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

# GPT-Image-2 Image Generation

>  - Asynchronous processing mode, returns task ID for subsequent queries
- OpenAI Images compatible protocol, supports text-to-image / image-to-image
- 15 image aspect ratios supported via the `size` field
- Output pixel tier controlled via `resolution` (`1k` / `2k` / `4k`)

- Up to 16 reference images, URL and base64 can be mixed
- Billed by resolution tier (1K / 2K / 4K) 

<Info>
  **Model name compatibility note**: This endpoint also accepts the alias `gpt-image-2-ext`, which is equivalent to `gpt-image-2`. The two are interchangeable and produce identical results.
</Info>

<RequestExample>
  ```bash cURL theme={null}
  # model can be "gpt-image-2", or the compatible alias "gpt-image-2-ext"
  curl --request POST \
    --url https://gccai.heqingsong.uk/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"
    }'
  ```

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

  url = "https://gccai.heqingsong.uk/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())
  ```

  ```javascript JavaScript theme={null}
  const url = "https://gccai.heqingsong.uk/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));
  ```

  ```go Go theme={null}
  package main

  import (
      "bytes"
      "encoding/json"
      "fmt"
      "io/ioutil"
      "net/http"
  )

  func main() {
      url := "https://gccai.heqingsong.uk/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))
  }
  ```

  ```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://gccai.heqingsong.uk/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 PHP theme={null}
  <?php

  $url = "https://gccai.heqingsong.uk/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;
  ?>
  ```

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

  url = URI("https://gccai.heqingsong.uk/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
  ```

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

  let url = URL(string: "https://gccai.heqingsong.uk/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()
  ```

  ```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://gccai.heqingsong.uk/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);
      }
  }
  ```

  ```dart Dart theme={null}
  import 'dart:convert';
  import 'package:http/http.dart' as http;

  void main() async {
    final url = Uri.parse('https://gccai.heqingsong.uk/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);
  }
  ```

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

  url <- "https://gccai.heqingsong.uk/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"))
  ```
</RequestExample>

<ResponseExample>
  ```json 200 theme={null}
  {
    "code": 200,
    "data": [
      {
        "status": "submitted",
        "task_id": "task_01KPQ7J7DWB7QZ3WCEK3YVPBRA"
      }
    ]
  }
  ```

  ```json 400 theme={null}
  {
    "error": {
      "code": 400,
      "message": "Invalid parameters: size not allowed / resolution not supported / pixel violation, etc.",
      "type": "invalid_request_error"
    }
  }
  ```

  ```json 401 theme={null}
  {
    "error": {
      "code": 401,
      "message": "Authentication failed, please check your API key",
      "type": "authentication_error"
    }
  }
  ```

  ```json 402 theme={null}
  {
    "error": {
      "code": 402,
      "message": "Insufficient account balance, please top up and try again",
      "type": "payment_required"
    }
  }
  ```

  ```json 429 theme={null}
  {
    "error": {
      "code": 429,
      "message": "Too many requests, please try again later",
      "type": "rate_limit_error"
    }
  }
  ```

  ```json 500 theme={null}
  {
    "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"
    }
  }
  ```

  ```json 503 theme={null}
  {
    "error": {
      "code": 503,
      "message": "Upstream temporarily unavailable, please try again later",
      "type": "service_unavailable"
    }
  }
  ```
</ResponseExample>

## Authorizations

<ParamField header="Authorization" type="string" required>
  All endpoints require Bearer Token authentication

  Get your API Key:

  Visit the [API Key management page](https://gccai.heqingsong.uk/keys) to get your API Key

  Include it in the request header:

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

## Body

<ParamField body="model" type="string" default="gpt-image-2" required>
  Image generation model name

  Fixed to `gpt-image-2` (compatible alias `gpt-image-2-ext`)

  <Note>
    For backward compatibility, the alias `gpt-image-2-ext` (for `gpt-image-2`) remains usable.
  </Note>
</ParamField>

<ParamField body="prompt" type="string" required>
  Text description for image generation

  * Supports English and Chinese, detailed descriptions recommended
  * Pre-submission content moderation / safety review — violations are rejected immediately
</ParamField>

<ParamField body="n" type="integer" default="1">
  Number of images to generate

  Range: `1 - 10`

  <Warning>
    Must be a pure number (e.g., `1`), do not wrap in quotes
  </Warning>
</ParamField>

<ParamField body="size" type="string" default="1:1">
  Image aspect ratio

  Supported ratios, plus `auto` to let the server pick a suitable ratio automatically:

  | size   | Type      |
  | ------ | --------- |
  | `auto` | Automatic |
  | `1:1`  | Square    |
  | `3:2`  | Landscape |
  | `2:3`  | Portrait  |
  | `4:3`  | Landscape |
  | `3:4`  | Portrait  |
  | `5:4`  | Landscape |
  | `4:5`  | Portrait  |
  | `16:9` | Landscape |
  | `9:16` | Portrait  |
  | `2:1`  | Landscape |
  | `1:2`  | Portrait  |
  | `3:1`  | Landscape |
  | `1:3`  | Portrait  |
  | `21:9` | Landscape |
  | `9:21` | Portrait  |

  Pixel dimensions can also be passed directly, such as `1881x836` / `887x1774`.

  <Warning>
    When `size` is set to `auto`, the default ratio is `1:1`.
  </Warning>
</ParamField>

<ParamField body="resolution" type="string" default="1k">
  Output resolution tier

  Options: `1k` / `2k` / `4k`

  `size × resolution` → actual pixel mapping:

  | size   | `1k`                  | `2k`      | `4k`          |
  | ------ | --------------------- | --------- | ------------- |
  | `1:1`  | 1024×1024 / 1254×1254 | 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 / 1448×1086 | 2560×2048 | **3216×2576** |
  | `4:5`  | 1024×1280 / 1122×1402 | 2048×2560 | **2576×3216** |
  | `16:9` | 1536×864 / 1672×941   | 2048×1152 | **3840×2160** |
  | `9:16` | 864×1536 / 941×1672   | 1152×2048 | **2160×3840** |
  | `2:1`  | 2048×1024 / 1774×887  | 2688×1344 | **3840×1920** |
  | `1:2`  | 1024×2048 / 887×1774  | 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 / 1915×821   | 2688×1152 | **3840×1648** |
  | `9:21` | 864×2016 / 821×1915   | 1152×2688 | **1648×3840** |

  <Warning>
    4K supports the 15 ratios listed above; you can also pass the pixel dimensions from the table directly via `size`.
  </Warning>
</ParamField>

<ParamField body="image_urls" type="array">
  Reference image array (OpenAI standard field). Switches to image-to-image mode when provided.

  <Expandable title="Details">
    * Up to 16 reference images, exceeding returns `image_urls exceeds max 16`
    * Max 20 MB per image, 256 MB in total
    * Supports `image URL` (public stable link)
    * Supports `base64 data URI` (e.g. `data:image/png;base64,...`)
    * URL and base64 can be mixed in the same array, handled by the server
    * Without `size`, output resolution = input image resolution; with `size`, output is forced to the specified ratio
  </Expandable>
</ParamField>

<Note>
  Other OpenAI standard fields (`response_format`, `style`) are not supported and will be ignored. Task results only return `url` — please download and convert to base64 yourself if needed.
</Note>

<ParamField body="official_fallback" type="boolean" default="false">
  Whether to fall back to the official channel

  * `false`: Do not use (default)
  * `true`: Use the official channel
</ParamField>

## Usage Examples

**Text-to-image (minimal request)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "A ginger cat sitting on a windowsill watching the sunset, watercolor style"
}
```

**Text-to-image (with ratio + 2K)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "a corgi astronaut on the moon, cinematic, 8k",
  "size": "16:9",
  "resolution": "2k"
}
```

**Text-to-image (4K output)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k"
}
```

**Text-to-image (multiple images)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "An ancient castle under a starry sky",
  "size": "16:9",
  "resolution": "4k",
  "n": 2
}
```

**Image-to-image (reference = URL)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "https://example.com/photo.jpg"
  ]
}
```

**Image-to-image (reference = base64)**

```json theme={null}
{
  "model": "gpt-image-2",
  "prompt": "Turn this photo into a watercolor painting",
  "image_urls": [
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  ]
}
```

**Image-to-image (multi-reference fusion, URL + base64 mixed)**

```json theme={null}
{
  "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

<ResponseField name="code" type="integer">
  Response status code
</ResponseField>

<ResponseField name="data" type="array">
  Response data array

  <Expandable title="Properties">
    <ResponseField name="status" type="string">
      Task status

      * `submitted` - Submitted
    </ResponseField>

    <ResponseField name="task_id" type="string">
      Unique task identifier, used for subsequent result queries
    </ResponseField>
  </Expandable>
</ResponseField>

## Querying Task Results

After successful submission, a `task_id` is returned. Poll the task status via `GET /v1/tasks/{task_id}`, see [Task Query API](/en/api-reference/tasks/status) for details.

### Success Response Example

```json theme={null}
{
  "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.gccai.ai/f/image/xxxxxxxx-gpt_image_2_task_xxx_0.png"
          ],
          "expires_at": 1776835126
        }
      ]
    }
  }
}
```

Image access: `data.result.images[0].url[0]`

### Task Status

| Status       | Meaning                            |
| ------------ | ---------------------------------- |
| `submitted`  | Submitted                          |
| `processing` | Being processed upstream           |
| `completed`  | Success, `result.images` available |
| `failed`     | Failed, check `error.message`      |