# model 可填 "gpt-image-2",也兼容别名 "gpt-image-2-ext"
curl --request POST \
--url https://api.tokengongfang.com/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.tokengongfang.com/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
const payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations"
payload := map[string]interface{}{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
String payload = """
{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
$payload = [
"model" => "gpt-image-2",
"prompt" => "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations")
payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations")!
let payload: [String: Any] = [
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
var payload = @"{
""model"": ""gpt-image-2"",
""prompt"": ""一只橘猫坐在窗台上看夕阳,水彩画风格"",
""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.tokengongfang.com/v1/images/generations');
final payload = {
'model': 'gpt-image-2',
'prompt': '一只橘猫坐在窗台上看夕阳,水彩画风格',
'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.tokengongfang.com/v1/images/generations"
payload <- list(
model = "gpt-image-2",
prompt = "一只橘猫坐在窗台上看夕阳,水彩画风格",
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": "参数错误:size 不合法 / resolution 不支持 / 像素违规等",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器错误",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "上游暂时不可用,请稍后再试",
"type": "service_unavailable"
}
}
GPT-Image-2
GPT-Image-2 图像生成
- 异步处理模式,返回任务ID用于后续查询
- 基于 OpenAI Images 兼容协议,支持文生图 / 图生图
- 支持 15 种图片比例,通过
size字段传入 - 通过
resolution(1k/2k/4k)控制实际输出像素档位 - 参考图最多 16 张,支持 URL 与 base64 混填
- 按分辨率档位(1K / 2K / 4K)计费
POST
/
v1
/
images
/
generations
# model 可填 "gpt-image-2",也兼容别名 "gpt-image-2-ext"
curl --request POST \
--url https://api.tokengongfang.com/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.tokengongfang.com/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
const payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations"
payload := map[string]interface{}{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
String payload = """
{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
$payload = [
"model" => "gpt-image-2",
"prompt" => "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations")
payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations")!
let payload: [String: Any] = [
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
var payload = @"{
""model"": ""gpt-image-2"",
""prompt"": ""一只橘猫坐在窗台上看夕阳,水彩画风格"",
""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.tokengongfang.com/v1/images/generations');
final payload = {
'model': 'gpt-image-2',
'prompt': '一只橘猫坐在窗台上看夕阳,水彩画风格',
'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.tokengongfang.com/v1/images/generations"
payload <- list(
model = "gpt-image-2",
prompt = "一只橘猫坐在窗台上看夕阳,水彩画风格",
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": "参数错误:size 不合法 / resolution 不支持 / 像素违规等",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器错误",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "上游暂时不可用,请稍后再试",
"type": "service_unavailable"
}
}
模型名兼容提示:本接口同时兼容别名
gpt-image-2-ext,它等价于 gpt-image-2,两者可互换使用、效果一致。# model 可填 "gpt-image-2",也兼容别名 "gpt-image-2-ext"
curl --request POST \
--url https://api.tokengongfang.com/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"n": 1,
"size": "16:9",
"resolution": "2k"
}'
import requests
url = "https://api.tokengongfang.com/v1/images/generations"
payload = {
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
const payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations"
payload := map[string]interface{}{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
String payload = """
{
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
$payload = [
"model" => "gpt-image-2",
"prompt" => "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations")
payload = {
model: "gpt-image-2",
prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
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.tokengongfang.com/v1/images/generations")!
let payload: [String: Any] = [
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
"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.tokengongfang.com/v1/images/generations";
var payload = @"{
""model"": ""gpt-image-2"",
""prompt"": ""一只橘猫坐在窗台上看夕阳,水彩画风格"",
""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.tokengongfang.com/v1/images/generations');
final payload = {
'model': 'gpt-image-2',
'prompt': '一只橘猫坐在窗台上看夕阳,水彩画风格',
'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.tokengongfang.com/v1/images/generations"
payload <- list(
model = "gpt-image-2",
prompt = "一只橘猫坐在窗台上看夕阳,水彩画风格",
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": "参数错误:size 不合法 / resolution 不支持 / 像素违规等",
"type": "invalid_request_error"
}
}
{
"error": {
"code": 401,
"message": "身份验证失败,请检查您的API密钥",
"type": "authentication_error"
}
}
{
"error": {
"code": 402,
"message": "账户余额不足,请充值后再试",
"type": "payment_required"
}
}
{
"error": {
"code": 429,
"message": "请求过于频繁,请稍后再试",
"type": "rate_limit_error"
}
}
{
"error": {
"code": 500,
"message": "服务器错误",
"type": "server_error"
}
}
{
"error": {
"code": 503,
"message": "上游暂时不可用,请稍后再试",
"type": "service_unavailable"
}
}
Authorizations
所有接口均需要使用 Bearer Token 进行认证获取 API Key:访问 API Key 管理页面 获取您的 API Key使用时在请求头中添加:
Authorization: Bearer YOUR_API_KEY
Body
图像生成模型名称固定填写
gpt-image-2(兼容别名 gpt-image-2-ext)为兼容旧版调用,别名
gpt-image-2-ext(对应 gpt-image-2)仍可正常使用。图像生成的文本描述
- 支持中英文,建议详细描述
- 提交前会经过平台敏感词 / 安全审核,命中违规内容会直接返回错误
生成图片张数取值范围:1 - 10
必须传入纯数字(如
1),不要加引号图像生成的比例支持以下比例,也可传入
也支持直接传入像素尺寸,例如
auto 由服务端自动选择合适比例:| size | 类型 |
|---|---|
auto | 自动 |
1:1 | 正方 |
3:2 | 横图 |
2:3 | 竖图 |
4:3 | 横图 |
3:4 | 竖图 |
5:4 | 横图 |
4:5 | 竖图 |
16:9 | 横图 |
9:16 | 竖图 |
2:1 | 横图 |
1:2 | 竖图 |
3:1 | 横图 |
1:3 | 竖图 |
21:9 | 横图 |
9:21 | 竖图 |
1881x836 / 887x1774。当
size 传入 auto 时,默认比例为 1:1。输出分辨率档位可选值:
1k / 2k / 4ksize × resolution → 实际像素对应关系:| 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 支持上述 15 个比例;也可以直接通过
size 传入表格中的像素尺寸。参考图数组(OpenAI 标准字段),传入后走图生图模式
显示 详细说明
显示 详细说明
- 最多 16 张参考图,超过会返回
image_urls exceeds max 16 - 单张图最大 20M,总体上限 256M
- 支持
图片 URL(公网可访问的稳定链接) - 支持
base64 data URI(形如data:image/png;base64,...) - 同一数组里可以 URL 与 base64 混填,服务端会自行处理
- 不传
size时输出分辨率 = 输入图分辨率;传size则强制按指定尺寸出图
其它 OpenAI 标准字段(
response_format、style)不支持,会被忽略。任务结果只返回 url——如需 base64 请自行下载转换。是否使用官方渠道兜底
false:不使用(默认)true:使用官方渠道
使用场景示例
文生图(最简请求){
"model": "gpt-image-2",
"prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格"
}
{
"model": "gpt-image-2",
"prompt": "a corgi astronaut on the moon, cinematic, 8k",
"size": "16:9",
"resolution": "2k"
}
{
"model": "gpt-image-2",
"prompt": "星空下的古老城堡",
"size": "16:9",
"resolution": "4k"
}
{
"model": "gpt-image-2",
"prompt": "星空下的古老城堡",
"size": "16:9",
"resolution": "4k",
"n": 2
}
{
"model": "gpt-image-2",
"prompt": "把这张照片变成水彩画风格",
"image_urls": [
"https://example.com/photo.jpg"
]
}
{
"model": "gpt-image-2",
"prompt": "把这张照片变成水彩画风格",
"image_urls": [
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
{
"model": "gpt-image-2",
"prompt": "把这两张照片融合成一张海报",
"size": "4:3",
"resolution": "2k",
"image_urls": [
"https://example.com/photo-a.jpg",
"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
]
}
Response
响应状态码
查询任务结果
提交成功后返回task_id,通过 GET /v1/tasks/{task_id} 轮询任务状态,详见 任务查询接口。
成功响应示例
{
"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]
任务状态说明
| 状态 | 含义 |
|---|---|
submitted | 已提交 |
processing | 上游处理中 |
completed | 成功,result.images 可用 |
failed | 失败,查看 error.message |
⌘I