Create Embeddings
curl --request POST \
--url https://api.highwayapi.ai/openai/v1/embeddings \
--header 'Authorization: <authorization>' \
--header 'Content-Type: <content-type>' \
--data '
{
"input": [
"<string>"
],
"model": "<string>",
"encoding_format": "<string>"
}
'import requests
url = "https://api.highwayapi.ai/openai/v1/embeddings"
payload = {
"input": ["<string>"],
"model": "<string>",
"encoding_format": "<string>"
}
headers = {
"Content-Type": "<content-type>",
"Authorization": "<authorization>"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'Content-Type': '<content-type>', Authorization: '<authorization>'},
body: JSON.stringify({input: ['<string>'], model: '<string>', encoding_format: '<string>'})
};
fetch('https://api.highwayapi.ai/openai/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.highwayapi.ai/openai/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([
'input' => [
'<string>'
],
'model' => '<string>',
'encoding_format' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Authorization: <authorization>",
"Content-Type: <content-type>"
],
]);
$response = curl_exec($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.highwayapi.ai/openai/v1/embeddings"
payload := strings.NewReader("{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Content-Type", "<content-type>")
req.Header.Add("Authorization", "<authorization>")
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.highwayapi.ai/openai/v1/embeddings")
.header("Content-Type", "<content-type>")
.header("Authorization", "<authorization>")
.body("{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.highwayapi.ai/openai/v1/embeddings")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Content-Type"] = '<content-type>'
request["Authorization"] = '<authorization>'
request.body = "{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"object": "<string>",
"data": [
{
"index": 123,
"embedding": [
123
],
"object": "<string>"
}
],
"model": "<string>",
"usage": {
"prompt_tokens": 123,
"total_tokens": 123
}
}Large Language Models
Create Embeddings
POST
/
openai
/
v1
/
embeddings
Create Embeddings
curl --request POST \
--url https://api.highwayapi.ai/openai/v1/embeddings \
--header 'Authorization: <authorization>' \
--header 'Content-Type: <content-type>' \
--data '
{
"input": [
"<string>"
],
"model": "<string>",
"encoding_format": "<string>"
}
'import requests
url = "https://api.highwayapi.ai/openai/v1/embeddings"
payload = {
"input": ["<string>"],
"model": "<string>",
"encoding_format": "<string>"
}
headers = {
"Content-Type": "<content-type>",
"Authorization": "<authorization>"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {'Content-Type': '<content-type>', Authorization: '<authorization>'},
body: JSON.stringify({input: ['<string>'], model: '<string>', encoding_format: '<string>'})
};
fetch('https://api.highwayapi.ai/openai/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.highwayapi.ai/openai/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([
'input' => [
'<string>'
],
'model' => '<string>',
'encoding_format' => '<string>'
]),
CURLOPT_HTTPHEADER => [
"Authorization: <authorization>",
"Content-Type: <content-type>"
],
]);
$response = curl_exec($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.highwayapi.ai/openai/v1/embeddings"
payload := strings.NewReader("{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Content-Type", "<content-type>")
req.Header.Add("Authorization", "<authorization>")
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.highwayapi.ai/openai/v1/embeddings")
.header("Content-Type", "<content-type>")
.header("Authorization", "<authorization>")
.body("{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.highwayapi.ai/openai/v1/embeddings")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Content-Type"] = '<content-type>'
request["Authorization"] = '<authorization>'
request.body = "{\n \"input\": [\n \"<string>\"\n ],\n \"model\": \"<string>\",\n \"encoding_format\": \"<string>\"\n}"
response = http.request(request)
puts response.read_body{
"object": "<string>",
"data": [
{
"index": 123,
"embedding": [
123
],
"object": "<string>"
}
],
"model": "<string>",
"usage": {
"prompt_tokens": 123,
"total_tokens": 123
}
}Creates an embedding vector representing the input text.
Request Headers
string
required
Enum value:
application/jsonstring
required
Bearer authentication format: Bearer {{API Key}}.
Request Body
string[]
required
The input text to embed, encoded as a string or an array of tokens. To embed multiple inputs in a single request, pass an array of strings or an array of token arrays. The input must not exceed the model’s maximum input tokens (
text-embedding-ada-002 has 8192 tokens), must not be an empty string, and the dimensions of any array must be less than or equal to 2048.string
required
The model ID to use. Enum value:
baai/bge-m3
string
The format for returning the embedding vector. Can be float or base64.
Response Information
string
required
Always list
object[]
required
string
required
The model ID used.
⌘I