client.AI.OpenAI.Embeddings.NewEmbeddings(context.TODO(), telnyx.AIOpenAIEmbeddingNewEmbeddingsParams{
		Input: telnyx.AIOpenAIEmbeddingNewEmbeddingsParamsInputUnion{
			OfString: telnyx.String("The quick brown fox jumps over the lazy dog"),
		},
		Model: "thenlper/gte-large",
	})
	if err != nil {
		panic(err.Error())
	}
	fmt.Printf("%+v\n", response.Data)
}

package com.telnyx.sdk.example;

import com.telnyx.sdk.client.TelnyxClient;
import com.telnyx.sdk.client.okhttp.TelnyxOkHttpClient;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsParams;
import com.telnyx.sdk.models.ai.openai.embeddings.EmbeddingCreateEmbeddingsResponse;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        TelnyxClient client = TelnyxOkHttpClient.fromEnv();

        EmbeddingCreateEmbeddingsParams params = EmbeddingCreateEmbeddingsParams.builder()
            .input("The quick brown fox jumps over the lazy dog")
            .model("thenlper/gte-large")
            .build();
        EmbeddingCreateEmbeddingsResponse response = client.ai().openai().embeddings().createEmbeddings(params);
    }
}

require "telnyx"

telnyx = Telnyx::Client.new(api_key: "My API Key")

response = telnyx.ai.openai.embeddings.create_embeddings(
  input: "The quick brown fox jumps over the lazy dog",
  model: "thenlper/gte-large"
)

puts(response)

<?php

require_once dirname(__DIR__) . '/vendor/autoload.php';

use Telnyx\Client;
use Telnyx\Core\Exceptions\APIException;

$client = new Client(apiKey: getenv('TELNYX_API_KEY') ?: 'My API Key');

try {
  $response = $client->ai->openai->embeddings->createEmbeddings(
    input: 'The quick brown fox jumps over the lazy dog',
    model: 'thenlper/gte-large',
    dimensions: 0,
    encodingFormat: 'float',
    user: 'user',
  );

  var_dump($response);
} catch (APIException $e) {
  echo $e->getMessage();
}

curl --request POST \
  --url https://api.telnyx.com/v2/ai/openai/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "input": "The quick brown fox jumps over the lazy dog",
  "model": "thenlper/gte-large"
}
'

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

{
  "detail": [
    {
      "loc": [
        "body",
        "name"
      ],
      "msg": "Field required",
      "type": "missing"
    }
  ]
}

Embedding

Bucket

OpenAI-compatible

API Reference

For AI Agents

Create embeddings

Authorizations

Body

Response