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

import requests

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

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

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

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

print(response.json())

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

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

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

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

package main

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

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

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

    jsonData, _ := json.Marshal(payload)

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

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

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

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

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

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

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

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

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

<?php

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

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

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

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

echo $response;
?>

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

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

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

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

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

import Foundation

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

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

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

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

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

task.resume()

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

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

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

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

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

        Console.WriteLine(result);
    }
}

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

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

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

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

  print(response.body);
}

library(httr)
library(jsonlite)

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

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

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

cat(content(response, "text"))

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

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

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

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

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

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

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

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

GPT-Image-2

GPT-Image-2 Bildgenerierung (offizieller Kanal)

OpenAI-offizielles Modell gpt-image-2, basierend auf dem mit /v1/images/generations kompatiblen Protokoll
Asynchrone Verarbeitung, gibt task_id für nachfolgende Abfragen zurück
Text-zu-Bild / Bild-zu-Bild / Inpainting (Maske) — alles in einem
Unterstützt transparente Hintergründe in PNG / WebP (Alphakanal)
Neues Feld resolution für die Stufe — Auswahl 1K / 2K / 4K
15 Seitenverhältnisse in den Stufen 1K / 2K / 4K verfügbar
Bis zu 4 Bilder pro Anfrage, bis zu 16 Referenzbilder
95 % Parameter-Übereinstimmung mit gpt-image-1.5-official — für die Migration genügt eine Änderung des Modellnamens

POST

images

generations

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

import requests

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

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

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

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

print(response.json())

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

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

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

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

package main

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

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

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

    jsonData, _ := json.Marshal(payload)

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

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

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

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

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

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

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

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

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

<?php

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

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

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

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

echo $response;
?>

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

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

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

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

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

import Foundation

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

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

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

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

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

task.resume()

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

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

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

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

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

        Console.WriteLine(result);
    }
}

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

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

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

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

  print(response.body);
}

library(httr)
library(jsonlite)

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

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

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

cat(content(response, "text"))

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

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

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

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

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

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

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

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

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

import requests

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

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

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

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

print(response.json())

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

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

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

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

package main

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

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

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

    jsonData, _ := json.Marshal(payload)

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

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

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

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

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

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

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

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

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

<?php

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

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

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

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

echo $response;
?>

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

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

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

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

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

import Foundation

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

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

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

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

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

task.resume()

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

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

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

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

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

        Console.WriteLine(result);
    }
}

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

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

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

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

  print(response.body);
}

library(httr)
library(jsonlite)

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

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

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

cat(content(response, "text"))

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

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

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

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

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

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

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

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

Autorisierung

string

erforderlich

Alle Endpunkte erfordern eine Authentifizierung per Bearer TokenAPI-Schlüssel erhalten:Besuchen Sie die Seite zur Verwaltung von API-Schlüsseln, um Ihren API-Schlüssel zu erhaltenFügen Sie ihn in den Anfrage-Header ein:

Authorization: Bearer YOUR_API_KEY

Body

string

Standard:"gpt-image-2-official"

erforderlich

Name des BildgenerierungsmodellsFest auf gpt-image-2-official (offizielles OpenAI-Modell gpt-image-2) gesetzt

boolean

Standard:"false"

Legt fest, ob der Inhalt vor dem Absenden des Bildauftrags moderiert wird.

true: Prompts und Eingabebilder mit omni-moderation-latest prüfen
false oder nicht angegeben: keine Moderationsanfrage und damit keine zusätzlichen Moderationskosten oder Verzögerung (Standard)

string

erforderlich

Textbeschreibung für die Bildgenerierung

Unterstützt Englisch und Chinesisch, detaillierte Beschreibungen werden empfohlen
Inhaltsmoderation / Sicherheitsprüfung vor dem Einreichen — Verstöße werden sofort abgelehnt

string

Standard:"1:1"

Seitenverhältnis des BildesExtern werden Verhältniswerte verwendet; intern werden sie gemäß resolution automatisch auf tatsächliche Pixel abgebildet.Unterstützte Seitenverhältnisse, plus auto, damit der Server automatisch ein passendes Verhältnis auswählt:

auto – Automatisch (Server wählt ein Verhältnis basierend auf Prompt / Referenzbildern)
1:1 – Quadrat (Standard, Social-Avatare / Logos)
3:2 – Querformat (gängiges DSLR-Verhältnis)
2:3 – Hochformat (vertikale Poster)
4:3 – Querformat (klassischer Monitor / Diashow)
3:4 – Hochformat
5:4 – Querformat
4:5 – Hochformat (Instagram-Hochformat-Post)
16:9 – Querformat (Breitbild-Video-Thumbnail)
9:16 – Hochformat (Telefon-Vollbild / Short-Video-Cover)
2:1 – Querformat (Web-Banner)
1:2 – Hochformat
3:1 – Querformat (ultrabreiter Banner)
1:3 – Hochformat (extra hohes Poster)
21:9 – Querformat (Kinoformat ultrabreit)
9:21 – Hochformat

Pixelabmessungen können auch direkt übergeben werden, z. B. 1881x836 / 887x1774.

Wenn size auf auto gesetzt ist, beträgt das Standardverhältnis 1:1.

string

Standard:"1k"

Auflösungsstufe (neues Feld)Steuert die tatsächliche Ausgabeschärfe.

1k – Basis 1024, kosteneffizient für den täglichen Einsatz (Standard)
2k – Basis 2048, geeignet für Poster / Anforderungen an hohe Auflösung
4k – Basis 3840, unterstützt die 15 Verhältnisse in der Zuordnungstabelle unten

4K unterstützt die 15 Verhältnisse in der Zuordnungstabelle unten; Sie können die Pixelabmessungen aus der Tabelle auch direkt über size übergeben.

string

Standard:"auto"

Bildqualität

auto – Automatisch (Standard, typischerweise gleichwertig mit low)
low – Schnell und sparsam, ausreichend für grobe Umrisse
medium – Ausgewogen
high – Höchste Präzision (4K + high kann über 120 s dauern)

string

Standard:"auto"

Hintergrundmodus

auto – Automatisch (Standard)
opaque – Undurchsichtig
transparent – Fordert einen transparenten Hintergrund an; die Ausgabe enthält einen Alphakanal

string

Standard:"auto"

Moderationsstärke

auto – Standard-Moderationsstärke
low – Mildere Moderation

string

Standard:"png"

Ausgabeformat

png – Standardformat, unterstützt transparente Hintergründe
jpeg – Kleinere Dateien, unterstützt keinen Alphakanal
webp – Unterstützt transparente Hintergründe, geeignet für moderne Browser

Wenn background auf transparent gesetzt ist, kann nur png oder webp ausgewählt werden.

integer

Ausgabe-Kompressionsstufe, Bereich 0–100

Nur für jpeg / webp wirksam

integer

Standard:"1"

Anzahl der zu generierenden BilderBereich: 1 ~ 4

Muss eine reine Zahl sein (z. B. 1), nicht in Anführungszeichen setzen

array

Array mit Referenzbild-URLs

Anzeigen Details

Max. 20 MB pro Bild, Gesamtobergrenze 256 MB
Bis zu 16 Referenzbilder; mehr wird abgelehnt
Müssen öffentlich zugängliche, stabile Bild-URLs sein

string

Masken-Bild-URL, für Inpainting verwendet

Muss zusammen mit image_urls verwendet werden

Stellen Sie vor dem Hochladen sicher, dass das Maskenbild einen Alphakanal besitzt.
Die Abmessungen des Maskenbildes müssen mit dem ersten Referenzbild übereinstimmen.

Size × Resolution Zuordnung

size × resolution → tatsächliche OpenAI-Pixel (15 Verhältnisse × 3 Stufen):

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

Hinweis: Einige Abmessungen sind auf Vielfache von 16 und Pixelgrenzen angenähert, z. B. 3:2 / 2:3 @ 2K mit 2048×1360 und 21:9 @ 4K mit 3840×1648. Als verbindliche Quelle gelten die tatsächlichen Pixel in der Tabelle.

Anwendungsbeispiele

Text-zu-Bild (minimale Anfrage)

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

Text-zu-Bild (transparenter Sticker)

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

Bild-zu-Bild (Hintergrund entfernen)

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

2K-Hochauflösungsposter

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

4K-Hintergrundbild

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

Bild-zu-Bild (Mehrfachreferenz-Fusion)

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

Inpainting (Maske)

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

Mehrere Bilder (n > 1)

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

Direkte Pixel-Zeichenkette (fortgeschritten)

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

Response

integer

Statuscode der Antwort

array

Array mit Antwortdaten

Anzeigen Eigenschaften

string

Aufgabenstatus

submitted – Eingereicht

string

Eindeutige Aufgabenkennung, wird für nachfolgende Ergebnisabfragen verwendet

Abfrage der Aufgabenergebnisse

Nach erfolgreicher Einreichung wird eine task_id zurückgegeben. Pollen Sie den Aufgabenstatus über GET /v1/tasks/{task_id}, siehe API zur Aufgabenabfrage für Details.

Beispiel einer erfolgreichen Antwort

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

Das Feld usage gibt den abrechenbaren Token-Verbrauch dieser Anfrage an:

Feld	Beschreibung
`input_tokens`	Insgesamt verbrauchte Eingabe-Tokens
`input_tokens_details.cached_tokens`	Aus dem Cache bediente Eingabe-Tokens
`input_tokens_details.image_tokens`	Von Eingabebildern verwendete Tokens
`input_tokens_details.text_tokens`	Von Eingabetext (Prompt) verwendete Tokens
`output_tokens`	Insgesamt verbrauchte Ausgabe-Tokens
`output_tokens_details.image_tokens`	Vom generierten Bild verwendete Tokens
`output_tokens_details.text_tokens`	Vom Ausgabetext verwendete Tokens
`total_tokens`	Gesamtanzahl der Tokens, entspricht `input_tokens` + `output_tokens`

Bei der Bildgenerierung besteht die Ausgabe hauptsächlich aus Bild-Tokens, daher entspricht output_tokens_details.image_tokens in der Regel output_tokens. Im obigen Beispiel gilt total_tokens = 22 + 196 = 218. Aufgabenstatusverlauf: submitted → in_progress → completed / failed. Bildzugriff: data.result.images[0].url[0].

Übersicht

Modelle

Textserie

Bildserie

Videoserie

Audioserie

Moderationsserie

Upload-Verwaltung

Aufgabenverwaltung

Kontoverwaltung

GPT-Image-2 Bildgenerierung (offizieller Kanal)

Autorisierung

Body

Size × Resolution Zuordnung

Anwendungsbeispiele

Response

Abfrage der Aufgabenergebnisse

Beispiel einer erfolgreichen Antwort

​Autorisierung

​Body

​Size × Resolution Zuordnung

​Anwendungsbeispiele

​Response

​Abfrage der Aufgabenergebnisse

​Beispiel einer erfolgreichen Antwort

Autorisierung

Body

Size × Resolution Zuordnung

Anwendungsbeispiele

Response

Abfrage der Aufgabenergebnisse

Beispiel einer erfolgreichen Antwort