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

> A14B attēla pārvēršana video, kas pieņem Wan 2.2 LoRA svarus un var atskaņot klipu pretējā virzienā

Animē `image_url` pēc `prompt`, izmantojot pielāgotus LoRA svarus, kas nodoti ar `loras`. Neobligāts `end_image_url` nosaka pēdējo kadru, bet `reverse_video` atskaņo rezultātu atpakaļgaitā. `num_frames` ir no 17 līdz 161, `resolution` — no 480p līdz 720p, un malu attiecība var būt auto, 16:9, 9:16 vai 1:1.

- Model id: `wan/v2.2-a14b/image-to-video/lora`
- Made by: Alibaba
- Category: Image to Video
- Output: video
- Estimated price per run: from $1.006 / run (cheapest run $1.006 (1006 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/image-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/image-to-video/lora`
- Docs page: https://doitong.com/lv/developers/models/wan/v2.2-a14b/image-to-video/lora

## Pricing

Price: **from $1.006 / run** (the lowest tier; the quote prices your exact input). Estimated from the typical cost of one run. The quote is exactly what the run charges.

Price rules (the first rule that matches the input wins; a parameter you leave out counts as its default):

- When `num_frames` > 81 and `resolution` = 480p: base price × 2
- When `num_frames` > 81 and `resolution` = 580p: base price × 2
- When `num_frames` > 81 and `resolution` = 720p: base price × 2

The full example input below costs $1.006 = 1006 API credits (1 request × 1006 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/image-to-video/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 |
|---|---|---|---|---|---|---|
| `image_url` | `image` | string (image URL) | yes |  |  | Avota attēla URL; atlasītā malu attiecība nosaka, vai nepieciešama priekšapstrāde: neatbilstība aktivizē izmēra maiņu un pēc tam centrālo apgriešanu. |
| `prompt` |  | string | yes |  |  | Teksta norādes video ģenerēšanai. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Kadru skaits ģenerēšanai ar diapazonu 17–161 ieskaitot. |
| `frames_per_second` |  | integer \| null | no | `16` | 4 – 60 | Ģenerētā video kadru nomaiņas ātrums, pieņemot vērtības no 4 līdz 60; iestatot `adjust_fps_for_interpolation` uz false, šis ātrums tiek saglabāts nemainīgs. Izmantojot interpolāciju un iestatot `adjust_fps_for_interpolation` uz true (noklusējums), reiziniet šo ātrumu ar viens plus interpolēto kadru skaits, lai iegūtu galīgo FPS. Piemēram, 16 FPS ar 1 interpolētu kadru kļūst par 32 FPS. |
| `negative_prompt` |  | string | no | `` |  | Negatīvā uzvedne, kas tiek lietota video ģenerēšanas laikā. |
| `seed` |  | integer \| null | no |  |  | Sēkla, kas padara ģenerēšanu atkārtojamu. Iestatot None, sēkla tiek izvēlēta nejauši. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Izvades video izšķirtspēja: 480p, 580p vai 720p. |
| `aspect_ratio` |  | enum (string) | no | `auto` | `auto`, `16:9`, `9:16`, `1:1` | Ģenerētā video proporcijas, kas tiek automātiski izvēlētas no ievades attēla, ja iestatīta 'auto'. |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | Semplešanas soļu skaits; lielāks skaits nodrošina labāku kvalitāti, bet paildzina apstrādi. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Ievades drošības pārbaude pirms apstrādes, ko drīkst atspējot tikai autorizēti konti. Pieprasījumi bez autorizācijas vienmēr tiek pārbaudīti; pretējā gadījumā true iespējo pārbaudi. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Nosaka ģenerētā video drošības pārbaudi; true iespējo pārbaudi pēc ģenerēšanas. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Ļauj lielajam valodas modelim papildināt uzvedni ar detalizētu informāciju. Šī paplašināšana nemaina uzvednes nozīmi. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | Paātrinājuma iestatījums; ieteicamā izvēle ir 'regular'. Lielāks paātrinājums samazina kvalitāti, lai saīsinātu ģenerēšanas laiku. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Klasifikatora brīvās vadības stiprums; palielinoties mērogam, iespējams kvalitātes zudums tiek mainīts pret precīzāku atbilstību uzvednei. |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | Vadības mērogs, kas nosaka, cik cieši modelis savā otrajā posmā seko uzvednei. |
| `shift` |  | number | no | `5` | 1 – 10 | Video nobīdes iestatījums ar pieļaujamo diapazonu 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Kadru interpolācijas iestatījums: izvēlieties None, lai izlaistu interpolāciju, vai norādiet modeli tās veikšanai. |
| `num_interpolated_frames` |  | integer | no | `1` | 0 – 4 | Ievietojiet 0–4 interpolētus kadrus katrā spraugā starp diviem ģenerētiem kadriem. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kadru nomaiņas ātruma pielāgošanas slēdzis: false saglabā norādīto FPS, bet true to reizina ar viens plus interpolēto kadru skaitu. Tādējādi 16 FPS kļūst par 32 FPS, ja tiek interpolēts 1 kadrs un pielāgošana ir iespējota. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Izvades video kvalitātes iestatījums, kas, palielinoties vērtībai, maina lielākus failus pret labāku attēlu. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Video rakstīšanas režīms; balanced nodrošina kompromisu starp ātrumu un kvalitāti. Izvēlieties small mazākajiem failiem un lēnākajai rakstīšanai; ātrāka rakstīšana rezultātus atgriež ātrāk, bet izveido lielākus failus. |
| `loras` |  | array of object {path, weight_name, scale, transformer} | no | `[]` |  | LoRA svari, kas tiek lietoti secināšanas laikā. |
| `loras[].path` |  | string | yes |  |  | LoRA svaru atrašanās vieta, norādīta kā URL vai ceļš. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA svara nosaukums, nepieciešams tikai tad, ja Hugging Face repozitorijā ir vairāk nekā 1 safetensors fails. Šis nosaukums tiek izmantots tikai tad, ja `path` identificē šādu repozitoriju. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Reizinātājs, kas tiek lietots LoRA svaram pirms tā sapludināšanas ar pamata modeli. |
| `loras[].transformer` |  | enum (string) | no | `high` | `high`, `low`, `both` | Transformatora mērķis LoRA svaram. Izvēlieties 'high' augsta trokšņa transformatoram, 'low' zema trokšņa transformatoram vai 'both', lai svaru ielādētu abos transformatoros. |
| `reverse_video` |  | boolean | no | `false` |  | Video atskaņošanas apvēršanas slēdzis; true apvērš atskaņošanu. |
| `end_image_url` | `end_image` | string (image URL) \| null | no |  |  | URL, kas norāda uz beigu attēlu. |

File parameters (`image`, `end_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/v2.2-a14b/image-to-video/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/v2.2-a14b/image-to-video/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/v2.2-a14b/image-to-video/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/image-to-video/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/v2.2-a14b/image-to-video/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": 1006,
    "usd": "1.006",
    "charged": 1006,
    "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
    },
    "prompt": "The white dragon warrior stands still, eyes full of determination and strength. The camera slowly moves closer or circles around the warrior, highlighting the powerful presence and heroic spirit of the character.",
    "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} | Ģenerēšanas rezultātā iegūtais video fails. |
| `prompt` | string | Teksta uzvedne, kas izmantota video ģenerēšanai. |
| `seed` | integer | Ģenerēšanas laikā lietotā sēklas vērtība. |

## Related models

- [Wan v2.2 A14B Text-to-Image A14B with LoRAs](https://doitong.com/developers/models/wan/v2.2-a14b/text-to-image/lora.md) (`wan/v2.2-a14b/text-to-image/lora`): $0.05 / image
- [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 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
- [Grok Imagine Video 1.5 Image to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/image-to-video.md) (`xai/grok-imagine-video/v1.5/image-to-video`): from $0.082 / second
- [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
- [LTX 2.5 Pro Image to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/image-to-video/pro.md) (`lightricks/ltx-2.5/image-to-video/pro`): from $0.12 / second
- [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

## Links

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