# Qwen Image Layered · LoRA API

> تفكيك الطبقات إلى 1 إلى 10 طبقات RGBA، مع ما يصل إلى 3 LoRAs لتخصيص النتائج

يقسم الصورة الموجودة في `image_url` إلى طبقات RGBA (`num_layers` من 1 إلى 10، والقيمة الافتراضية 4)، ويقبل ما يصل إلى 3 LoRAs في `loras` لإنتاج مخرجات مخصصة. يتوفر `prompt` اختياري لوصف الصورة، و`guidance_scale` من 1 إلى 20، وما يصل إلى 50 خطوة. الإخراج بصيغة png أو webp.

- Model id: `qwen-image-layered/lora`
- Made by: Alibaba
- Category: Image Editing
- Output: image
- Price: $0.06 / image (cheapest run $0.24 (240 API credits))
- Run: `POST https://api.doitong.com/v1/run/qwen-image-layered/lora`
- Quote: `POST https://api.doitong.com/v1/quote/qwen-image-layered/lora`
- Docs page: https://doitong.com/ar/developers/models/qwen-image-layered/lora

## Pricing

Price: **$0.06 / image**. Billed per generated image (`num_layers`, default 1).

The full example input below costs $0.24 = 240 API credits (4 images × 60 API credits).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/qwen-image-layered/lora` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string \| null | no |  |  | تعليق يصف الصورة المقدمة. |
| `image_url` | `image` | string (image URL) | yes |  |  | عنوان URL لصورة المدخل. |
| `negative_prompt` |  | string | no | `` |  | الموجّه السلبي المستخدم عند توليد الصورة. |
| `num_inference_steps` |  | integer | no | `28` | 1 – 50 | عدد خطوات الاستدلال المطلوب تنفيذها. |
| `guidance_scale` |  | number | no | `5` | 1 – 20 | مقياس التوجيه المطبّق أثناء توليد الصورة. |
| `seed` |  | integer \| null | no |  |  | بذرة لصور قابلة لإعادة الإنتاج: ينتج الموجّه والبذرة المتطابقان الصورة نفسها عند عدم تغيير إصدار النموذج. |
| `num_layers` |  | integer | no | `4` | 1 – 10 | عدد الطبقات المطلوب إنتاجها. |
| `enable_safety_checker` |  | boolean | no | `true` |  | فحص السلامة، الذي يعيد صورًا سوداء بدلًا من أي صور مصنفة على أنها غير آمنة. تُمكّن القيمة true الفحص؛ وتعطله false للحسابات المخولة فقط، بينما تُفحص الطلبات من دون تخويل على أي حال. |
| `output_format` |  | enum (string) | no | `png` | `png`, `webp` | تنسيق ملف الصورة الناتجة. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | مستوى التسريع المطبّق على المعالجة. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | أوزان LoRA المراد تطبيقها، بحد أقصى 3 إدخالات. |
| `loras[].path` |  | string | yes |  |  | موقع أوزان LoRA، مقدمًا كعنوان URL أو معرّف مستودع HuggingFace بتنسيق owner/repo. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | عامل القياس المطبق على LoRA، ويتراوح من 0.0 إلى 4.0. |

File parameters (`image`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/qwen-image-layered/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/qwen-image-layered/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/qwen-image-layered/lora", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "qwen-image-layered/lora",
      "input": {
        "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "qwen-image-layered/lora",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 240,
    "usd": "0.24",
    "charged": 240,
    "refunded": 0
  },
  "input": {
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string"
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | معلومات الملفات الخاصة بالصور المولّدة. |
| `timings` | object |  |
| `seed` | integer | بذرة توليد الصورة، بما في ذلك القيمة المختارة عشوائيًا إذا لم يتضمن المدخل بذرة؛ وإلا تكرر القيمة المقدمة. |
| `has_nsfw_concepts` | array of boolean | يشير إلى ما إذا كانت مفاهيم NSFW تظهر في الصور المُولّدة. |
| `prompt` | string \| null | الموجّه المقدم لتوليد الصور. |

## Related models

- [Qwen Image Layered](https://doitong.com/developers/models/qwen-image-layered.md) (`qwen-image-layered`): $0.05 / image
- [Qwen Image 3 Edit](https://doitong.com/developers/models/alibaba/qwen-image-3/edit.md) (`alibaba/qwen-image-3/edit`): from $0.04 / image
- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Seedream 5.0 Pro Edit](https://doitong.com/developers/models/bytedance/seedream/v5/pro/edit.md) (`bytedance/seedream/v5/pro/edit`): from $0.0675 / run of output image
- [Qwen Image Edit](https://doitong.com/developers/models/qwen-image-edit.md) (`qwen-image-edit`): $0.03 / image

## Links

- HTML page: https://doitong.com/developers/models/qwen-image-layered/lora
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=qwen-image-layered/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/qwen-image-layered/lora
