Seedream-5.0-Pro Image Generation

curl --request POST \
  --url https://api.apimart.ai/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "size": "16:9",
    "resolution": "2K"
  }'

import requests

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

payload = {
    "model": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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":      "seedream-5-0-pro",
        "prompt":     "A cyberpunk city night scene, neon lights reflecting on wet streets",
        "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": "seedream-5-0-pro",
          "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
          "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" => "seedream-5-0-pro",
    "prompt" => "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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"": ""seedream-5-0-pro"",
            ""prompt"": ""A cyberpunk city night scene, neon lights reflecting on wet streets"",
            ""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);
    }
}

#include <stdio.h>
#include <curl/curl.h>

int main(void) {
    CURL *curl;
    CURLcode res;

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/images/generations";
        const char *payload = "{"
            "\"model\":\"seedream-5-0-pro\","
            "\"prompt\":\"A cyberpunk city night scene, neon lights reflecting on wet streets\","
            "\"size\":\"16:9\","
            "\"resolution\":\"2K\""
        "}";

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, "Authorization: Bearer <token>");
        headers = curl_slist_append(headers, "Content-Type: application/json");

        curl_easy_setopt(curl, CURLOPT_URL, url);
        curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
        curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

        res = curl_easy_perform(curl);

        if(res != CURLE_OK) {
            fprintf(stderr, "curl_easy_perform() failed: %s\n",
                    curl_easy_strerror(res));
        }

        curl_slist_free_all(headers);
        curl_easy_cleanup(curl);
    }

    curl_global_cleanup();
    return 0;
}

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/images/generations"];

        NSDictionary *payload = @{
            @"model": @"seedream-5-0-pro",
            @"prompt": @"A cyberpunk city night scene, neon lights reflecting on wet streets",
            @"size": @"16:9",
            @"resolution": @"2K"
        };

        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];

        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
        [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
        [request setHTTPBody:jsonData];

        NSURLSessionDataTask *task = [[NSURLSession sharedSession]
            dataTaskWithRequest:request
            completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                if (error) {
                    NSLog(@"Error: %@", error);
                    return;
                }
                NSString *result = [[NSString alloc] initWithData:data
                                                        encoding:NSUTF8StringEncoding];
                NSLog(@"%@", result);
            }];

        [task resume];
        [[NSRunLoop mainRunLoop] run];
    }
    return 0;
}

(* Requires cohttp and yojson libraries *)
open Lwt
open Cohttp
open Cohttp_lwt_unix

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

let payload = {|{
  "model": "seedream-5-0-pro",
  "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
  "size": "16:9",
  "resolution": "2K"
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" "Bearer <token>"
    |> fun h -> Header.add h "Content-Type" "application/json"
  in
  let body = Cohttp_lwt.Body.of_string payload in

  let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
    body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
    print_endline body_str
  in
  Lwt_main.run response

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': 'seedream-5-0-pro',
    'prompt': 'A cyberpunk city night scene, neon lights reflecting on wet streets',
    '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 = "seedream-5-0-pro",
  prompt = "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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_01K8SGYNNNVBQTXNR4MM964S7K"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Invalid authentication credentials",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient balance. Please top up your account",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden. You don't have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Rate limit exceeded. 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"
  }
}

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": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "size": "16:9",
    "resolution": "2K"
  }'

import requests

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

payload = {
    "model": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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":      "seedream-5-0-pro",
        "prompt":     "A cyberpunk city night scene, neon lights reflecting on wet streets",
        "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": "seedream-5-0-pro",
          "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
          "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" => "seedream-5-0-pro",
    "prompt" => "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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"": ""seedream-5-0-pro"",
            ""prompt"": ""A cyberpunk city night scene, neon lights reflecting on wet streets"",
            ""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);
    }
}

#include <stdio.h>
#include <curl/curl.h>

int main(void) {
    CURL *curl;
    CURLcode res;

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/images/generations";
        const char *payload = "{"
            "\"model\":\"seedream-5-0-pro\","
            "\"prompt\":\"A cyberpunk city night scene, neon lights reflecting on wet streets\","
            "\"size\":\"16:9\","
            "\"resolution\":\"2K\""
        "}";

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, "Authorization: Bearer <token>");
        headers = curl_slist_append(headers, "Content-Type: application/json");

        curl_easy_setopt(curl, CURLOPT_URL, url);
        curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
        curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

        res = curl_easy_perform(curl);

        if(res != CURLE_OK) {
            fprintf(stderr, "curl_easy_perform() failed: %s\n",
                    curl_easy_strerror(res));
        }

        curl_slist_free_all(headers);
        curl_easy_cleanup(curl);
    }

    curl_global_cleanup();
    return 0;
}

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/images/generations"];

        NSDictionary *payload = @{
            @"model": @"seedream-5-0-pro",
            @"prompt": @"A cyberpunk city night scene, neon lights reflecting on wet streets",
            @"size": @"16:9",
            @"resolution": @"2K"
        };

        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];

        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
        [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
        [request setHTTPBody:jsonData];

        NSURLSessionDataTask *task = [[NSURLSession sharedSession]
            dataTaskWithRequest:request
            completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                if (error) {
                    NSLog(@"Error: %@", error);
                    return;
                }
                NSString *result = [[NSString alloc] initWithData:data
                                                        encoding:NSUTF8StringEncoding];
                NSLog(@"%@", result);
            }];

        [task resume];
        [[NSRunLoop mainRunLoop] run];
    }
    return 0;
}

(* Requires cohttp and yojson libraries *)
open Lwt
open Cohttp
open Cohttp_lwt_unix

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

let payload = {|{
  "model": "seedream-5-0-pro",
  "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
  "size": "16:9",
  "resolution": "2K"
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" "Bearer <token>"
    |> fun h -> Header.add h "Content-Type" "application/json"
  in
  let body = Cohttp_lwt.Body.of_string payload in

  let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
    body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
    print_endline body_str
  in
  Lwt_main.run response

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': 'seedream-5-0-pro',
    'prompt': 'A cyberpunk city night scene, neon lights reflecting on wet streets',
    '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 = "seedream-5-0-pro",
  prompt = "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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_01K8SGYNNNVBQTXNR4MM964S7K"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Invalid authentication credentials",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient balance. Please top up your account",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden. You don't have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Rate limit exceeded. 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": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "size": "16:9",
    "resolution": "2K"
  }'

import requests

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

payload = {
    "model": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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":      "seedream-5-0-pro",
        "prompt":     "A cyberpunk city night scene, neon lights reflecting on wet streets",
        "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": "seedream-5-0-pro",
          "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
          "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" => "seedream-5-0-pro",
    "prompt" => "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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: "seedream-5-0-pro",
  prompt: "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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": "seedream-5-0-pro",
    "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
    "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"": ""seedream-5-0-pro"",
            ""prompt"": ""A cyberpunk city night scene, neon lights reflecting on wet streets"",
            ""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);
    }
}

#include <stdio.h>
#include <curl/curl.h>

int main(void) {
    CURL *curl;
    CURLcode res;

    curl_global_init(CURL_GLOBAL_DEFAULT);
    curl = curl_easy_init();

    if(curl) {
        const char *url = "https://api.apimart.ai/v1/images/generations";
        const char *payload = "{"
            "\"model\":\"seedream-5-0-pro\","
            "\"prompt\":\"A cyberpunk city night scene, neon lights reflecting on wet streets\","
            "\"size\":\"16:9\","
            "\"resolution\":\"2K\""
        "}";

        struct curl_slist *headers = NULL;
        headers = curl_slist_append(headers, "Authorization: Bearer <token>");
        headers = curl_slist_append(headers, "Content-Type: application/json");

        curl_easy_setopt(curl, CURLOPT_URL, url);
        curl_easy_setopt(curl, CURLOPT_POSTFIELDS, payload);
        curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);

        res = curl_easy_perform(curl);

        if(res != CURLE_OK) {
            fprintf(stderr, "curl_easy_perform() failed: %s\n",
                    curl_easy_strerror(res));
        }

        curl_slist_free_all(headers);
        curl_easy_cleanup(curl);
    }

    curl_global_cleanup();
    return 0;
}

#import <Foundation/Foundation.h>

int main(int argc, const char * argv[]) {
    @autoreleasepool {
        NSURL *url = [NSURL URLWithString:@"https://api.apimart.ai/v1/images/generations"];

        NSDictionary *payload = @{
            @"model": @"seedream-5-0-pro",
            @"prompt": @"A cyberpunk city night scene, neon lights reflecting on wet streets",
            @"size": @"16:9",
            @"resolution": @"2K"
        };

        NSError *error;
        NSData *jsonData = [NSJSONSerialization dataWithJSONObject:payload
                                                          options:0
                                                            error:&error];

        NSMutableURLRequest *request = [NSMutableURLRequest requestWithURL:url];
        [request setHTTPMethod:@"POST"];
        [request setValue:@"Bearer <token>" forHTTPHeaderField:@"Authorization"];
        [request setValue:@"application/json" forHTTPHeaderField:@"Content-Type"];
        [request setHTTPBody:jsonData];

        NSURLSessionDataTask *task = [[NSURLSession sharedSession]
            dataTaskWithRequest:request
            completionHandler:^(NSData *data, NSURLResponse *response, NSError *error) {
                if (error) {
                    NSLog(@"Error: %@", error);
                    return;
                }
                NSString *result = [[NSString alloc] initWithData:data
                                                        encoding:NSUTF8StringEncoding];
                NSLog(@"%@", result);
            }];

        [task resume];
        [[NSRunLoop mainRunLoop] run];
    }
    return 0;
}

(* Requires cohttp and yojson libraries *)
open Lwt
open Cohttp
open Cohttp_lwt_unix

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

let payload = {|{
  "model": "seedream-5-0-pro",
  "prompt": "A cyberpunk city night scene, neon lights reflecting on wet streets",
  "size": "16:9",
  "resolution": "2K"
}|}

let () =
  let headers = Header.init ()
    |> fun h -> Header.add h "Authorization" "Bearer <token>"
    |> fun h -> Header.add h "Content-Type" "application/json"
  in
  let body = Cohttp_lwt.Body.of_string payload in

  let response = Client.post ~headers ~body (Uri.of_string url) >>= fun (resp, body) ->
    body |> Cohttp_lwt.Body.to_string >|= fun body_str ->
    print_endline body_str
  in
  Lwt_main.run response

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': 'seedream-5-0-pro',
    'prompt': 'A cyberpunk city night scene, neon lights reflecting on wet streets',
    '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 = "seedream-5-0-pro",
  prompt = "A cyberpunk city night scene, neon lights reflecting on wet streets",
  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_01K8SGYNNNVBQTXNR4MM964S7K"
    }
  ]
}

{
  "error": {
    "code": 400,
    "message": "Invalid request parameters",
    "type": "invalid_request_error"
  }
}

{
  "error": {
    "code": 401,
    "message": "Invalid authentication credentials",
    "type": "authentication_error"
  }
}

{
  "error": {
    "code": 402,
    "message": "Insufficient balance. Please top up your account",
    "type": "payment_required"
  }
}

{
  "error": {
    "code": 403,
    "message": "Access forbidden. You don't have permission to access this resource",
    "type": "permission_error"
  }
}

{
  "error": {
    "code": 429,
    "message": "Rate limit exceeded. 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"
  }
}

Authorizations

string

required

All API endpoints require Bearer Token authenticationGet your API Key:Visit the API Key Management Page to get your API KeyAdd it to the request header:

Authorization: Bearer YOUR_API_KEY

Single-image model: seedream-5-0-pro generates only 1 image per request (except layer decomposition). The following are rejected (HTTP 400, no task, no charge):

n > 1
sequential_image_generation (group generation is not supported)
stream (streaming is not supported)
tools (web search is not supported)
more than 10 items in image_urls

Interactive editing

Use <point> / <bbox> coordinates in the prompt, or upload an image with hand-drawn annotations, to target edits precisely.

Point coordinates: <point>x y</point> (specify a single point; the model determines the affected area)
Bounding-box coordinates: <bbox>x1 y1 x2 y2</bbox> (specify the top-left and bottom-right coordinates to precisely control the size of the edit area)

Layer decomposition

Split one image into a base image and up to 16 transparent PNG layers, with position and stacking information.

Body

string

default:"seedream-5-0-pro"

required

Image generation model name

seedream-5-0-pro (recommended)
Also accepted: seedream-5.0-pro

boolean

default:"false"

Whether to run content moderation before submitting the image task.

true: use omni-moderation-latest to review prompts and input images
false or omitted: do not send a moderation request, adding no moderation cost or latency (default)

string

required

Text description for image generationOptional when layer_decomposition: true; if omitted, the model automatically identifies and separates the main elements in the image.In addition to Chinese and English, native text generation supports Russian, Arabic, Filipino, Thai, Turkish, Korean, Malay, Spanish, Portuguese, Indonesian, French, German, Vietnamese, and Japanese.

Tip: Keep it within 600 English words; overly long descriptions may lose detail.

string

default:"1K"

Resolution tier (lowercase accepted). This is an API Mart extension equivalent to placing the tier directly in size.

1K (default)
1.5K (same price as 1K, better quality — prefer 1.5K unless you have a reason not to)
2K

Unsupported tiers such as 3K / 4K return 400.If both a tier-style size and resolution are provided, size takes precedence.

When size is an exact pixel value (e.g. 2048x1024), this field is ignored and dimensions come only from size.

string

default:"auto"

A tier keyword, aspect ratio, auto, or exact pixel dimensions.

Style ①: resolution tier (recommended)

The tier can be placed directly in size, or supplied through the API Mart extension field resolution:

{ "size": "2K" }

{ "resolution": "2K" }

These forms are equivalent. When only a tier is specified, describe the intended layout in the prompt (for example, “portrait poster” or “landscape cover”) and let the model choose the aspect ratio.

Style ②: tier + aspect ratio

Used with resolution. Supported ratios:

1:1, 4:3, 3:4, 16:9, 9:16, 3:2, 2:3, 2:1, 1:2, 21:9
Also accepts 16x9-style x separators
2x1 is equivalent to 2:1, and 1x2 is equivalent to 1:2. The x must be lowercase and spaces are not allowed.
auto (default): only the resolution tier is applied; final aspect ratio is chosen from the prompt / references

Ratios outside the list (e.g. 9:21) return 400 — no silent fallback to 1:1.Tier × ratio → output pixels:

Resolution	1:1	4:3	3:4	16:9	9:16	3:2	2:3	2:1	1:2	21:9
1K	1024×1024	1152×864	864×1152	1312×736	736×1312	1248×832	832×1248	1440×720	720×1440	1568×672
1.5K	1536×1536	1792×1344	1344×1792	2048×1152	1152×2048	1872×1248	1248×1872	2176×1088	1088×2176	2352×1008
2K	2048×2048	2304×1728	1728×2304	2560×1440	1440×2560	2496×1664	1664×2496	2880×1440	1440×2880	3024×1296

{ "resolution": "2K", "size": "2:1" }

Style ③: exact pixels

When size is widthxheight, pixels are used as-is and resolution does not apply. Accepts 2048X1024 / 2048×1024.

Constraint	Range
Total pixels (width × height)	`[921600, 4624220]` (about `1280×720` ~ `2048×2048×1.1025`)
Aspect ratio (width / height)	`[1/16, 16]`

Limits apply to the product of width and height, not each edge alone. Example: 512×512 is too small (400); 2048×1024 is valid.

string

default:"opaque"

Output background mode:

opaque: solid background (default)
transparent: transparent background

transparent is available only for image-to-image requests with exactly one input image that already has an alpha channel; output_format: "png" is also required.

boolean

default:"false"

Whether to decompose the image into layers. When enabled, the model returns one base image and up to 16 PNG layers with alpha channels.Exactly one PNG or JPEG image is required. It must contain [262144, 36000000] total pixels and be no larger than 30 MB. size accepts only 1K, 1.5K, 2K, or auto and defaults to auto. output_format controls only the base image format; decomposed layers are always PNG.

object

default:"{\"mode\":\"standard\"}"

Prompt optimization mode:

standard: standard mode with better quality (default)

The flattened form "optimize_prompt_options.mode": "standard" is also accepted.

integer

default:"1"

Number of images to generate. Only 1 is supported; use seedream-5-0-lite for grouped image generation.

array

Reference image URL list for single / multi-reference image-to-image, up to 10Two formats:1. Public URL

http:// or https://
Example: https://example.com/image.jpg

2. Base64 (Data URI)

Format: data:image/<format>;base64,<data> — <format> must be lowercase
Example: data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABg...

Per-image limits:

Formats: jpeg / png / webp / bmp / tiff / gif / heic / heif
Aspect ratio (w/h): [1/16, 16]
Each edge > 14 px
Size ≤ 30 MB
Total pixels ≤ 6000×6000 (36,000,000)

Billing: First reference image free; each additional image has a fixed surcharge.

string

default:"jpeg"

Output image format

jpeg (default)
png

Compatibility: response_format is equivalent to output_format; other values are treated as jpeg.

boolean

default:"false"

Whether to add an “AI generated” watermark at the bottom-right

true: add watermark
false: no watermark (default)

Request Examples

Text-to-image (tier + ratio)

{
  "model": "seedream-5-0-pro",
  "prompt": "Cyberpunk city night scene, neon reflections on wet streets",
  "resolution": "2K",
  "size": "2:1",
  "output_format": "png"
}

Text-to-image (exact pixels)

{
  "model": "seedream-5-0-pro",
  "prompt": "Minimal e-commerce hero image, white background, product centered",
  "size": "1600x1600"
}

Multi-reference

{
  "model": "seedream-5-0-pro",
  "prompt": "Replace the outfit in image 1 with the outfit in image 2",
  "image_urls": [
    "https://example.com/person.jpg",
    "https://example.com/dress.jpg"
  ],
  "resolution": "2K",
  "size": "auto"
}

Recommended: 1.5K same price, better quality

{
  "model": "seedream-5-0-pro",
  "prompt": "A cute orange cat on a windowsill in afternoon sun, cinematic",
  "resolution": "1.5K",
  "size": "16:9"
}

Layer decomposition

{
  "model": "seedream-5-0-pro",
  "image_urls": ["https://example.com/poster.png"],
  "layer_decomposition": true,
  "size": "2K"
}

You can also use <bbox> coordinates normalized to 0–1000 to identify elements to extract precisely:

{
  "model": "seedream-5-0-pro",
  "prompt": "Separate the image into precise layers. The text is at <bbox>180 64 812 198</bbox>; the parrot is at <bbox>347 305 642 997</bbox>.",
  "image_urls": ["https://example.com/poster.png"],
  "layer_decomposition": true
}

Interactive editing

Describe hand-drawn annotations in the image using natural language:

{
  "model": "seedream-5-0-pro",
  "prompt": "Edit the image according to the sketch. Add a stack of magazines in the marked area at the lower left and a cup of coffee in the marked area on the right. Remove all sketch lines and preserve the composition.",
  "image_urls": ["https://example.com/sketch.png"],
  "size": "2K",
  "output_format": "png"
}

Or target locations precisely with <point> / <bbox>:

{
  "model": "seedream-5-0-pro",
  "prompt": "Place the subject from image 1 at <bbox>179 283 796 986</bbox> into image 2 at <bbox>118 331 933 871</bbox>.",
  "image_urls": [
    "https://example.com/a.png",
    "https://example.com/b.png"
  ]
}

Alpha-channel editing

{
  "model": "seedream-5-0-pro",
  "prompt": "Change the parrot into a peacock while preserving the transparent background",
  "image_urls": ["https://cdn.example.com/images/layer.png"],
  "background": "transparent",
  "output_format": "png",
  "size": "2K"
}

Complete example: submit a task and retrieve the image

The following script shows the full flow: submit an asynchronous task, poll its status, handle failure states, and read the final image URL. Replace YOUR_API_KEY before running it.

Python

import time
import requests

API_KEY = "YOUR_API_KEY"
BASE_URL = "https://api.apimart.ai"
headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json",
}

# 1. Submit the generation task
create_response = requests.post(
    f"{BASE_URL}/v1/images/generations",
    headers=headers,
    json={
        "model": "seedream-5-0-pro",
        "prompt": "A Jiangnan water town in ink-wash style, with light morning mist",
        "resolution": "1.5K",
        "size": "16:9",
        "output_format": "png",
    },
    timeout=30,
)
create_response.raise_for_status()
task_id = create_response.json()["data"][0]["task_id"]
print(f"Task submitted: {task_id}")

# 2. Poll task status
while True:
    task_response = requests.get(
        f"{BASE_URL}/v1/tasks/{task_id}",
        headers=headers,
        timeout=30,
    )
    task_response.raise_for_status()
    task = task_response.json()
    status = task["status"]
    print(f"Status: {status}; progress: {task.get('progress', 0)}%")

    if status == "success":
        image = task["result"]["images"][0]
        print("Image URL:", image["url"][0])
        print("Image size:", image["sizes"][0])
        print("Image format:", image["output_formats"][0])
        break

    if status in {"failed", "cancelled"}:
        raise RuntimeError(task.get("error", f"Task {status}"))

    time.sleep(5)

On success, the task query endpoint returns:

{
  "id": "task_01JFXYZ123456789ABCDEF",
  "status": "success",
  "progress": 100,
  "cost": 0.045,
  "result": {
    "images": [
      {
        "url": ["https://cdn.example.com/images/image_task_xxx_0.png"],
        "sizes": ["2048x1152"],
        "output_formats": ["png"],
        "expires_at": 1784696685
      }
    ]
  }
}

Returned images are mirrored to storage managed by the platform. You should still download and persist them in your own system promptly; do not treat the result URL as permanent storage.

Complete cURL scenarios

Multi-image composition (up to 10 references)

curl -X POST "https://api.apimart.ai/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "seedream-5-0-pro",
    "prompt": "Place the person from image 1 into the scene from image 2 and unify the lighting at dusk",
    "image_urls": [
      "https://example.com/person.jpg",
      "https://example.com/scene.jpg"
    ],
    "resolution": "1.5K",
    "size": "16:9",
    "output_format": "png"
  }'

Exact pixels, prompt optimization, and watermark

curl -X POST "https://api.apimart.ai/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "seedream-5-0-pro",
    "prompt": "A cyberpunk city skyline with neon lights reflected on wet streets",
    "size": "2048x1024",
    "optimize_prompt_options": { "mode": "standard" },
    "watermark": true
  }'

Decompose and edit a transparent layer independently

First, decompose the source image:

curl -X POST "https://api.apimart.ai/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "seedream-5-0-pro",
    "image_urls": ["https://example.com/poster.png"],
    "layer_decomposition": true,
    "size": "2K"
  }'

Then retrieve the URL of a transparent layer and edit it independently:

curl -X POST "https://api.apimart.ai/v1/images/generations" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "seedream-5-0-pro",
    "prompt": "Change the parrot in the image into a peacock",
    "image_urls": ["https://cdn.example.com/images/image_task_xxx_4.png"],
    "background": "transparent",
    "output_format": "png",
    "size": "2K"
  }'

Layer-decomposition response and reconstruction

The url, sizes, output_formats, and layers arrays correspond by index; index 0 is always the base image:

{
  "result": {
    "images": [{
      "url": [
        "https://cdn.example.com/images/image_task_xxx_0.jpeg",
        "https://cdn.example.com/images/image_task_xxx_1.png",
        "https://cdn.example.com/images/image_task_xxx_2.png"
      ],
      "sizes": ["2048x2048", "1273x265", "492x98"],
      "output_formats": ["jpeg", "png", "png"],
      "layer_decomposition": true,
      "layers": [
        { "z_index": 0, "size": "2048x2048", "output_format": "jpeg" },
        {
          "z_index": 1,
          "size": "1273x265",
          "output_format": "png",
          "name": "Title text",
          "description": "Large yellow title text in a serif typeface",
          "bounding_box": {
            "absolute": [383, 120, 1655, 384],
            "normalized": [187, 59, 808, 188]
          }
        },
        {
          "z_index": 2,
          "size": "492x98",
          "output_format": "png",
          "name": "Upper-left tagline",
          "description": "Two-line English tagline in white",
          "bounding_box": {
            "absolute": [140, 451, 631, 548],
            "normalized": [68, 220, 308, 268]
          }
        }
      ]
    }]
  }
}

Composite layers in ascending z_index order. To reconstruct them on the output base image with absolute coordinates:

x = left
y = top
w = right - left
h = bottom - top

To reconstruct them on any W × H canvas, use normalized coordinates:

x = left / 1000 × W
y = top / 1000 × H
w = (right - left) / 1000 × W
h = (bottom - top) / 1000 × H

Layer decomposition is billed per image. Up to 17 images are preauthorized when the task is submitted. After completion, each output is assigned a tier based on its actual pixel count and settled individually; any excess preauthorization is refunded automatically. Your balance must cover the 17-image preauthorization, and size: "auto" is preauthorized at the 2K tier.

Billing Notes

Total = output unit price + reference surcharge × max(0, ref_count − 1)

Output is priced by actual total pixels (~2.61M = 2,601,124):

Condition	Unit price
≤ 2.61 million pixels (1.5K or lower: `resolution` `1K` / `1.5K` / omit, or exact pixels ≤ 2,601,124)	$0.045 / image
> 2.61 million pixels (higher than 1.5K: `resolution: "2K"`, or exact pixels > 2,601,124)	$0.09 / image

1.5K costs the same as 1K ($0.045).
With exact-pixel size, billing uses actual output area; resolution is ignored (e.g. size: "2048x2048" → $0.09).
First reference image is free; each additional reference has a surcharge.
Failed tasks are fully refunded.

Layer-decomposition preauthorization and settlement

Because the final number and dimensions of layers are unknown when a task is submitted, preauthorization uses conservative rules based on the request:

Exact pixels: tiered by the requested pixel area.
1K / 1.5K: preauthorized at the 1K tier.
2K: preauthorized at the 2K tier.
auto: can output up to 2K, so it is preauthorized at the 2K tier.

After completion, the base image and every actual layer are tiered and summed individually using their real pixel areas. Excess preauthorization is refunded automatically. Layers are usually much smaller than the base image, so even a task preauthorized at the 2K tier may ultimately settle entirely at the 1K tier.

Example: a 1080×1080 input is decomposed into 10 images. The task is preauthorized as 17 images × 2K tier. If all 10 final images contain no more than 2.61 million pixels, settlement uses 10 images × 1K tier and the remaining credit is refunded automatically.

Common Errors

Case	Notes
Unsupported `resolution` tier	e.g. 3K / 4K → 400
Unsupported `size` value	Neither `1K` / `1.5K` / `2K` / `auto`, a supported aspect ratio, nor valid pixel dimensions → 400
Exact-pixel total out of range	Must be in `[921600, 4624220]`
Exact-pixel aspect out of range	Must be in `[1/16, 16]`
`n > 1` / grouped-image parameters	Rejected by the single-image model
More than 10 reference images	Rejected
Layer decomposition without an image or with multiple images	Exactly one image is required
Layer decomposition with a ratio or exact pixels	`size` supports only `1K` / `1.5K` / `2K` / `auto`
Transparent background for text-to-image or multiple inputs	Exactly one input image with an alpha channel is required
Transparent background with JPEG	Set `output_format: "png"`
`stream` / `tools`	Not supported by this model; returns 400
Invalid prompt optimization mode	Only `standard` is supported

⏱️ Slower generation: ~90s for 1K, ~160s for 2K (quality first). Poll Get Task Status every 5–10 seconds; set the client timeout to 5 minutes. Save generated results promptly.

Response

integer

Response status code

array

Response data array

Show Properties

string

Task status

submitted - Submitted

string

Unique task identifier

Overview

Models

Text Series

Image Series

Video Series

Audio Series

Moderation Series

Upload Management

Task Management

Account Management

Seedream-5.0-Pro Image Generation

Authorizations

Interactive editing

Layer decomposition

Body

Style ①: resolution tier (recommended)

Style ②: tier + aspect ratio

Style ③: exact pixels

Request Examples

Text-to-image (tier + ratio)

Text-to-image (exact pixels)

Multi-reference

Recommended: 1.5K same price, better quality

Layer decomposition

Interactive editing

Alpha-channel editing

Complete example: submit a task and retrieve the image

Complete cURL scenarios

Multi-image composition (up to 10 references)

Exact pixels, prompt optimization, and watermark

Decompose and edit a transparent layer independently

Layer-decomposition response and reconstruction

Billing Notes

Layer-decomposition preauthorization and settlement

Common Errors

Response

​Authorizations

Interactive editing

Layer decomposition

​Body

​Style ①: resolution tier (recommended)

​Style ②: tier + aspect ratio

​Style ③: exact pixels

​Request Examples

​Text-to-image (tier + ratio)

​Text-to-image (exact pixels)

​Multi-reference

​Recommended: 1.5K same price, better quality

​Layer decomposition

​Interactive editing

​Alpha-channel editing

​Complete example: submit a task and retrieve the image

​Complete cURL scenarios

​Multi-image composition (up to 10 references)

​Exact pixels, prompt optimization, and watermark

​Decompose and edit a transparent layer independently

​Layer-decomposition response and reconstruction

​Billing Notes

​Layer-decomposition preauthorization and settlement

​Common Errors

​Response

Authorizations

Body

Style ①: resolution tier (recommended)

Style ②: tier + aspect ratio

Style ③: exact pixels

Request Examples

Text-to-image (tier + ratio)

Text-to-image (exact pixels)

Multi-reference

Recommended: 1.5K same price, better quality

Layer decomposition

Interactive editing

Alpha-channel editing

Complete example: submit a task and retrieve the image

Complete cURL scenarios

Multi-image composition (up to 10 references)

Exact pixels, prompt optimization, and watermark

Decompose and edit a transparent layer independently

Layer-decomposition response and reconstruction

Billing Notes

Layer-decomposition preauthorization and settlement

Common Errors

Response