# El campo model puede ser "gpt-image-2" o el alias compatible "gpt-image-2-ext"
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
};
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k",
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
""";
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",
"prompt" => "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n" => 1,
"size" => "16:9",
"resolution" => "2k"
];
$ch = curl_init($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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
]
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"",
""prompt"": ""A ginger cat sitting on a windowsill watching the sunset, watercolor style"",
""n"": 1,
""size"": ""16:9"",
""resolution"": ""2k""
}";
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',
'prompt': 'A ginger cat sitting on a windowsill watching the sunset, watercolor style',
'n': 1,
'size': '16:9',
'resolution': '2k'
};
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",
prompt = "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n = 1,
size = "16:9",
resolution = "2k"
)
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_01KPQ7J7DWB7QZ3WCEK3YVPBRA"
}
]
}
{
"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": 429,
"message": "Too many requests, please try again later",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "build_request_failed: invalid size: 3:5, allowed: 1:1 / 16:9 / 9:16 / 4:3 / 3:4 / 3:2 / 2:3 / 5:4 / 4:5 / 2:1 / 1:2 / 3:1 / 1:3 / 21:9 / 9:21",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "Upstream temporarily unavailable, please try again later",
"type": "service_unavailable"
}
}
GPT-Image-2
Generación de imágenes con GPT-Image-2
-
Modo de procesamiento asíncrono, devuelve un ID de tarea para consultas posteriores
-
Protocolo compatible con OpenAI Images, admite texto a imagen / imagen a imagen
-
15 proporciones de imagen admitidas mediante el campo
size -
Nivel de píxeles de salida controlado mediante
resolution(1k/2k/4k) -
Hasta 16 imágenes de referencia, URL y base64 pueden combinarse
-
Facturación por nivel de resolución (1K / 2K / 4K)
POST
/
v1
/
images
/
generations
# El campo model puede ser "gpt-image-2" o el alias compatible "gpt-image-2-ext"
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
};
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k",
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
""";
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",
"prompt" => "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n" => 1,
"size" => "16:9",
"resolution" => "2k"
];
$ch = curl_init($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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
]
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"",
""prompt"": ""A ginger cat sitting on a windowsill watching the sunset, watercolor style"",
""n"": 1,
""size"": ""16:9"",
""resolution"": ""2k""
}";
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',
'prompt': 'A ginger cat sitting on a windowsill watching the sunset, watercolor style',
'n': 1,
'size': '16:9',
'resolution': '2k'
};
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",
prompt = "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n = 1,
size = "16:9",
resolution = "2k"
)
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_01KPQ7J7DWB7QZ3WCEK3YVPBRA"
}
]
}
{
"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": 429,
"message": "Too many requests, please try again later",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "build_request_failed: invalid size: 3:5, allowed: 1:1 / 16:9 / 9:16 / 4:3 / 3:4 / 3:2 / 2:3 / 5:4 / 4:5 / 2:1 / 1:2 / 3:1 / 1:3 / 21:9 / 9:21",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "Upstream temporarily unavailable, please try again later",
"type": "service_unavailable"
}
}
Aviso de compatibilidad de nombres de modelo: Esta interfaz también admite el alias
gpt-image-2-ext, equivalente a gpt-image-2; ambos son intercambiables y producen los mismos resultados.# El campo model puede ser "gpt-image-2" o el alias compatible "gpt-image-2-ext"
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
};
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k",
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
}
""";
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",
"prompt" => "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n" => 1,
"size" => "16:9",
"resolution" => "2k"
];
$ch = curl_init($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",
prompt: "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n: 1,
size: "16:9",
resolution: "2k"
}
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",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
"n": 1,
"size": "16:9",
"resolution": "2k"
]
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"",
""prompt"": ""A ginger cat sitting on a windowsill watching the sunset, watercolor style"",
""n"": 1,
""size"": ""16:9"",
""resolution"": ""2k""
}";
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',
'prompt': 'A ginger cat sitting on a windowsill watching the sunset, watercolor style',
'n': 1,
'size': '16:9',
'resolution': '2k'
};
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",
prompt = "A ginger cat sitting on a windowsill watching the sunset, watercolor style",
n = 1,
size = "16:9",
resolution = "2k"
)
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_01KPQ7J7DWB7QZ3WCEK3YVPBRA"
}
]
}
{
"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": 429,
"message": "Too many requests, please try again later",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "build_request_failed: invalid size: 3:5, allowed: 1:1 / 16:9 / 9:16 / 4:3 / 3:4 / 3:2 / 2:3 / 5:4 / 4:5 / 2:1 / 1:2 / 3:1 / 1:3 / 21:9 / 9:21",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "Upstream temporarily unavailable, please try again later",
"type": "service_unavailable"
}
}
Autorizaciones
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
Nombre del modelo de generación de imágenesFijo en
gpt-image-2 (alias compatible gpt-image-2-ext)Para mantener la compatibilidad con llamadas anteriores, el alias
gpt-image-2-ext (corresponde a gpt-image-2) sigue estando disponible.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
Número de imágenes a generarRango:
1 - 10Debe ser un número puro (p. ej.,
1), no lo envuelva en comillasProporción de la imagenProporciones admitidas, más
También pueden pasarse dimensiones en píxeles directamente, como
auto para dejar que el servidor elija una proporción adecuada automáticamente:| size | Tipo |
|---|---|
auto | Automático |
1:1 | Cuadrada |
3:2 | Horizontal |
2:3 | Vertical |
4:3 | Horizontal |
3:4 | Vertical |
5:4 | Horizontal |
4:5 | Vertical |
16:9 | Horizontal |
9:16 | Vertical |
2:1 | Horizontal |
1:2 | Vertical |
3:1 | Horizontal |
1:3 | Vertical |
21:9 | Horizontal |
9:21 | Vertical |
1881x836 / 887x1774.Cuando
size se establece en auto, la proporción predeterminada es 1:1.Nivel de resolución de salidaOpciones:
1k / 2k / 4kMapeo size × resolution → píxeles reales:| size | 1k | 2k | 4k |
|---|---|---|---|
1:1 | 1024×1024 / 1254×1254 | 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 / 1448×1086 | 2560×2048 | 3216×2576 |
4:5 | 1024×1280 / 1122×1402 | 2048×2560 | 2576×3216 |
16:9 | 1536×864 / 1672×941 | 2048×1152 | 3840×2160 |
9:16 | 864×1536 / 941×1672 | 1152×2048 | 2160×3840 |
2:1 | 2048×1024 / 1774×887 | 2688×1344 | 3840×1920 |
1:2 | 1024×2048 / 887×1774 | 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 / 1915×821 | 2688×1152 | 3840×1648 |
9:21 | 864×2016 / 821×1915 | 1152×2688 | 1648×3840 |
El 4K admite las 15 proporciones listadas arriba; también puede pasar las dimensiones en píxeles de la tabla directamente mediante
size.Array de imágenes de referencia (campo estándar de OpenAI). Cambia al modo imagen a imagen cuando se proporciona.
Mostrar Detalles
Mostrar Detalles
- Hasta 16 imágenes de referencia, excederlas devuelve
image_urls exceeds max 16 - Máximo 20 MB por imagen, 256 MB en total
- Admite
URL de imagen(enlace público estable) - Admite
data URI base64(p. ej.data:image/png;base64,...) - URL y base64 pueden combinarse en el mismo array, gestionado por el servidor
- Sin
size, la resolución de salida = resolución de la imagen de entrada; consize, la salida se fuerza a la proporción especificada
Otros campos estándar de OpenAI (
response_format, style) no son compatibles y serán ignorados. Los resultados de las tareas solo devuelven url — descargue y convierta a base64 usted mismo si lo necesita.Si recurrir al canal oficial como fallback
false: No usar (predeterminado)true: Usar el canal oficial
Ejemplos de uso
Texto a imagen (solicitud mínima){
"model": "gpt-image-2",
"prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style"
}
{
"model": "gpt-image-2",
"prompt": "a corgi astronaut on the moon, cinematic, 8k",
"size": "16:9",
"resolution": "2k"
}
{
"model": "gpt-image-2",
"prompt": "An ancient castle under a starry sky",
"size": "16:9",
"resolution": "4k"
}
{
"model": "gpt-image-2",
"prompt": "An ancient castle under a starry sky",
"size": "16:9",
"resolution": "4k",
"n": 2
}
{
"model": "gpt-image-2",
"prompt": "Turn this photo into a watercolor painting",
"image_urls": [
"https://example.com/photo.jpg"
]
}
{
"model": "gpt-image-2",
"prompt": "Turn this photo into a watercolor painting",
"image_urls": [
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
{
"model": "gpt-image-2",
"prompt": "Fuse these two photos into a single poster",
"size": "4:3",
"resolution": "2k",
"image_urls": [
"https://example.com/photo-a.jpg",
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
Response
Código de estado de la respuesta
Consulta de resultados de la tarea
Tras un envío correcto, se devuelve untask_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": {
"id": "task_01KPQ7J7DWB7QZ3WCEK3YVPBRA",
"status": "completed",
"progress": 100,
"created": 1776748674,
"completed": 1776748726,
"actual_time": 52,
"cost": 0.05279,
"credits_cost": 0.5279,
"estimated_time": 100,
"result": {
"images": [
{
"url": [
"https://upload.apimart.ai/f/image/xxxxxxxx-gpt_image_2_task_xxx_0.png"
],
"expires_at": 1776835126
}
]
}
}
}
data.result.images[0].url[0]
Estado de la tarea
| Estado | Significado |
|---|---|
submitted | Enviada |
processing | Procesándose en el upstream |
completed | Éxito, result.images disponible |
failed | Falló, compruebe error.message |
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