curl --request POST \
  --url https://ai.cubeuaeai.com/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "gpt-image-2",
  "prompt": "A sunset skyline of a futuristic city with flying cars",
  "n": 1,
  "size": "1024x1024",
  "quality": "high",
  "output_format": "png",
  "moderation": "auto",
  "output_compression": 80
}
'

import requests

url = "https://ai.cubeuaeai.com/v1/images/generations"

payload = {
    "model": "gpt-image-2",
    "prompt": "A sunset skyline of a futuristic city with flying cars",
    "n": 1,
    "size": "1024x1024",
    "quality": "high",
    "output_format": "png",
    "moderation": "auto",
    "output_compression": 80
}
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: 'gpt-image-2',
    prompt: 'A sunset skyline of a futuristic city with flying cars',
    n: 1,
    size: '1024x1024',
    quality: 'high',
    output_format: 'png',
    moderation: 'auto',
    output_compression: 80
  })
};

fetch('https://ai.cubeuaeai.com/v1/images/generations', 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://ai.cubeuaeai.com/v1/images/generations",
  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' => 'gpt-image-2',
    'prompt' => 'A sunset skyline of a futuristic city with flying cars',
    'n' => 1,
    'size' => '1024x1024',
    'quality' => 'high',
    'output_format' => 'png',
    'moderation' => 'auto',
    'output_compression' => 80
  ]),
  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://ai.cubeuaeai.com/v1/images/generations"

	payload := strings.NewReader("{\n  \"model\": \"gpt-image-2\",\n  \"prompt\": \"A sunset skyline of a futuristic city with flying cars\",\n  \"n\": 1,\n  \"size\": \"1024x1024\",\n  \"quality\": \"high\",\n  \"output_format\": \"png\",\n  \"moderation\": \"auto\",\n  \"output_compression\": 80\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://ai.cubeuaeai.com/v1/images/generations")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"gpt-image-2\",\n  \"prompt\": \"A sunset skyline of a futuristic city with flying cars\",\n  \"n\": 1,\n  \"size\": \"1024x1024\",\n  \"quality\": \"high\",\n  \"output_format\": \"png\",\n  \"moderation\": \"auto\",\n  \"output_compression\": 80\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://ai.cubeuaeai.com/v1/images/generations")

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\": \"gpt-image-2\",\n  \"prompt\": \"A sunset skyline of a futuristic city with flying cars\",\n  \"n\": 1,\n  \"size\": \"1024x1024\",\n  \"quality\": \"high\",\n  \"output_format\": \"png\",\n  \"moderation\": \"auto\",\n  \"output_compression\": 80\n}"

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

{
  "data": [
    {
      "b64_json": "<string>",
      "revised_prompt": "<string>"
    }
  ]
}