# Wan v2.2 A14B Text-to-Image A14B with LoRAs API

> A14B 文字轉圖像，支援用於風格調整的 LoRA 權重，以及 PNG 或 JPEG 輸出

從 `prompt` 生成圖像，並套用透過 `loras` 傳入的自訂 LoRA 權重。`image_size` 提供正方形、直向和橫向預設值，`image_format` 可為 png 或 jpeg。也提供 `guidance_scale`、`guidance_scale_2`、最多 40 的 `num_inference_steps` 和 `negative_prompt`。

- Model id: `wan/v2.2-a14b/text-to-image/lora`
- Made by: Alibaba
- Category: Text to Image
- Output: image
- Price: $0.05 / image (cheapest run $0.05 (50 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-image/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-image/lora`
- Docs page: https://doitong.com/zh-TW/developers/models/wan/v2.2-a14b/text-to-image/lora

## Pricing

Price: **$0.05 / image**. Billed per generated image.

The full example input below costs $0.05 = 50 API credits (1 image × 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.ru/v1/quote/wan/v2.2-a14b/text-to-image/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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | 引導生成圖像的文字指示。 |
| `negative_prompt` |  | string | no | `` |  | 生成影片時套用的負面提示詞。 |
| `seed` |  | integer \| null | no |  |  | 使生成結果可重現的種子。設為 None 會隨機選擇種子。 |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | 取樣步數；步數越多，處理時間越長但品質越好。 |
| `enable_safety_checker` |  | boolean | no | `false` |  | 處理前的輸入安全篩選，只有獲授權的帳戶可以關閉。未獲授權的請求一律會篩選；其他情況下，true 會啟用篩選。 |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | 控制生成影片的安全篩選；設為 true 會在生成後執行檢查。 |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | 允許大型語言模型以詳細資訊豐富提示詞。啟用此擴展不會改變提示詞的含義。 |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | 加速設定，建議選擇 'regular'。提高加速程度會犧牲品質，以縮短生成時間。 |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | 無分類器引導強度；比例越高，越貼近提示詞，但可能造成品質損失。 |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | 控制模型在第二階段遵循提示詞程度的引導強度。 |
| `shift` |  | number | no | `2` | 1 – 10 | 圖像位移設定，允許範圍為 1.0–10.0。 |
| `loras` |  | array of object {path, weight_name, scale, transformer} | no | `[]` |  | 推論期間套用的 LoRA 權重。 |
| `loras[].path` |  | string | yes |  |  | LoRA 權重的位置，以 URL 或路徑指定。 |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA 權重名稱；僅當 Hugging Face 儲存庫包含超過 1 個 safetensors 檔案時為必填。此名稱僅在 `path` 指定這類儲存庫時使用。 |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | 合併至基礎模型前套用至 LoRA 權重的倍數。 |
| `loras[].transformer` |  | enum (string) | no | `high` | `high`, `low`, `both` | LoRA 權重的 Transformer 目標。選擇 'high' 將權重套用至高雜訊 Transformer，選擇 'low' 套用至低雜訊 Transformer，或選擇 'both' 載入至兩個 Transformer。 |
| `reverse_video` |  | boolean | no | `false` |  | 影片反轉開關；true 會反轉播放方向。 |
| `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` | 生成圖像的尺寸。 |
| `image_format` |  | enum (string) | no | `jpeg` | `png`, `jpeg` | 結果圖像的檔案格式。 |

## 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.ru/v1/run/wan/v2.2-a14b/text-to-image/lora?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.ru/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.ru/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/wan/v2.2-a14b/text-to-image/lora?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.ru/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/wan/v2.2-a14b/text-to-image/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.ru/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": "wan/v2.2-a14b/text-to-image/lora",
      "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": "wan/v2.2-a14b/text-to-image/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": 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": {
    "image": {
      "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
    },
    "seed": 42
  },
  "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size} | 生成產生的圖像檔案。 |
| `seed` | integer | 生成期間套用的種子值。 |

## Related models

- [Wan-2.2 Text-to-Video A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/text-to-video/lora.md) (`wan/v2.2-a14b/text-to-video/lora`): from $0.507 / run
- [Wan v2.2 A14B Image-to-Video A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/image-to-video/lora.md) (`wan/v2.2-a14b/image-to-video/lora`): from $1.006 / run
- [Qwen Image 3 Text to Image](https://doitong.com/developers/models/alibaba/qwen-image-3/text-to-image.md) (`alibaba/qwen-image-3/text-to-image`): from $0.04 / image
- [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

## Links

- HTML page: https://doitong.com/developers/models/wan/v2.2-a14b/text-to-image/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=wan/v2.2-a14b/text-to-image/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan/v2.2-a14b/text-to-image/lora