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

Génération d'images GPT-Image-2 (canal officiel)

Modèle officiel OpenAI gpt-image-2, basé sur le protocole compatible /v1/images/generations
Traitement asynchrone, renvoie un task_id pour les requêtes ultérieures
Texte-vers-image / image-vers-image / inpainting (mask) — tout-en-un
Prise en charge des arrière-plans transparents PNG / WebP (canal alpha)
Nouveau champ de niveau resolution — sélection 1K / 2K / 4K
15 ratios d’aspect pris en charge sur les niveaux 1K / 2K / 4K
Jusqu’à 4 images par requête, jusqu’à 16 images de référence
Alignement de paramètres à 95 % avec gpt-image-1.5-official — la migration ne nécessite qu’un changement de nom de modèle

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"
  }
}

Autorisations

string

requis

Tous les points de terminaison nécessitent une authentification Bearer TokenObtenir votre clé API :Rendez-vous sur la page de gestion des clés API pour obtenir votre clé APIIncluez-la dans l’en-tête de la requête :

Authorization: Bearer YOUR_API_KEY

Body

string

défaut:"gpt-image-2-official"

requis

Nom du modèle de génération d’imagesFixé à gpt-image-2-official (modèle officiel OpenAI gpt-image-2)

boolean

défaut:"false"

Indique s’il faut modérer le contenu avant d’envoyer la tâche d’image.

true : vérifier les prompts et les images d’entrée avec omni-moderation-latest
false ou omis : ne pas envoyer de requête de modération, sans coût ni latence de modération supplémentaires (par défaut)

string

requis

Description textuelle pour la génération d’images

Prend en charge l’anglais et le chinois, des descriptions détaillées sont recommandées
Modération de contenu / examen de sécurité avant soumission — les violations sont rejetées immédiatement

string

défaut:"1:1"

Ratio d’aspect de l’imageÀ l’extérieur, des valeurs de ratio sont utilisées ; en interne, elles sont automatiquement associées aux pixels réels selon resolution.Ratios pris en charge, plus auto pour laisser le serveur choisir automatiquement un ratio adapté :

auto — Automatique (le serveur choisit un ratio selon le prompt / les images de référence)
1:1 — Carré (par défaut, avatars sociaux / logos)
3:2 — Paysage (ratio courant de reflex numérique)
2:3 — Portrait (affiches verticales)
4:3 — Paysage (moniteur classique / diaporama)
3:4 — Portrait
5:4 — Paysage
4:5 — Portrait (publication Instagram verticale)
16:9 — Paysage (miniature vidéo grand écran)
9:16 — Portrait (plein écran téléphone / couverture de vidéo courte)
2:1 — Paysage (bannière Web)
1:2 — Portrait
3:1 — Paysage (bannière ultra-large)
1:3 — Portrait (affiche extra-haute)
21:9 — Paysage (ultra-large cinématographique)
9:21 — Portrait

Les dimensions en pixels peuvent également être transmises directement, par exemple 1881x836 / 887x1774.

Lorsque size est défini sur auto, le ratio par défaut est 1:1.

string

défaut:"1k"

Niveau de résolution (nouveau champ)Contrôle la netteté réelle de la sortie.

1k — Base 1024, économique pour une utilisation quotidienne (par défaut)
2k — Base 2048, adapté aux affiches / besoins en haute définition
4k — Base 3840, prend en charge les 15 ratios du tableau de correspondance ci-dessous

La 4K prend en charge les 15 ratios du tableau de correspondance ci-dessous ; vous pouvez également transmettre les dimensions en pixels du tableau directement via size.

string

défaut:"auto"

Qualité de l’image

auto — Automatique (par défaut, généralement équivalent à low)
low — Rapide et économique, suffisant pour des contours grossiers
medium — Équilibré
high — Précision maximale (4K + high peut prendre plus de 120 s)

string

défaut:"auto"

Mode d’arrière-plan

auto — Automatique (par défaut)
opaque — Opaque
transparent — Demande un arrière-plan transparent ; la sortie contient un canal alpha

string

défaut:"auto"

Force de modération

auto — Force de modération par défaut
low — Modération plus permissive

string

défaut:"png"

Format de sortie

png — Format par défaut, prend en charge les arrière-plans transparents
jpeg — Fichiers plus petits, ne prend pas en charge le canal alpha
webp — Prend en charge les arrière-plans transparents, adapté aux navigateurs modernes

Lorsque background vaut transparent, seuls png ou webp peuvent être sélectionnés.

integer

Niveau de compression de sortie, plage 0-100

N’est effectif que pour jpeg / webp

integer

défaut:"1"

Nombre d’images à générerPlage : 1 ~ 4

Doit être un nombre brut (par exemple 1), ne pas mettre entre guillemets

array

Tableau d’URL d’images de référence

Afficher Détails

20 Mo maximum par image, plafond total de 256 Mo
Jusqu’à 16 images de référence ; au-delà, sera rejeté
Doivent être des URL d’images publiquement accessibles et stables

string

URL de l’image de masque, utilisée pour l’inpainting

Doit être utilisé conjointement avec image_urls

Assurez-vous que l’image de masque possède un canal Alpha avant de la téléverser.
Les dimensions de l’image de masque doivent correspondre à la première image de référence.

Correspondance Size × Resolution

size × resolution → pixels réels OpenAI (15 ratios × 3 niveaux) :

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

Note : Certaines dimensions sont approximées à des multiples de 16 et à des limites de pixels, comme 3:2 / 2:3 @ 2K qui est 2048×1360 et 21:9 @ 4K qui est 3840×1648. Référez-vous aux pixels réels du tableau comme source de vérité.

Exemples d’utilisation

Texte-vers-image (requête minimale)

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

Texte-vers-image (sticker transparent)

{
  "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
}

Image-vers-image (suppression de l’arrière-plan)

{
  "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"
}

Affiche haute définition 2K

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

Fond d’écran 4K

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

Image-vers-image (fusion multi-références)

{
  "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 (masque)

{
  "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"
}

Plusieurs images (n > 1)

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

Chaîne de pixels directe (avancée)

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

Response

integer

Code de statut de la réponse

array

Tableau de données de réponse

Afficher Propriétés

string

Statut de la tâche

submitted — Soumise

string

Identifiant unique de la tâche, utilisé pour les requêtes ultérieures de résultats

Interrogation des résultats de tâche

Après une soumission réussie, un task_id est renvoyé. Interrogez l’état de la tâche via GET /v1/tasks/{task_id}, voir API d’interrogation des tâches pour plus de détails.

Exemple de réponse en cas de succès

{
  "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
    }
  }
}

Le champ usage indique la consommation de tokens facturée pour cette requête :

Champ	Description
`input_tokens`	Nombre total de tokens d’entrée consommés
`input_tokens_details.cached_tokens`	Tokens d’entrée servis depuis le cache
`input_tokens_details.image_tokens`	Tokens utilisés par les images d’entrée
`input_tokens_details.text_tokens`	Tokens utilisés par le texte d’entrée (prompt)
`output_tokens`	Nombre total de tokens de sortie consommés
`output_tokens_details.image_tokens`	Tokens utilisés par l’image générée
`output_tokens_details.text_tokens`	Tokens utilisés par le texte de sortie
`total_tokens`	Nombre total de tokens, égal à `input_tokens` + `output_tokens`

Pour la génération d’images, la sortie est principalement composée de tokens d’image, donc output_tokens_details.image_tokens est généralement égal à output_tokens. Dans l’exemple ci-dessus, total_tokens = 22 + 196 = 218. Flux de statuts de la tâche : submitted → in_progress → completed / failed. Accès à l’image : data.result.images[0].url[0].

Aperçu

Modèles

Série Texte

Série Image

Série Vidéo

Série Audio

Série Modération

Gestion des uploads

Gestion des tâches

Gestion du compte

Génération d'images GPT-Image-2 (canal officiel)

Autorisations

Body

Correspondance Size × Resolution

Exemples d’utilisation

Response

Interrogation des résultats de tâche

Exemple de réponse en cas de succès

​Autorisations

​Body

​Correspondance Size × Resolution

​Exemples d’utilisation

​Response

​Interrogation des résultats de tâche

​Exemple de réponse en cas de succès

Autorisations

Body

Correspondance Size × Resolution

Exemples d’utilisation

Response

Interrogation des résultats de tâche

Exemple de réponse en cas de succès