Zum Hauptinhalt springen
POST
/
v1
/
images
/
generations
# model kann "gpt-image-2" sein, alternativ auch der 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"
  }
}
Hinweis zur Modellnamen-Kompatibilität: Diese Schnittstelle unterstützt auch den Alias gpt-image-2-ext, der gpt-image-2 entspricht. Beide sind austauschbar und liefern identische Ergebnisse.
# model kann "gpt-image-2" sein, alternativ auch der 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"
  }
}

Autorisierung

Authorization
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

model
string
Standard:"gpt-image-2"
erforderlich
Name des BildgenerierungsmodellsFest auf gpt-image-2 gesetzt (kompatibler Alias gpt-image-2-ext)
Zur Kompatibilität mit älteren Aufrufen kann der Alias gpt-image-2-ext (entspricht gpt-image-2) weiterhin verwendet werden.
prompt
string
erforderlich
Textbeschreibung für die Bildgenerierung
  • Unterstützt Englisch und Chinesisch, detaillierte Beschreibungen werden empfohlen
  • Inhaltsmoderation / Sicherheitsprüfung vor dem Einreichen — Verstöße werden sofort abgelehnt
n
integer
Standard:"1"
Anzahl der zu generierenden BilderBereich: 1 - 10
Muss eine reine Zahl sein (z. B. 1), nicht in Anführungszeichen setzen
size
string
Standard:"1:1"
Seitenverhältnis des BildesUnterstützte Seitenverhältnisse, plus auto, damit der Server automatisch ein passendes Verhältnis auswählt:
sizeTyp
autoAutomatisch
1:1Quadrat
3:2Querformat
2:3Hochformat
4:3Querformat
3:4Hochformat
5:4Querformat
4:5Hochformat
16:9Querformat
9:16Hochformat
2:1Querformat
1:2Hochformat
3:1Querformat
1:3Hochformat
21:9Querformat
9:21Hochformat
Pixelabmessungen können auch direkt übergeben werden, z. B. 1881x836 / 887x1774.
Wenn size auf auto gesetzt ist, beträgt das Standardverhältnis 1:1.
resolution
string
Standard:"1k"
AusgabeauflösungsstufeOptionen: 1k / 2k / 4ksize × resolution → tatsächliche Pixelzuordnung:
size1k2k4k
1:11024×1024 / 1254×12542048×20482880×2880
3:21536×10242048×13603520×2336
2:31024×15361360×20482336×3520
4:31024×7682048×15363312×2480
3:4768×10241536×20482480×3312
5:41280×1024 / 1448×10862560×20483216×2576
4:51024×1280 / 1122×14022048×25602576×3216
16:91536×864 / 1672×9412048×11523840×2160
9:16864×1536 / 941×16721152×20482160×3840
2:12048×1024 / 1774×8872688×13443840×1920
1:21024×2048 / 887×17741344×26881920×3840
3:11881×836 / 1536×5123072×10243840×1280
1:3887×1774 / 512×15361024×30721280×3840
21:92016×864 / 1915×8212688×11523840×1648
9:21864×2016 / 821×19151152×26881648×3840
4K unterstützt die oben aufgeführten 15 Seitenverhältnisse; Sie können die Pixelabmessungen aus der Tabelle auch direkt über size übergeben.
image_urls
array
Array von Referenzbildern (OpenAI-Standardfeld). Wechselt bei Angabe in den Bild-zu-Bild-Modus.
Andere OpenAI-Standardfelder (response_format, style) werden nicht unterstützt und ignoriert. Aufgabenergebnisse geben nur url zurück — bitte laden Sie das Bild bei Bedarf selbst herunter und konvertieren Sie es in Base64.
official_fallback
boolean
Standard:"false"
Ob auf den offiziellen Kanal zurückgegriffen werden soll
  • false: Nicht verwenden (Standard)
  • true: Offiziellen Kanal verwenden

Anwendungsbeispiele

Text-zu-Bild (minimale Anfrage)
{
  "model": "gpt-image-2",
  "prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style"
}
Text-zu-Bild (mit Seitenverhältnis + 2K)
{
  "model": "gpt-image-2",
  "prompt": "a corgi astronaut on the moon, cinematic, 8k",
  "size": "16:9",
  "resolution": "2k"
}
Text-zu-Bild (4K-Ausgabe)
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k"
}
Text-zu-Bild (mehrere Bilder)
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k",
  "n": 2
}
Bild-zu-Bild (Referenz = URL)
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "https://example.com/photo.jpg"
  ]
}
Bild-zu-Bild (Referenz = Base64)
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  ]
}
Bild-zu-Bild (Mehrfachreferenz-Fusion, URL + Base64 gemischt)
{
  "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

code
integer
Statuscode der Antwort
data
array
Array mit Antwortdaten

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": {
    "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
        }
      ]
    }
  }
}
Bildzugriff: data.result.images[0].url[0]

Aufgabenstatus

StatusBedeutung
submittedEingereicht
processingWird vorgelagert verarbeitet
completedErfolg, result.images verfügbar
failedFehlgeschlagen, siehe error.message