Saltar para o conteúdo principal
POST
/
v1
/
images
/
generations
# model pode ser "gpt-image-2", também compatível com o 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"
  }
}
Aviso de compatibilidade de nome de modelo: esta interface também é compatível com o alias gpt-image-2-ext, que é equivalente a gpt-image-2; ambos podem ser usados de forma intercambiável e produzem o mesmo resultado.
# model pode ser "gpt-image-2", também compatível com o 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"
  }
}

Autorizações

Authorization
string
obrigatório
Todos os endpoints requerem autenticação por Bearer TokenObtenha sua chave de API:Acesse a página de gerenciamento de chaves de API para obter sua chave de APIInclua-a no cabeçalho da requisição:
Authorization: Bearer YOUR_API_KEY

Body

model
string
padrão:"gpt-image-2"
obrigatório
Nome do modelo de geração de imagensFixo em gpt-image-2 (alias compatível gpt-image-2-ext)
Para compatibilidade com chamadas de versões anteriores, o alias gpt-image-2-ext (correspondente a gpt-image-2) continua podendo ser usado normalmente.
prompt
string
obrigatório
Descrição textual para a geração da imagem
  • Suporta inglês e chinês, descrições detalhadas são recomendadas
  • Moderação de conteúdo / revisão de segurança antes do envio — violações são rejeitadas imediatamente
n
integer
padrão:"1"
Número de imagens a serem geradasIntervalo: 1 - 10
Deve ser um número puro (ex.: 1), não envolva em aspas
size
string
padrão:"1:1"
Proporção da imagemProporções suportadas, além de auto para deixar o servidor escolher uma proporção adequada automaticamente:
sizeTipo
autoAutomático
1:1Quadrado
3:2Paisagem
2:3Retrato
4:3Paisagem
3:4Retrato
5:4Paisagem
4:5Retrato
16:9Paisagem
9:16Retrato
2:1Paisagem
1:2Retrato
3:1Paisagem
1:3Retrato
21:9Paisagem
9:21Retrato
Dimensões em pixels também podem ser passadas diretamente, como 1881x836 / 887x1774.
Quando size é definido como auto, a proporção padrão é 1:1.
resolution
string
padrão:"1k"
Nível de resolução de saídaOpções: 1k / 2k / 4kMapeamento size × resolution → pixels reais:
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
O 4K suporta as 15 proporções listadas acima; você também pode passar as dimensões em pixels da tabela diretamente via size.
image_urls
array
Array de imagens de referência (campo padrão OpenAI). Alterna para o modo imagem para imagem quando fornecido.
Outros campos padrão da OpenAI (response_format, style) não são suportados e serão ignorados. Os resultados das tarefas retornam apenas url — faça você mesmo o download e converta para base64 se necessário.
official_fallback
boolean
padrão:"false"
Se deve recorrer ao canal oficial como fallback
  • false: Não usar (padrão)
  • true: Usar o canal oficial

Exemplos de uso

Texto para imagem (requisição mínima)
{
  "model": "gpt-image-2",
  "prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style"
}
Texto para imagem (com proporção + 2K)
{
  "model": "gpt-image-2",
  "prompt": "a corgi astronaut on the moon, cinematic, 8k",
  "size": "16:9",
  "resolution": "2k"
}
Texto para imagem (saída em 4K)
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k"
}
Texto para imagem (múltiplas)
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k",
  "n": 2
}
Imagem para imagem (referência = URL)
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "https://example.com/photo.jpg"
  ]
}
Imagem para imagem (referência = base64)
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  ]
}
Imagem para imagem (fusão multi-referência, URL + base64 combinados)
{
  "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
Código de status da resposta
data
array
Array de dados da resposta

Consulta de resultados da tarefa

Após o envio bem-sucedido, um task_id é retornado. Consulte o status da tarefa via GET /v1/tasks/{task_id}, veja API de consulta de tarefas para mais detalhes.

Exemplo de resposta de sucesso

{
  "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
        }
      ]
    }
  }
}
Acesso à imagem: data.result.images[0].url[0]

Status da tarefa

StatusSignificado
submittedEnviada
processingSendo processada no upstream
completedSucesso, result.images disponível
failedFalhou, verifique error.message