Create Embeddings - Mesh API

Create Embeddings

curl --request POST \
  --url https://api.meshapi.ai/v1/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "openai/text-embedding-3-small",
  "input": "The quick brown fox jumps over the lazy dog."
}
'

import requests

url = "https://api.meshapi.ai/v1/embeddings"

payload = {
    "model": "openai/text-embedding-3-small",
    "input": "The quick brown fox jumps over the lazy dog."
}
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: 'openai/text-embedding-3-small',
    input: 'The quick brown fox jumps over the lazy dog.'
  })
};

fetch('https://api.meshapi.ai/v1/embeddings', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.meshapi.ai/v1/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' => 'openai/text-embedding-3-small',
    'input' => 'The quick brown fox jumps over the lazy dog.'
  ]),
  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;
}

package main

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

func main() {

	url := "https://api.meshapi.ai/v1/embeddings"

	payload := strings.NewReader("{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\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))

}

HttpResponse<String> response = Unirest.post("https://api.meshapi.ai/v1/embeddings")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.meshapi.ai/v1/embeddings")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\n}"

response = http.request(request)
puts response.read_body

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        -0.03264831379055977,
        -0.03786936774849892,
        0.007462255656719208
      ]
    }
  ],
  "model": "amazon/titan-embed-text-v2",
  "usage": {
    "prompt_tokens": 3,
    "total_tokens": 3
  }
}

POST

/

v1

/

embeddings

Create Embeddings

curl --request POST \
  --url https://api.meshapi.ai/v1/embeddings \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "openai/text-embedding-3-small",
  "input": "The quick brown fox jumps over the lazy dog."
}
'

import requests

url = "https://api.meshapi.ai/v1/embeddings"

payload = {
    "model": "openai/text-embedding-3-small",
    "input": "The quick brown fox jumps over the lazy dog."
}
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: 'openai/text-embedding-3-small',
    input: 'The quick brown fox jumps over the lazy dog.'
  })
};

fetch('https://api.meshapi.ai/v1/embeddings', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

<?php

$curl = curl_init();

curl_setopt_array($curl, [
  CURLOPT_URL => "https://api.meshapi.ai/v1/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' => 'openai/text-embedding-3-small',
    'input' => 'The quick brown fox jumps over the lazy dog.'
  ]),
  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;
}

package main

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

func main() {

	url := "https://api.meshapi.ai/v1/embeddings"

	payload := strings.NewReader("{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\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))

}

HttpResponse<String> response = Unirest.post("https://api.meshapi.ai/v1/embeddings")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.meshapi.ai/v1/embeddings")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n  \"model\": \"openai/text-embedding-3-small\",\n  \"input\": \"The quick brown fox jumps over the lazy dog.\"\n}"

response = http.request(request)
puts response.read_body

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        -0.03264831379055977,
        -0.03786936774849892,
        0.007462255656719208
      ]
    }
  ],
  "model": "amazon/titan-embed-text-v2",
  "usage": {
    "prompt_tokens": 3,
    "total_tokens": 3
  }
}

Authorizations

Authorization

string

header

required

Enter your MeshAPI key (rsk_...) — sent as Authorization: Bearer <key>.

Body

application/json

Request body for POST /v1/embeddings.

Mirrors the OpenAI embeddings API. The input field accepts four shapes:

string — a single text to embed
list[string] — a batch of texts
list[int] — a single pre-tokenised input (token IDs)
list[list[int]] — a batch of pre-tokenised inputs

input

required

Text(s) to embed. Accepts a string, list of strings, list of token IDs, list of token ID lists, or a list of MultimodalEmbeddingInput objects (for BytePlus multimodal embedding models).

model

string | null

Model ID to use for embedding, e.g. perplexity/pplx-embed-v1-4b.

Example:

"perplexity/pplx-embed-v1-4b"

dimensions

integer | null

Number of dimensions for the output embedding vector (model-dependent).

Required range: x >= 1

encoding_format

enum<string> | null

Format of the returned embedding. Defaults to float.

Available options:

float,

base64

input_type

string | null

Intended use of the embedding, e.g. query or document. Some models use this to apply asymmetric embedding.

provider

Provider routing preferences. Pass a provider slug string (e.g. 'perplexity') or a ProviderPreferences object to control fallback and ordering behaviour.

user

string | null

End-user identifier for abuse monitoring.

Maximum string length: 256

instructions

string | null

Inference prompt for BytePlus multimodal embeddings. A default is generated from the input modality if not set.

sparse_embedding

Sparse Embedding · object | null

Sparse vector switch for BytePlus text embeddings. Pass {"type": "enabled"} to return both dense and sparse vectors, or {"type": "disabled"} for dense only.

Response

Embedding response