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

> Wan 2.1 image-to-video، حسبِ ضرورت LoRA معاونت، اختیاری الٹی پلے بیک اور Turbo mode کے ساتھ

`prompt` سے ان پٹ تصویر (`image_url`) کو اینیمیشن دیتا ہے، اور `loras` کے ذریعے حسب ضرورت LoRA وزن استعمال کرتا ہے۔ دیگر اختیارات میں کلپ کو الٹا چلانے کے لیے `reverse_video` اور تیز تخلیق کے لیے `turbo_mode` شامل ہیں۔ ریزولوشن 480p یا 720p، `num_frames` 81-100، فریم ریٹ 5-24، اور نسبتِ ابعاد auto، 16:9، 9:16 یا 1:1 ہے۔

- 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.com/v1/run/wan-i2v-lora`
- Quote: `POST https://api.doitong.com/v1/quote/wan-i2v-lora`
- Docs page: https://doitong.com/ur/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.com/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 |  |  | ویڈیو تخلیق کی رہنمائی کرنے والی متنی ہدایات۔ |
| `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` |  | ویڈیو تخلیق کرتے وقت لاگو ہونے والا منفی پرامپٹ۔ |
| `image_url` | `image` | string (image URL) | yes |  |  | ماخذ تصویر کا URL؛ منتخب aspect ratio یہ طے کرتا ہے کہ preprocessing درکار ہے یا نہیں: عدم مطابقت سے resizing کے بعد center crop ہوتا ہے۔ |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | تخلیق کے لیے فریموں کی تعداد، 81 سے 100 تک شامل۔ |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | تخلیق کردہ ویڈیو کا فریم ریٹ، فریم per سیکنڈ میں، 5 سے 24 تک۔ |
| `seed` |  | integer \| null | no |  |  | تخلیق کو قابلِ تکرار بنانے والا سیڈ۔ اسے None پر سیٹ کرنے سے سیڈ تصادفی طور پر منتخب ہوتا ہے۔ |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `720p` | آؤٹ پٹ ویڈیو ریزولوشن، 480p یا 720p۔ |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | sampling steps کی تعداد، جس میں تعداد بڑھنے کے ساتھ زیادہ پروسیسنگ وقت کے بدلے بہتر معیار ملتا ہے۔ |
| `guide_scale` |  | number | no | `5` | 1 – 10 | Classifier-free guidance کی طاقت، اسکیل بڑھنے کے ساتھ ممکنہ معیار کے نقصان کے بدلے پرامپٹ سے زیادہ قریب مطابقت فراہم کرتی ہے۔ |
| `shift` |  | number | no | `5` | 1 – 10 | ویڈیو تخلیق کرتے وقت لاگو ہونے والی shift setting۔ |
| `enable_safety_checker` |  | boolean | no | `false` |  | Safety-checking switch؛ off setting کے لیے account authorization ضروری ہے۔ authorization کے بغیر setting سے قطع نظر ہر درخواست check کی جاتی ہے؛ true checker فعال کرتا ہے۔ |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | متعین کرتا ہے کہ پرامپٹ کی توسیع فعال ہے یا نہیں۔ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `auto`, `16:9`, `9:16`, `1:1` | آؤٹ پٹ ویڈیو کا چوڑائی سے اونچائی کا تناسب۔ |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Inference کے دوران لاگو کیے جانے والے LoRA weights۔ |
| `loras[].path` |  | string | yes |  |  | LoRA weights کا مقام، URL یا path کے طور پر۔ |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA weight name، صرف اس وقت ضروری ہے جب Hugging Face repository میں 1 سے زیادہ safetensors فائل ہو۔ یہ نام صرف اس وقت استعمال ہوتا ہے جب `path` ایسی repository کی شناخت کرے۔ |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | بنیادی ماڈل میں ضم کرنے سے پہلے LoRA weight پر لاگو ہونے والا multiplier۔ |
| `reverse_video` |  | boolean | no | `false` |  | ویڈیو الٹانے کا toggle؛ true پلے بیک کو الٹ دیتا ہے۔ |
| `turbo_mode` |  | boolean | no | `true` |  | تیز تر ویڈیو تخلیق کا toggle۔ فعال کرنے سے بصری معیار میں نمایاں کمی کے بغیر تخلیق کا وقت کم ہوتا ہے۔ |

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.com/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.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/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.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",
    "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.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": "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `video` | object {url, content_type, file_name, file_size} | تخلیق سے تیار کردہ ویڈیو فائل۔ |
| `seed` | integer | تخلیق کے دوران لاگو ہونے والی سیڈ قدر۔ |

## Related models

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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.com/v1/models/wan-i2v-lora
