curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
  }'

import requests

url = "https://api.apimart.ai/v1/images/generations"

payload = {
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/images/generations";

const payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1,
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/images/generations"

    payload := map[string]interface{}{
        "model":      "gpt-image-2-official",
        "prompt":     "An ancient castle beneath a starry sky",
        "size":       "16:9",
        "resolution": "2k",
        "quality":    "high",
        "n":          1,
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/images/generations";

        String payload = """
        {
          "model": "gpt-image-2-official",
          "prompt": "An ancient castle beneath a starry sky",
          "size": "16:9",
          "resolution": "2k",
          "quality": "high",
          "n": 1
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}

<?php

$url = "https://api.apimart.ai/v1/images/generations";

$payload = [
    "model" => "gpt-image-2-official",
    "prompt" => "An ancient castle beneath a starry sky",
    "size" => "16:9",
    "resolution" => "2k",
    "quality" => "high",
    "n" => 1
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>

require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/images/generations")

payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1
}

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 = payload.to_json

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

import Foundation

let url = URL(string: "https://api.apimart.ai/v1/images/generations")!

let payload: [String: Any] = [
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/images/generations";

        var payload = @"{
            ""model"": ""gpt-image-2-official"",
            ""prompt"": ""An ancient castle beneath a starry sky"",
            ""size"": ""16:9"",
            ""resolution"": ""2k"",
            ""quality"": ""high"",
            ""n"": 1
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}

import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/images/generations');

  final payload = {
    'model': 'gpt-image-2-official',
    'prompt': 'An ancient castle beneath a starry sky',
    'size': '16:9',
    'resolution': '2k',
    'quality': 'high',
    'n': 1,
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}

library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/images/generations"

payload <- list(
  model = "gpt-image-2-official",
  prompt = "An ancient castle beneath a starry sky",
  size = "16:9",
  resolution = "2k",
  quality = "high",
  n = 1
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01KPTXXXXXXXXXXXXXXX"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid parameters: size not allowed / resolution not supported / pixel violation, etc.",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden, you do not have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}

{
  "error": {
    "code": 500,
    "message": "Internal server error, please try again later",
    "type": "server_error"
  }
}

{
  "error": {
    "code": 502,
    "message": "Bad gateway, the server is temporarily unavailable",
    "type": "bad_gateway"
  }
}

GPT-Image-2

Generación de imágenes con GPT-Image-2 canal oficial

Modelo oficial gpt-image-2 de OpenAI, basado en el protocolo compatible /v1/images/generations
Procesamiento asíncrono, devuelve task_id para consultas posteriores
Texto a imagen / imagen a imagen / inpainting (máscara) — todo en uno
Compatibilidad con fondos transparentes PNG / WebP (canal alfa)
Nuevo campo de nivel resolution — selección de 1K / 2K / 4K
15 proporciones admitidas en los niveles 1K / 2K / 4K
Hasta 4 imágenes por solicitud, hasta 16 imágenes de referencia
95% de alineación de parámetros con gpt-image-1.5-official — la migración solo requiere cambiar el nombre del modelo

POST

images

generations

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
  }'

import requests

url = "https://api.apimart.ai/v1/images/generations"

payload = {
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/images/generations";

const payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1,
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/images/generations"

    payload := map[string]interface{}{
        "model":      "gpt-image-2-official",
        "prompt":     "An ancient castle beneath a starry sky",
        "size":       "16:9",
        "resolution": "2k",
        "quality":    "high",
        "n":          1,
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/images/generations";

        String payload = """
        {
          "model": "gpt-image-2-official",
          "prompt": "An ancient castle beneath a starry sky",
          "size": "16:9",
          "resolution": "2k",
          "quality": "high",
          "n": 1
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}

<?php

$url = "https://api.apimart.ai/v1/images/generations";

$payload = [
    "model" => "gpt-image-2-official",
    "prompt" => "An ancient castle beneath a starry sky",
    "size" => "16:9",
    "resolution" => "2k",
    "quality" => "high",
    "n" => 1
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>

require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/images/generations")

payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1
}

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 = payload.to_json

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

import Foundation

let url = URL(string: "https://api.apimart.ai/v1/images/generations")!

let payload: [String: Any] = [
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/images/generations";

        var payload = @"{
            ""model"": ""gpt-image-2-official"",
            ""prompt"": ""An ancient castle beneath a starry sky"",
            ""size"": ""16:9"",
            ""resolution"": ""2k"",
            ""quality"": ""high"",
            ""n"": 1
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}

import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/images/generations');

  final payload = {
    'model': 'gpt-image-2-official',
    'prompt': 'An ancient castle beneath a starry sky',
    'size': '16:9',
    'resolution': '2k',
    'quality': 'high',
    'n': 1,
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}

library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/images/generations"

payload <- list(
  model = "gpt-image-2-official",
  prompt = "An ancient castle beneath a starry sky",
  size = "16:9",
  resolution = "2k",
  quality = "high",
  n = 1
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01KPTXXXXXXXXXXXXXXX"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid parameters: size not allowed / resolution not supported / pixel violation, etc.",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden, you do not have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}

{
  "error": {
    "code": 500,
    "message": "Internal server error, please try again later",
    "type": "server_error"
  }
}

{
  "error": {
    "code": 502,
    "message": "Bad gateway, the server is temporarily unavailable",
    "type": "bad_gateway"
  }
}

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
  }'

import requests

url = "https://api.apimart.ai/v1/images/generations"

payload = {
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())

const url = "https://api.apimart.ai/v1/images/generations";

const payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1,
};

const headers = {
  Authorization: "Bearer <token>",
  "Content-Type": "application/json",
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload),
})
  .then((response) => response.json())
  .then((data) => console.log(data))
  .catch((error) => console.error("Error:", error));

package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://api.apimart.ai/v1/images/generations"

    payload := map[string]interface{}{
        "model":      "gpt-image-2-official",
        "prompt":     "An ancient castle beneath a starry sky",
        "size":       "16:9",
        "resolution": "2k",
        "quality":    "high",
        "n":          1,
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}

import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://api.apimart.ai/v1/images/generations";

        String payload = """
        {
          "model": "gpt-image-2-official",
          "prompt": "An ancient castle beneath a starry sky",
          "size": "16:9",
          "resolution": "2k",
          "quality": "high",
          "n": 1
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}

<?php

$url = "https://api.apimart.ai/v1/images/generations";

$payload = [
    "model" => "gpt-image-2-official",
    "prompt" => "An ancient castle beneath a starry sky",
    "size" => "16:9",
    "resolution" => "2k",
    "quality" => "high",
    "n" => 1
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>

require 'net/http'
require 'json'
require 'uri'

url = URI("https://api.apimart.ai/v1/images/generations")

payload = {
  model: "gpt-image-2-official",
  prompt: "An ancient castle beneath a starry sky",
  size: "16:9",
  resolution: "2k",
  quality: "high",
  n: 1
}

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 = payload.to_json

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

import Foundation

let url = URL(string: "https://api.apimart.ai/v1/images/generations")!

let payload: [String: Any] = [
    "model": "gpt-image-2-official",
    "prompt": "An ancient castle beneath a starry sky",
    "size": "16:9",
    "resolution": "2k",
    "quality": "high",
    "n": 1
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()

using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://api.apimart.ai/v1/images/generations";

        var payload = @"{
            ""model"": ""gpt-image-2-official"",
            ""prompt"": ""An ancient castle beneath a starry sky"",
            ""size"": ""16:9"",
            ""resolution"": ""2k"",
            ""quality"": ""high"",
            ""n"": 1
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}

import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://api.apimart.ai/v1/images/generations');

  final payload = {
    'model': 'gpt-image-2-official',
    'prompt': 'An ancient castle beneath a starry sky',
    'size': '16:9',
    'resolution': '2k',
    'quality': 'high',
    'n': 1,
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json',
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}

library(httr)
library(jsonlite)

url <- "https://api.apimart.ai/v1/images/generations"

payload <- list(
  model = "gpt-image-2-official",
  prompt = "An ancient castle beneath a starry sky",
  size = "16:9",
  resolution = "2k",
  quality = "high",
  n = 1
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))

{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01KPTXXXXXXXXXXXXXXX"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid parameters: size not allowed / resolution not supported / pixel violation, etc.",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Authentication failed, please check your API key",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient account balance, please top up and try again",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden, you do not have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Too many requests, please try again later",
    "type": "rate_limit_error"
  }
}

{
  "error": {
    "code": 500,
    "message": "Internal server error, please try again later",
    "type": "server_error"
  }
}

{
  "error": {
    "code": 502,
    "message": "Bad gateway, the server is temporarily unavailable",
    "type": "bad_gateway"
  }
}

Autorizaciones

string

requerido

Todos los endpoints requieren autenticación con Bearer TokenObtenga su API Key:Visite la página de gestión de API Keys para obtener su API KeyInclúyala en el encabezado de la solicitud:

Authorization: Bearer YOUR_API_KEY

Body

string

predeterminado:"gpt-image-2-official"

requerido

Nombre del modelo de generación de imágenesFijo en gpt-image-2-official (modelo oficial gpt-image-2 de OpenAI)

boolean

predeterminado:"false"

Indica si se debe moderar el contenido antes de enviar la tarea de imagen.

true: revisar los prompts y las imágenes de entrada con omni-moderation-latest
false u omitido: no enviar una solicitud de moderación, sin coste ni latencia de moderación adicionales (predeterminado)

string

requerido

Descripción textual para la generación de la imagen

Admite inglés y chino, se recomiendan descripciones detalladas
Moderación de contenido / revisión de seguridad antes del envío — las violaciones se rechazan inmediatamente

string

predeterminado:"1:1"

Proporción de la imagenExternamente usa valores de proporción; internamente se mapean a píxeles reales según resolution.Proporciones admitidas, más auto para dejar que el servidor elija una proporción adecuada automáticamente:

auto - Automática (el servidor elige una proporción según el prompt / imágenes de referencia)
1:1 - Cuadrada (predeterminada, avatares sociales / logos)
3:2 - Horizontal (proporción común de DSLR)
2:3 - Vertical (pósters verticales)
4:3 - Horizontal (monitor clásico / presentación de diapositivas)
3:4 - Vertical
5:4 - Horizontal
4:5 - Vertical (publicación vertical de Instagram)
16:9 - Horizontal (miniatura de video panorámico)
9:16 - Vertical (pantalla completa de móvil / portada de video corto)
2:1 - Horizontal (banner web)
1:2 - Vertical
3:1 - Horizontal (banner ultra panorámico)
1:3 - Vertical (póster extra alto)
21:9 - Horizontal (cinematográfico ultra panorámico)
9:21 - Vertical

También pueden pasarse dimensiones en píxeles directamente, como 1881x836 / 887x1774.

Cuando size se establece en auto, la proporción predeterminada es 1:1.

string

predeterminado:"1k"

Nivel de resolución (nuevo campo)Controla la nitidez real de la salida.

1k - Línea base 1024, rentable para uso diario (predeterminado)
2k - Línea base 2048, adecuado para pósters / necesidades de alta definición
4k - Línea base 3840, admite las 15 proporciones de la tabla de mapeo siguiente

El 4K admite las 15 proporciones en la tabla de mapeo siguiente; también puede pasar las dimensiones en píxeles de la tabla directamente mediante size.

string

predeterminado:"auto"

Calidad de la imagen

auto - Automática (predeterminado, normalmente equivale a low)
low - Rápida y económica, suficiente para bocetos
medium - Equilibrada
high - Precisión máxima (4K + high puede tardar >120s)

string

predeterminado:"auto"

Modo de fondo

auto - Automático (predeterminado)
opaque - Opaco
transparent - Solicita un fondo transparente; la salida incluye un canal alfa

string

predeterminado:"auto"

Nivel de moderación

auto - Nivel de moderación predeterminado
low - Moderación más permisiva

string

predeterminado:"png"

Formato de salida

png - Formato predeterminado, admite fondos transparentes
jpeg - Archivos más pequeños, no admite canal alfa
webp - Admite fondos transparentes, adecuado para navegadores modernos

Cuando background sea transparent, solo se puede seleccionar png o webp.

integer

Nivel de compresión de salida, rango 0-100

Solo efectivo para jpeg / webp

integer

predeterminado:"1"

Número de imágenes a generarRango: 1 ~ 4

Debe ser un número puro (p. ej., 1), no lo envuelva en comillas

array

Array de URLs de imágenes de referencia

Mostrar Detalles

Máximo 20 MB por imagen, límite total de 256 MB
Hasta 16 imágenes de referencia; las que excedan serán rechazadas
Deben ser URLs de imagen estables y accesibles públicamente

string

URL de la imagen de máscara, usada para inpainting

Debe usarse junto con image_urls

Asegúrese de que la imagen de máscara tenga un canal Alpha antes de cargarla.
Las dimensiones de la imagen de máscara deben coincidir con la primera imagen de referencia.

Mapeo Size × Resolution

size × resolution → píxeles reales de OpenAI (15 proporciones × 3 niveles):

size	`1k`	`2k`	`4k`
`1:1`	1024×1024	2048×2048	2880×2880
`3:2`	1536×1024	2048×1360	3520×2336
`2:3`	1024×1536	1360×2048	2336×3520
`4:3`	1024×768	2048×1536	3312×2480
`3:4`	768×1024	1536×2048	2480×3312
`5:4`	1280×1024	2560×2048	3216×2576
`4:5`	1024×1280	2048×2560	2576×3216
`16:9`	1536×864	2048×1152	3840×2160
`9:16`	864×1536	1152×2048	2160×3840
`2:1`	2048×1024	2688×1344	3840×1920
`1:2`	1024×2048	1344×2688	1920×3840
`3:1`	1881×836 / 1536×512	3072×1024	3840×1280
`1:3`	887×1774 / 512×1536	1024×3072	1280×3840
`21:9`	2016×864	2688×1152	3840×1648
`9:21`	864×2016	1152×2688	1648×3840

Nota: Algunas dimensiones se aproximan en función de múltiplos de 16 y límites de píxeles, como 3:2 / 2:3 @ 2K siendo 2048×1360 y 21:9 @ 4K siendo 3840×1648. Use los píxeles reales de la tabla como fuente de verdad.

Ejemplos de uso

Texto a imagen (solicitud mínima)

{
  "model": "gpt-image-2-official",
  "prompt": "An ancient castle beneath a starry sky"
}

Texto a imagen (sticker transparente)

{
  "model": "gpt-image-2-official",
  "prompt": "A cute cartoon orange cat sticker, full body, thick white outline, flat vector style, isolated on a fully transparent background",
  "size": "1:1",
  "resolution": "1k",
  "quality": "medium",
  "background": "transparent",
  "output_format": "png",
  "n": 1
}

Imagen a imagen (eliminar el fondo)

{
  "model": "gpt-image-2-official",
  "prompt": "Remove the background, keep only the product, isolated on a fully transparent background",
  "image_urls": ["https://your-cdn.com/product.jpg"],
  "size": "1:1",
  "resolution": "1k",
  "background": "transparent",
  "output_format": "png"
}

Póster en alta definición 2K

{
  "model": "gpt-image-2-official",
  "prompt": "Cyberpunk night scene",
  "size": "16:9",
  "resolution": "2k",
  "quality": "high",
  "output_format": "jpeg",
  "output_compression": 90
}

Fondo de pantalla 4K

{
  "model": "gpt-image-2-official",
  "prompt": "Snow mountain sunrise panorama",
  "size": "16:9",
  "resolution": "4k",
  "quality": "high",
  "n": 1
}

Imagen a imagen (fusión multireferencia)

{
  "model": "gpt-image-2-official",
  "prompt": "Fuse the two reference images into a single illustration poster, preserving the main silhouettes",
  "size": "1:1",
  "quality": "high",
  "image_urls": [
    "https://your-cdn.com/input-a.png",
    "https://your-cdn.com/input-b.png"
  ]
}

Inpainting (máscara)

{
  "model": "gpt-image-2-official",
  "prompt": "Replace the background with a desert sunset",
  "size": "1:1",
  "quality": "medium",
  "image_urls": ["https://your-cdn.com/photo.png"],
  "mask_url": "https://your-cdn.com/mask.png"
}

Múltiples imágenes (n > 1)

{
  "model": "gpt-image-2-official",
  "prompt": "Four minimalist poster variations of a red fox",
  "size": "1:1",
  "quality": "low",
  "n": 4
}

Cadena de píxeles directa (avanzado)

{
  "model": "gpt-image-2-official",
  "prompt": "wide cinematic shot",
  "size": "3840x2160",
  "quality": "high"
}

Response

integer

Código de estado de la respuesta

array

Array de datos de la respuesta

Mostrar Propiedades

string

Estado de la tarea

submitted - Enviada

string

Identificador único de la tarea, usado para consultas posteriores de resultados

Consulta de resultados de la tarea

Tras un envío correcto, se devuelve un task_id. Consulte el estado de la tarea mediante GET /v1/tasks/{task_id}, consulte la API de consulta de tareas para más detalles.

Ejemplo de respuesta exitosa

{
  "code": 200,
  "data": {
    "actual_time": 14,
    "completed": 1784607890,
    "cost": 0.004792,
    "created": 1784607876,
    "credits_cost": 0.047920000000000004,
    "estimated_time": 60,
    "id": "task_01KPTXXXXXXXXXXXXXXX",
    "progress": 100,
    "result": {
      "images": [
        {
          "expires_at": 1784694290,
          "url": [
            "https://upload.apimart.ai/f/image/xxxxxxxx-gpt_image_2_official_task_xxx_0.png"
          ]
        }
      ]
    },
    "status": "completed",
    "usage": {
      "input_tokens": 22,
      "input_tokens_details": {
        "cached_tokens": 0,
        "image_tokens": 0,
        "text_tokens": 22
      },
      "output_tokens": 196,
      "output_tokens_details": {
        "image_tokens": 196,
        "text_tokens": 0
      },
      "total_tokens": 218
    }
  }
}

El campo usage indica el consumo de tokens facturable de esta solicitud:

Campo	Descripción
`input_tokens`	Total de tokens de entrada consumidos
`input_tokens_details.cached_tokens`	Tokens de entrada servidos desde la caché
`input_tokens_details.image_tokens`	Tokens usados por las imágenes de entrada
`input_tokens_details.text_tokens`	Tokens usados por el texto de entrada (prompt)
`output_tokens`	Total de tokens de salida consumidos
`output_tokens_details.image_tokens`	Tokens usados por la imagen generada
`output_tokens_details.text_tokens`	Tokens usados por el texto de salida
`total_tokens`	Total de tokens, igual a `input_tokens` + `output_tokens`

En la generación de imágenes la salida son principalmente tokens de imagen, por lo que output_tokens_details.image_tokens suele ser igual a output_tokens. En el ejemplo anterior, total_tokens = 22 + 196 = 218. Flujo de estado de la tarea: submitted → in_progress → completed / failed. Acceso a la imagen: data.result.images[0].url[0].

Visión general

Modelos

Serie de texto

Serie de imágenes

Serie de video

Serie de audio

Serie de Moderación

Gestión de subidas

Gestión de tareas

Gestión de cuenta

Generación de imágenes con GPT-Image-2 canal oficial

Autorizaciones

Body

Mapeo Size × Resolution

Ejemplos de uso

Response

Consulta de resultados de la tarea

Ejemplo de respuesta exitosa

​Autorizaciones

​Body

​Mapeo Size × Resolution

​Ejemplos de uso

​Response

​Consulta de resultados de la tarea

​Ejemplo de respuesta exitosa

Autorizaciones

Body

Mapeo Size × Resolution

Ejemplos de uso

Response

Consulta de resultados de la tarea

Ejemplo de respuesta exitosa