# model pode ser "gpt-image-2", também compatível com o alias "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
Geração de imagens GPT-Image-2
-
Modo de processamento assíncrono, retorna ID da tarefa para consultas posteriores
-
Protocolo compatível com OpenAI Images, suporta texto para imagem / imagem para imagem
-
15 proporções de imagem suportadas via o campo
size -
Nível de pixels de saída controlado via
resolution(1k/2k/4k) -
Até 16 imagens de referência, URL e base64 podem ser combinados
-
Cobrança por nível de resolução (1K / 2K / 4K)
POST
/
v1
/
images
/
generations
# model pode ser "gpt-image-2", também compatível com o alias "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 compatibilidade de nome de modelo: esta interface também é compatível com o alias
gpt-image-2-ext, que é equivalente a gpt-image-2; ambos podem ser usados de forma intercambiável e produzem o mesmo resultado.# model pode ser "gpt-image-2", também compatível com o alias "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"
}
}
Autorizações
Todos os endpoints requerem autenticação por Bearer TokenObtenha sua chave de API:Acesse a página de gerenciamento de chaves de API para obter sua chave de APIInclua-a no cabeçalho da requisição:
Authorization: Bearer YOUR_API_KEY
Body
Nome do modelo de geração de imagensFixo em
gpt-image-2 (alias compatível gpt-image-2-ext)Para compatibilidade com chamadas de versões anteriores, o alias
gpt-image-2-ext (correspondente a gpt-image-2) continua podendo ser usado normalmente.Descrição textual para a geração da imagem
- Suporta inglês e chinês, descrições detalhadas são recomendadas
- Moderação de conteúdo / revisão de segurança antes do envio — violações são rejeitadas imediatamente
Número de imagens a serem geradasIntervalo:
1 - 10Deve ser um número puro (ex.:
1), não envolva em aspasProporção da imagemProporções suportadas, além de
Dimensões em pixels também podem ser passadas diretamente, como
auto para deixar o servidor escolher uma proporção adequada automaticamente:| size | Tipo |
|---|---|
auto | Automático |
1:1 | Quadrado |
3:2 | Paisagem |
2:3 | Retrato |
4:3 | Paisagem |
3:4 | Retrato |
5:4 | Paisagem |
4:5 | Retrato |
16:9 | Paisagem |
9:16 | Retrato |
2:1 | Paisagem |
1:2 | Retrato |
3:1 | Paisagem |
1:3 | Retrato |
21:9 | Paisagem |
9:21 | Retrato |
1881x836 / 887x1774.Quando
size é definido como auto, a proporção padrão é 1:1.Nível de resolução de saídaOpções:
1k / 2k / 4kMapeamento size × resolution → pixels reais:| 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 |
O 4K suporta as 15 proporções listadas acima; você também pode passar as dimensões em pixels da tabela diretamente via
size.Array de imagens de referência (campo padrão OpenAI). Alterna para o modo imagem para imagem quando fornecido.
Mostrar Detalhes
Mostrar Detalhes
- Até 16 imagens de referência, exceder retorna
image_urls exceeds max 16 - Máximo de 20 MB por imagem, 256 MB no total
- Suporta
URL de imagem(link público estável) - Suporta
data URI base64(ex.:data:image/png;base64,...) - URL e base64 podem ser combinados no mesmo array, processado pelo servidor
- Sem
size, a resolução de saída = resolução da imagem de entrada; comsize, a saída é forçada à proporção especificada
Outros campos padrão da OpenAI (
response_format, style) não são suportados e serão ignorados. Os resultados das tarefas retornam apenas url — faça você mesmo o download e converta para base64 se necessário.Se deve recorrer ao canal oficial como fallback
false: Não usar (padrão)true: Usar o canal oficial
Exemplos de uso
Texto para imagem (requisição 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 status da resposta
Consulta de resultados da tarefa
Após o envio bem-sucedido, umtask_id é retornado. Consulte o status da tarefa via GET /v1/tasks/{task_id}, veja API de consulta de tarefas para mais detalhes.
Exemplo de resposta de sucesso
{
"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]
Status da tarefa
| Status | Significado |
|---|---|
submitted | Enviada |
processing | Sendo processada no upstream |
completed | Sucesso, result.images disponível |
failed | Falhou, verifique error.message |
⌘I