curl --request POST \
  --url https://api.vidgo.ai/api/generate/submit \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "qwen-image-3.0-pro/text-to-image",
  "callback_url": "https://your-domain.com/callback",
  "input": {
    "prompt": "A cinematic scene with natural lighting and coherent motion",
    "resolution": "1K",
    "size": "1:1"
  }
}
'

import requests

url = "https://api.vidgo.ai/api/generate/submit"

payload = {
    "model": "qwen-image-3.0-pro/text-to-image",
    "callback_url": "https://your-domain.com/callback",
    "input": {
        "prompt": "A cinematic scene with natural lighting and coherent motion",
        "resolution": "1K",
        "size": "1:1"
    }
}
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: 'qwen-image-3.0-pro/text-to-image',
    callback_url: 'https://your-domain.com/callback',
    input: {
      prompt: 'A cinematic scene with natural lighting and coherent motion',
      resolution: '1K',
      size: '1:1'
    }
  })
};

fetch('https://api.vidgo.ai/api/generate/submit', 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.vidgo.ai/api/generate/submit",
  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' => 'qwen-image-3.0-pro/text-to-image',
    'callback_url' => 'https://your-domain.com/callback',
    'input' => [
        'prompt' => 'A cinematic scene with natural lighting and coherent motion',
        'resolution' => '1K',
        'size' => '1:1'
    ]
  ]),
  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.vidgo.ai/api/generate/submit"

	payload := strings.NewReader("{\n  \"model\": \"qwen-image-3.0-pro/text-to-image\",\n  \"callback_url\": \"https://your-domain.com/callback\",\n  \"input\": {\n    \"prompt\": \"A cinematic scene with natural lighting and coherent motion\",\n    \"resolution\": \"1K\",\n    \"size\": \"1:1\"\n  }\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.vidgo.ai/api/generate/submit")
  .header("Authorization", "Bearer <token>")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"qwen-image-3.0-pro/text-to-image\",\n  \"callback_url\": \"https://your-domain.com/callback\",\n  \"input\": {\n    \"prompt\": \"A cinematic scene with natural lighting and coherent motion\",\n    \"resolution\": \"1K\",\n    \"size\": \"1:1\"\n  }\n}")
  .asString();

require 'uri'
require 'net/http'

url = URI("https://api.vidgo.ai/api/generate/submit")

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\": \"qwen-image-3.0-pro/text-to-image\",\n  \"callback_url\": \"https://your-domain.com/callback\",\n  \"input\": {\n    \"prompt\": \"A cinematic scene with natural lighting and coherent motion\",\n    \"resolution\": \"1K\",\n    \"size\": \"1:1\"\n  }\n}"

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

{
  "code": 200,
  "data": {
    "task_id": "<string>",
    "created_time": "2023-11-07T05:31:56Z"
  }
}