# model には "gpt-image-2" を指定でき、エイリアス "gpt-image-2-ext" にも対応しています
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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" => "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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"": ""窓辺に座って夕日を見つめる茶トラ猫、水彩画風"",
""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': '窓辺に座って夕日を見つめる茶トラ猫、水彩画風',
'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 = "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "パラメータエラー:size が不正 / resolution が未対応 / ピクセル違反など",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "認証に失敗しました。API キーをご確認ください",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "アカウント残高が不足しています。チャージ後に再試行してください",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "リクエストが多すぎます。しばらくしてから再試行してください",
"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": "上流が一時的に利用できません。しばらくしてから再試行してください",
"type": "service_unavailable"
}
}
GPT-Image-2
GPT-Image-2 画像生成
-
非同期処理モード、後続のクエリ用にタスクIDを返します
-
OpenAI Images 互換プロトコルに基づき、テキストから画像 / 画像から画像をサポート
-
sizeフィールドで 15 種類の比率をサポート -
resolution(1k/2k/4k)で実際の出力ピクセル段階を制御 -
参照画像は最大 16 枚、URL と base64 の混在をサポート
-
解像度段階(1K / 2K / 4K)に応じて課金
POST
/
v1
/
images
/
generations
# model には "gpt-image-2" を指定でき、エイリアス "gpt-image-2-ext" にも対応しています
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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" => "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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"": ""窓辺に座って夕日を見つめる茶トラ猫、水彩画風"",
""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': '窓辺に座って夕日を見つめる茶トラ猫、水彩画風',
'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 = "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "パラメータエラー:size が不正 / resolution が未対応 / ピクセル違反など",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "認証に失敗しました。API キーをご確認ください",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "アカウント残高が不足しています。チャージ後に再試行してください",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "リクエストが多すぎます。しばらくしてから再試行してください",
"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": "上流が一時的に利用できません。しばらくしてから再試行してください",
"type": "service_unavailable"
}
}
モデル名互換のお知らせ:本エンドポイントはエイリアス
gpt-image-2-ext にも対応しており、gpt-image-2 と同等です。両者は互換的に使用でき、効果は同一です。# model には "gpt-image-2" を指定でき、エイリアス "gpt-image-2-ext" にも対応しています
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.apimart.ai/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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" => "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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: "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
"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"": ""窓辺に座って夕日を見つめる茶トラ猫、水彩画風"",
""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': '窓辺に座って夕日を見つめる茶トラ猫、水彩画風',
'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 = "窓辺に座って夕日を見つめる茶トラ猫、水彩画風",
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": "パラメータエラー:size が不正 / resolution が未対応 / ピクセル違反など",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "認証に失敗しました。API キーをご確認ください",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "アカウント残高が不足しています。チャージ後に再試行してください",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "リクエストが多すぎます。しばらくしてから再試行してください",
"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": "上流が一時的に利用できません。しばらくしてから再試行してください",
"type": "service_unavailable"
}
}
Authorizations
すべてのエンドポイントは Bearer Token による認証が必要ですAPI キーの取得:API キー管理ページ にアクセスして API キーを取得してください使用時はリクエストヘッダーに以下を追加:
Authorization: Bearer YOUR_API_KEY
Body
画像生成モデル名
gpt-image-2 に固定(エイリアス gpt-image-2-ext に対応)旧バージョンの呼び出しとの互換性のため、エイリアス
gpt-image-2-ext(gpt-image-2 に対応)は引き続き正常に使用できます。画像生成のテキスト記述
- 日本語・英語・中国語をサポート、詳細な記述を推奨
- 送信前にプラットフォームのセンシティブワード / セーフティレビューを通過します。違反内容は即座にエラーを返します
生成する画像の枚数範囲:
1 - 10必ず数値(例:
1)を入力してください。引用符で囲まないでください画像生成の比率以下の比率をサポート、
auto を渡すとサーバー側で適切な比率を自動選択します:| size | タイプ |
|---|---|
auto | 自動 |
1:1 | 正方形 |
3:2 | 横 |
2:3 | 縦 |
4:3 | 横 |
3:4 | 縦 |
5:4 | 横 |
4:5 | 縦 |
16:9 | 横 |
9:16 | 縦 |
2:1 | 横 |
1:2 | 縦 |
3:1 | 横 |
1:3 | 縦 |
21:9 | 横 |
9:21 | 縦 |
1881x836 / 887x1774 のようなピクセルサイズも直接指定できます。size に auto を指定した場合、デフォルトの比率は 1:1 です。出力解像度の段階選択肢:
1k / 2k / 4ksize × resolution → 実際のピクセル対応:| 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 |
4K は上記 15 種類の比率をサポートします。表内のピクセルサイズを
size で直接指定することもできます。参照画像配列(OpenAI 標準フィールド)。渡すと画像から画像モードに切り替わります
表示 詳細
表示 詳細
- 参照画像は最大 16 枚。超過すると
image_urls exceeds max 16が返ります - 1 枚あたり最大 20MB、合計上限 256MB
画像 URL(公開アクセス可能な安定したリンク)をサポートbase64 data URI(例:data:image/png;base64,...)をサポート- 同じ配列内で URL と base64 を混在可能、サーバー側で処理します
sizeを渡さない場合、出力解像度 = 入力画像の解像度。sizeを渡すと指定サイズに強制
その他の OpenAI 標準フィールド(
response_format、style など)は現在サポートされておらず、無視されます。タスク結果は url のみを返します。base64 が必要な場合はご自身でダウンロードして変換してください。公式チャネルをフォールバックとして使用するかどうか
false:使用しない(デフォルト)true:公式チャネルを使用
使用シナリオ例
テキストから画像(最小リクエスト){
"model": "gpt-image-2",
"prompt": "窓辺に座って夕日を見つめる茶トラ猫、水彩画風"
}
{
"model": "gpt-image-2",
"prompt": "a corgi astronaut on the moon, cinematic, 8k",
"size": "16:9",
"resolution": "2k"
}
{
"model": "gpt-image-2",
"prompt": "星空の下の古城",
"size": "16:9",
"resolution": "4k"
}
{
"model": "gpt-image-2",
"prompt": "星空の下の古城",
"size": "16:9",
"resolution": "4k",
"n": 2
}
{
"model": "gpt-image-2",
"prompt": "この写真を水彩画風に変換",
"image_urls": [
"https://example.com/photo.jpg"
]
}
{
"model": "gpt-image-2",
"prompt": "この写真を水彩画風に変換",
"image_urls": [
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
{
"model": "gpt-image-2",
"prompt": "この 2 枚の写真を 1 枚のポスターに融合",
"size": "4:3",
"resolution": "2k",
"image_urls": [
"https://example.com/photo-a.jpg",
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
Response
レスポンスステータスコード
タスク結果のクエリ
提出成功後にtask_id が返されます。GET /v1/tasks/{task_id} でタスク状態をポーリングしてください。詳細は タスククエリ API を参照。
成功レスポンス例
{
"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]
タスクステータス
| ステータス | 意味 |
|---|---|
submitted | 提出済み |
processing | 上流で処理中 |
completed | 成功、result.images 利用可能 |
failed | 失敗、error.message を確認 |
⌘I