# Wan-2.1 Image-to-Video with LoRAs API

> تبدیل تصویر به ویدئوی Wan 2.1 با پشتیبانی از LoRA سفارشی، پخش معکوس اختیاری و حالت turbo

یک تصویر ورودی (`image_url`) را بر اساس `prompt` و با وزن‌های LoRA سفارشی از طریق `loras` متحرک می‌کند. گزینه‌های دیگر شامل `reverse_video` برای پخش معکوس کلیپ و `turbo_mode` برای تولید سریع‌تر هستند. وضوح 480p یا 720p، `num_frames` برابر 81-100، نرخ فریم 5-24 و نسبت تصویر auto، 16:9، 9:16 یا 1:1 است.

- Model id: `wan-i2v-lora`
- Made by: Alibaba
- Category: Image to Video
- Output: video
- Price: $0.75 / video (cheapest run $0.75 (750 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan-i2v-lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan-i2v-lora`
- Docs page: https://doitong.com/fa/developers/models/wan-i2v-lora

## Pricing

Price: **$0.75 / video**. Billed once per generated video.

The full example input below costs $0.75 = 750 API credits (1 video × 750 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-i2v-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 | yes |  |  | دستورهای متنی برای هدایت تولید ویدیو. |
| `negative_prompt` |  | string | no | `bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards` |  | پرامپت منفی اعمال‌شده هنگام تولید ویدیو. |
| `image_url` | `image` | string (image URL) | yes |  |  | نشانی اینترنتی تصویر منبع؛ نسبت تصویر انتخاب‌شده تعیین می‌کند پیش‌پردازش لازم است یا نه: ناهماهنگی باعث تغییر اندازه و سپس برش مرکزی می‌شود. |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | تعداد فریم برای تولید، از 81 تا 100 به‌صورت شامل. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | نرخ فریم ویدیوی تولیدی، برحسب فریم بر ثانیه، از 5 تا 24. |
| `seed` |  | integer \| null | no |  |  | Seed برای تکرارپذیر کردن تولید. تنظیم آن روی None، Seed را به‌صورت تصادفی انتخاب می‌کند. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | وضوح ویدیوی خروجی، 480p یا 720p. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | تعداد گام‌های نمونه‌برداری؛ با افزایش تعداد، زمان پردازش بیشتر و کیفیت بهتر می‌شود. |
| `guide_scale` |  | number | no | `5` | 1 – 10 | شدت راهنمایی بدون طبقه‌بندی؛ با افزایش مقیاس، احتمال افت کیفیت با تطبیق نزدیک‌تر با پرامپت مبادله می‌شود. |
| `shift` |  | number | no | `5` | 1 – 10 | تنظیم جابه‌جایی اعمال‌شده هنگام تولید ویدیو. |
| `enable_safety_checker` |  | boolean | no | `false` |  | کلید بررسی ایمنی که حالت خاموش آن به مجوز حساب نیاز دارد. بدون این مجوز، هر درخواست صرف‌نظر از تنظیم بررسی می‌شود؛ true بررسی‌کننده را فعال می‌کند. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | مشخص می‌کند گسترش پرامپت فعال باشد یا نه. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `auto`, `16:9`, `9:16`, `1:1` | نسبت عرض به ارتفاع ویدیوی خروجی. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | وزن‌های LoRA اعمال‌شده هنگام استنتاج. |
| `loras[].path` |  | string | yes |  |  | محل وزن‌های LoRA که به‌صورت URL یا مسیر مشخص می‌شود. |
| `loras[].weight_name` |  | string \| null | no |  |  | نام وزن LoRA؛ فقط وقتی الزامی است که یک مخزن Hugging Face بیش از 1 فایل safetensors داشته باشد. این نام فقط زمانی استفاده می‌شود که `path` چنین مخزنی را مشخص کند. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | ضریبی که پیش از ادغام LoRA در مدل پایه، روی وزن LoRA اعمال می‌شود. |
| `reverse_video` |  | boolean | no | `false` |  | کلید معکوس‌سازی ویدیو؛ مقدار true پخش را معکوس می‌کند. |
| `turbo_mode` |  | boolean | no | `true` |  | کلید تولید سریع‌تر ویدیو. فعال‌کردن آن بدون افت محسوس کیفیت بصری، زمان تولید را کاهش می‌دهد. |

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
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "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.ru/v1/run/wan-i2v-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",
    "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.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-i2v-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",
    "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.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",
    "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/wan-i2v-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-i2v-lora",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "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": "wan-i2v-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": 750,
    "usd": "0.75",
    "charged": 750,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
  },
  "output": {
    "video": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_name": "0-output.mp4",
      "file_size": 1843200
    },
    "seed": 42
  },
  "outputs": [
    {
      "type": "video",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
      "content_type": "video/mp4",
      "file_size": 1843200,
      "width": 1280,
      "height": 720,
      "duration": 5,
      "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 |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | فایل ویدیویی تولیدشده. |
| `seed` | integer | مقدار Seed اعمال‌شده هنگام تولید. |

## Related models

- [Wan 3.0 Image to Video](https://doitong.com/developers/models/alibaba/wan-3.0/image-to-video.md) (`alibaba/wan-3.0/image-to-video`): from $0.05 / second
- [FLUX 3 Max Image to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/image-to-video.md) (`blackforestlabs/flux-3-max/image-to-video`): from $0.0425 / second of output video
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- [Kling 3.0 Pro Image to Video](https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md) (`kling-video/v3/pro/image-to-video`): from $0.112 / second
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- [MiniMax H3 Image to Video](https://doitong.com/developers/models/minimax/h3/image-to-video.md) (`minimax/h3/image-to-video`): from $0.05 / second
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- [Seedance 2.0 Image to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/image-to-video.md) (`bytedance/seedance-2.0/image-to-video`): from $0.141 / second

## Links

- HTML page: https://doitong.com/developers/models/wan-i2v-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-i2v-lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan-i2v-lora