> ## Documentation Index
> Fetch the complete documentation index at: https://docs.apimart.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# GPT-Image(1/1.5) 图像生成

>  - 异步处理模式，返回任务ID用于后续查询
- 支持文生图、图生图、局部重绘等多种生成模式
- 支持透明背景、多种输出格式、多质量档位
- 单次最多生成 4 张图片，参考图最多 15 张 

<RequestExample>
  ```bash cURL theme={null}
  curl --request POST \
    --url https://api.apimart.ai/v1/images/generations \
    --header 'Authorization: Bearer <token>' \
    --header 'Content-Type: application/json' \
    --data '{
      "model": "gpt-image-1-official",
      "prompt": "星空下的古老城堡",
      "size": "1:1",
      "quality": "auto",
      "n": 1
    }'
  ```

  ```python Python theme={null}
  import requests

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

  payload = {
      "model": "gpt-image-1-official",
      "prompt": "星空下的古老城堡",
      "size": "1:1",
      "quality": "auto",
      "n": 1
  }

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

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

  print(response.json())
  ```

  ```javascript JavaScript theme={null}
  const url = "https://api.apimart.ai/v1/images/generations";

  const payload = {
    model: "gpt-image-1-official",
    prompt: "星空下的古老城堡",
    size: "1:1",
    quality: "auto",
    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));
  ```

  ```go Go theme={null}
  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-1-official",
          "prompt":  "星空下的古老城堡",
          "size":    "1:1",
          "quality": "auto",
          "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))
  }
  ```

  ```java Java theme={null}
  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-1-official",
            "prompt": "星空下的古老城堡",
            "size": "1:1",
            "quality": "auto",
            "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 PHP theme={null}
  <?php

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

  $payload = [
      "model" => "gpt-image-1-official",
      "prompt" => "星空下的古老城堡",
      "size" => "1:1",
      "quality" => "auto",
      "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;
  ?>
  ```

  ```ruby Ruby theme={null}
  require 'net/http'
  require 'json'
  require 'uri'

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

  payload = {
    model: "gpt-image-1-official",
    prompt: "星空下的古老城堡",
    size: "1:1",
    quality: "auto",
    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
  ```

  ```swift Swift theme={null}
  import Foundation

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

  let payload: [String: Any] = [
      "model": "gpt-image-1-official",
      "prompt": "星空下的古老城堡",
      "size": "1:1",
      "quality": "auto",
      "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()
  ```

  ```csharp C# theme={null}
  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-1-official"",
              ""prompt"": ""星空下的古老城堡"",
              ""size"": ""1:1"",
              ""quality"": ""auto"",
              ""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);
      }
  }
  ```

  ```dart Dart theme={null}
  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-1-official',
      'prompt': '星空下的古老城堡',
      'size': '1:1',
      'quality': 'auto',
      'n': 1,
    };

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

    print(response.body);
  }
  ```

  ```r R theme={null}
  library(httr)
  library(jsonlite)

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

  payload <- list(
    model = "gpt-image-1-official",
    prompt = "星空下的古老城堡",
    size = "1:1",
    quality = "auto",
    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"))
  ```
</RequestExample>

<ResponseExample>
  ```json 200 theme={null}
  {
    "code": 200,
    "data": [
      {
        "status": "submitted",
        "task_id": "task_01KXXXXXXXXXXXXXXX"
      }
    ]
  }
  ```

  ```json 400 theme={null}
  {
    "error": {
      "code": 400,
      "message": "请求参数无效",
      "type": "invalid_request_error"
    }
  }
  ```

  ```json 401 theme={null}
  {
    "error": {
      "code": 401,
      "message": "身份验证失败，请检查您的API密钥",
      "type": "authentication_error"
    }
  }
  ```

  ```json 402 theme={null}
  {
    "error": {
      "code": 402,
      "message": "账户余额不足，请充值后再试",
      "type": "payment_required"
    }
  }
  ```

  ```json 403 theme={null}
  {
    "error": {
      "code": 403,
      "message": "访问被禁止，您没有权限访问此资源",
      "type": "permission_error"
    }
  }
  ```

  ```json 429 theme={null}
  {
    "error": {
      "code": 429,
      "message": "请求过于频繁，请稍后再试",
      "type": "rate_limit_error"
    }
  }
  ```

  ```json 500 theme={null}
  {
    "error": {
      "code": 500,
      "message": "服务器内部错误，请稍后重试",
      "type": "server_error"
    }
  }
  ```

  ```json 502 theme={null}
  {
    "error": {
      "code": 502,
      "message": "网关错误，服务器暂时不可用",
      "type": "bad_gateway"
    }
  }
  ```
</ResponseExample>

## 支持的模型

| 模型名                      | 说明                 | 模式        | 图生图 | 最大张数 | 计费方式  |
| ------------------------ | ------------------ | --------- | --- | ---- | ----- |
| `gpt-image-1-official`   | 稳定优先，适合通用图片生成      | 文生图 / 图生图 | 支持  | 4 张  | 尺寸×质量 |
| `gpt-image-1.5-official` | 新版本，适合更高质量和更复杂编辑场景 | 文生图 / 图生图 | 支持  | 4 张  | 尺寸×质量 |

## Authorizations

<ParamField header="Authorization" type="string" required>
  所有接口均需要使用Bearer Token进行认证

  获取 API Key：

  访问 [API Key 管理页面](https://apimart.ai/keys) 获取您的 API Key

  使用时在请求头中添加：

  ```
  Authorization: Bearer YOUR_API_KEY
  ```
</ParamField>

## Body

<ParamField body="model" type="string" required>
  模型名称

  * `gpt-image-1-official` - 稳定优先，适合通用图片生成
  * `gpt-image-1.5-official` - 新版本，适合更高质量和更复杂编辑场景
</ParamField>

<ParamField body="prompt" type="string" required>
  图像生成的文本描述，支持中英文
</ParamField>

<ParamField body="size" type="string" default="1:1">
  画面比例

  支持的比例：

  * `1:1` - 正方形构图（默认）
  * `3:2` - 横构图
  * `2:3` - 竖构图
</ParamField>

<ParamField body="n" type="integer" default="1">
  生成图片张数

  取值范围：1-4

  * 传入值 ≤ 0 时，系统按 `1` 处理
  * 传入值 > 4 时，系统按 `4` 处理

  **⚠️ 注意：** 必须输入纯数字（如 `1`），不要加引号，否则会报错
</ParamField>

<ParamField body="quality" type="string" default="auto">
  图片质量

  * `auto` - 自动选择质量（默认）
  * `low` - 更快、更省
  * `medium` - 质量与消耗折中
  * `high` - 质量更高，消耗更高
</ParamField>

<ParamField body="background" type="string" default="auto">
  背景模式

  * `auto` - 自动背景（默认）
  * `opaque` - 不透明背景
  * `transparent` - 透明背景，推荐搭配 `png` 输出格式

  <Warning>
    `background: transparent` 不能和 `output_format: jpeg` 同时使用
  </Warning>
</ParamField>

<ParamField body="moderation" type="string" default="auto">
  审核强度

  * `auto` - 默认审核强度
  * `low` - 更宽松的审核强度
</ParamField>

<ParamField body="output_format" type="string" default="png">
  输出格式

  * `png` - 默认格式，适合透明背景
  * `jpeg` - 文件更小，适合普通图片输出

  <Warning>
    `background: transparent` 不能和 `output_format: jpeg` 同时使用
  </Warning>
</ParamField>

<ParamField body="output_compression" type="integer">
  输出压缩强度，范围 0-100

  * 建议仅在 `jpeg` 下使用
  * `png` 场景建议不传
</ParamField>

<ParamField body="image_urls" type="array">
  参考图像的 URL 数组，传入后自动按图生图处理

  <Expandable title="详细说明">
    * 传 1 张为单参考图编辑
    * 传 2-15 张为多参考图融合编辑
    * 超过 15 张服务端会拒绝处理
    * 必须是公网可访问的稳定图片 URL
  </Expandable>

  **限制：** 最多 15 张参考图
</ParamField>

<ParamField body="mask_url" type="string">
  遮罩图 URL，用于局部重绘（inpainting）

  * 需搭配 `image_urls` 一起使用
  * 传入后会按官方编辑接口一并提交

  <Warning>
    1、上传遮罩图前，请先确认图片 Alpha 通道为「是」。

    2、遮罩图尺寸需与首张参考图一致。
  </Warning>
</ParamField>

## 尺寸对照表

对外统一使用比例值，系统内部自动映射到官方实际尺寸并完成计费。

| 比例    | 实际尺寸      | 说明    |
| ----- | --------- | ----- |
| `1:1` | 1024×1024 | 正方形构图 |
| `2:3` | 1024×1536 | 竖构图   |
| `3:2` | 1536×1024 | 横构图   |

## 使用场景示例

**文生图（最简请求）**

```json theme={null}
{
  "model": "gpt-image-1-official",
  "prompt": "星空下的古老城堡"
}
```

**文生图（完整参数）**

```json theme={null}
{
  "model": "gpt-image-1-official",
  "prompt": "A flat icon of a glass bottle with no background",
  "size": "2:3",
  "quality": "high",
  "background": "transparent",
  "moderation": "low",
  "output_format": "png",
  "n": 1
}
```

**图生图（单参考图）**

```json theme={null}
{
  "model": "gpt-image-1.5-official",
  "prompt": "将参考图改成插画风格，保留主体轮廓",
  "size": "1:1",
  "quality": "auto",
  "image_urls": [
    "https://your-cdn.com/input.png"
  ],
  "n": 1
}
```

**图生图（多参考图融合）**

```json theme={null}
{
  "model": "gpt-image-1.5-official",
  "prompt": "将两张参考图融合成一张插画海报，保留主体轮廓",
  "size": "1:1",
  "quality": "auto",
  "background": "transparent",
  "image_urls": [
    "https://your-cdn.com/input-a.png",
    "https://your-cdn.com/input-b.png"
  ],
  "moderation": "low",
  "output_format": "png",
  "n": 1
}
```

**多张生成（n > 1）**

```json theme={null}
{
  "model": "gpt-image-1-official",
  "prompt": "Four minimalist poster variations of a red fox",
  "size": "1:1",
  "quality": "low",
  "output_format": "png",
  "n": 4
}
```

## Response

<ResponseField name="code" type="integer">
  响应状态码
</ResponseField>

<ResponseField name="data" type="array">
  返回数据数组

  <Expandable title="属性">
    <ResponseField name="status" type="string">
      任务状态

      * `submitted` - 已提交
    </ResponseField>

    <ResponseField name="task_id" type="string">
      任务唯一标识符
    </ResponseField>
  </Expandable>
</ResponseField>

## 注意事项

1. **异步处理**：提交后返回 `task_id`，需轮询 `/v1/tasks/{task_id}` 获取结果
2. **模型选择**：通用图片生成优先使用 `gpt-image-1-official`，高质量编辑和复杂图生图建议使用 `gpt-image-1.5-official`
3. **图片 URL 要求**：图生图推荐使用公网可直接访问的稳定图片 URL
4. **计费规则**：按成功生成的图片张数计费，失败不扣费