# MOSS Image API

> نموذج لتحويل النص إلى صورة، يدعم النصين الصيني والإنجليزي داخل الصور، مع مطالبات تراعي التخطيط وتوسيعًا اختياريًا

ينشئ صورًا من `prompt` يصل إلى 16384 حرفًا، مكتوبًا بلغة طبيعية أو على شكل تسلسلات من الوسوم أو تخطيطات JSON، ما يساعد على وضع النصوص والعناصر بدقة. يخطط توسيع المطالبة لتخطيط منظم أولًا، وهو مفعّل افتراضيًا. تأتي الأحجام من ستة إعدادات مسبقة (مربعة وعمودية وأفقية)، وتُقرّب إلى مضاعفات 16 بين 512 و2048 بكسل. يمكنك طلب من 1 إلى 4 صور مع 1 إلى 100 خطوة، وتعيين `guidance_scale` من 0 إلى 10، واستخدام `negative_prompt` و`seed`، وإخراج الصور بصيغ JPEG أو PNG أو WebP.

- Model id: `moss-image`
- Made by: Open model
- Category: Text to Image
- Output: image
- Price: $0.05 / megapixel (cheapest run $0.05 (50 API credits))
- Run: `POST https://api.doitong.com/v1/run/moss-image`
- Quote: `POST https://api.doitong.com/v1/quote/moss-image`
- Docs page: https://doitong.com/ar/developers/models/moss-image

## Pricing

Price: **$0.05 / megapixel**. Billed per megapixel of output (width × height of every image). Each image is rounded up to a whole megapixel.

The full example input below costs $0.05 = 50 API credits (1 MP × 50 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/moss-image` 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 | yes |  | 1 – 16384 characters | موجّه لتوليد الصورة يقبل اللغة الطبيعية أو تسلسلات العلامات أو تخطيطات JSON. |
| `negative_prompt` |  | string | no | `` | ≤ 16384 characters | موجّه سلبي يُستخدم للتوجيه، مع توفير تخطي طبقة المحوّل للفرع السلبي عندما يكون الموجّه فارغًا. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | تحسين للموجّه يحتفظ بأي نص مرئي مطلوب أثناء تخطيط تخطيط منظم لأبعاد الصورة المحددة قبل التوليد. يبقى الموجّه الأصلي مستخدمًا إذا لم يتوفر التحسين. |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | أبعاد المخرج مقيّدة من 512 إلى 2048 بكسل لكل من العرض والارتفاع، مع تقريب كل منهما إلى مضاعف 16. |
| `num_inference_steps` |  | integer | no | `50` | 1 – 100 | عدد خطوات إزالة التشويش المطلوب تنفيذها. |
| `guidance_scale` |  | number | no | `3` | 0 – 10 | قوة التوجيه الخالي من المصنف. |
| `seed` |  | integer \| null | no |  |  | بذرة عشوائية تجعل التوليد قابلاً لإعادة الإنتاج. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | عدد الصور المطلوب إنتاجها. |
| `enable_safety_checker` |  | boolean | no | `true` |  | تحكم في الإشراف على المخرج لا يمكن تعطيله إلا للحسابات المصرح لها؛ وتخضع جميع الطلبات الأخرى للفحوص بغض النظر عن هذا الإعداد. تُعاد صورة سوداء بدلًا من أي صورة يُبلغ عنها بأنها غير آمنة. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png`, `webp` | تنسيق الصورة الناتجة. |

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## 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/moss-image?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# 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/moss-image?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
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 = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/moss-image", 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": "moss-image",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "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": "moss-image",
  "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": 50,
    "usd": "0.05",
    "charged": 50,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "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
      }
    ],
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "actual_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} | الصور الناتجة عن التوليد. |
| `seed` | integer | البذرة المطبقة عند توليد الصورة الأولى. |
| `has_nsfw_concepts` | array of boolean | مؤشر المحتوى غير الآمن لكل صورة مُولّدة. |
| `actual_prompt` | string \| null | الموجّه المحسّن المطبق أثناء التوليد إذا نجح توسيع الموجّه. |

## Related models

- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image
- [Nano Banana Pro](https://doitong.com/developers/models/nano-banana-pro.md) (`nano-banana-pro`): from $0.15 / image

## Links

- HTML page: https://doitong.com/developers/models/moss-image
- 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=moss-image
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/moss-image