# Wan-2.2 Text-to-Video A14B with LoRAs API

> A14B text-to-video yenye usaidizi wa LoRA na uchezaji wa kinyume wa hiari

Hutengeneza video kutoka kwa `prompt` ya maandishi huku ikitumia uzani wa LoRA ulioorodheshwa katika `loras`. `reverse_video` huchezesha klipu kinyume. `num_frames` huanzia 17 hadi 161, `resolution` ni 480p, 580p au 720p, na uwiano wa vipimo ni 16:9, 9:16 au 1:1. Interpolation ya film au rife na mizani miwili ya mwongozo zinapatikana.

- Model id: `wan/v2.2-a14b/text-to-video/lora`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Estimated price per run: from $0.507 / run (cheapest run $0.507 (507 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-video/lora`
- Quote: `POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-video/lora`
- Docs page: https://doitong.com/sw/developers/models/wan/v2.2-a14b/text-to-video/lora

## Pricing

Price: **from $0.507 / 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 $0.507 = 507 API credits (1 request × 507 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-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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Maelekezo ya maandishi yanayoongoza uzalishaji wa video. |
| `negative_prompt` |  | string | no | `` |  | Kidokezo hasi kinachotumika wakati wa kutengeneza video. |
| `num_frames` |  | integer | no | `81` | 17 – 161 | Idadi ya fremu za uzalishaji, yenye masafa jumuishi ya 17–161. |
| `frames_per_second` |  | integer \| null | no | `16` | 4 – 60 | Kasi ya fremu za video iliyozalishwa, inayokubali thamani kutoka 4 hadi 60; kuweka `adjust_fps_for_interpolation` kuwa false huhifadhi kasi hii bila mabadiliko. Interpolation inapotumika na `adjust_fps_for_interpolation` ikiwa true (chaguo lake chaguomsingi), zidisha kasi hii kwa moja pamoja na idadi ya fremu zilizointerpolatiwa ili kupata FPS ya mwisho. Kwa mfano, 16 FPS yenye fremu 1 iliyointerpolatiwa huwa 32 FPS. |
| `seed` |  | integer \| null | no |  |  | Seed inayofanya uzalishaji uweze kurudiwa. Kuiweka kuwa None huchagua seed bila mpangilio. |
| `resolution` |  | enum (string) | no | `720p` | `480p`, `580p`, `720p` | Mwonekano wa video ya tokeo: 480p, 580p au 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `16:9`, `9:16`, `1:1` | Uwiano wa video ya tokeo, ama 16:9 au 9:16. |
| `num_inference_steps` |  | integer | no | `27` | 2 – 40 | Idadi ya hatua za sampuli, ambapo muda mrefu wa uchakataji huleta ubora bora kadiri idadi inavyoongezeka. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Ukaguzi wa usalama wa ingizo kabla ya uchakataji, ambao ni akaunti zilizoidhinishwa pekee zinazoweza kuuzima. Maombi yasiyo na idhini hukaguliwa kila mara; vinginevyo, true huwezesha ukaguzi. |
| `enable_output_safety_checker` |  | boolean | no | `false` |  | Hudhibiti ukaguzi wa usalama wa video iliyozalishwa; kuweka true huwezesha ukaguzi baada ya uzalishaji. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Ruhusu modeli kubwa ya lugha kuimarisha kidokezo kwa maelezo. Kuwasha upanuzi huu hakubadilishi maana ya kidokezo. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular` | Mpangilio wa kuongeza kasi, ambapo 'regular' ndiyo chaguo linalopendekezwa. Kuongeza kasi hupunguza ubora ili kufupisha muda wa uzalishaji. |
| `guidance_scale` |  | number | no | `3.5` | 1 – 10 | Nguvu ya mwongozo isiyotegemea kiainishaji, ambapo ongezeko la kipimo hubadilisha uwezekano wa kupoteza ubora kwa ulinganifu wa karibu zaidi na kidokezo. |
| `guidance_scale_2` |  | number | no | `4` | 1 – 10 | Mizani ya mwongozo inayodhibiti jinsi modeli inavyofuata kidokezo katika hatua yake ya pili. |
| `shift` |  | number | no | `5` | 1 – 10 | Mpangilio wa mgeuzo wa video, wenye masafa yanayoruhusiwa ya 1.0–10.0. |
| `interpolator_model` |  | enum (string) | no | `film` | `none`, `film`, `rife` | Mpangilio wa interpolation ya fremu: chagua None kuruka interpolation, au bainisha modeli ya kuitekeleza. |
| `num_interpolated_frames` |  | integer | no | `1` | 0 – 4 | Weka fremu 0–4 zilizointerpolatiwa katika kila pengo kati ya fremu mbili zilizozalishwa. |
| `adjust_fps_for_interpolation` |  | boolean | no | `true` |  | Kigeuzi cha kurekebisha kasi ya fremu: false huhifadhi FPS iliyotolewa, ilhali true huizidisha kwa moja pamoja na idadi ya fremu zilizointerpolatiwa. Hivyo, 16 FPS huwa 32 FPS wakati fremu 1 imeinterpolatiwa na urekebishaji umewezeshwa. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Mpangilio wa ubora wa video ya tokeo unaobadilisha ukubwa wa faili kwa picha bora zaidi kadiri thamani inavyoongezeka. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Hali ya kuandika video, ambapo balanced hutoa uwiano kati ya kasi na ubora. Chagua small kwa faili ndogo zaidi na uandishi wa polepole zaidi; uandishi wa haraka hurudisha matokeo mapema lakini huunda faili kubwa zaidi. |
| `loras` |  | array of object {path, weight_name, scale, transformer} | no | `[]` |  | Uzito wa LoRA unaotumika wakati wa inference. |
| `loras[].path` |  | string | yes |  |  | Mahali pa uzani wa LoRA, palipobainishwa kama URL au njia. |
| `loras[].weight_name` |  | string \| null | no |  |  | Jina la uzito wa LoRA, linalohitajika tu wakati hazina ya Hugging Face ina zaidi ya faili 1 la safetensors. Jina hili hutumika tu wakati `path` inabainisha hazina hiyo. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Kizidishi kinachotumika kwenye uzito wa LoRA kabla ya kuunganishwa na modeli msingi. |
| `loras[].transformer` |  | enum (string) | no | `high` | `high`, `low`, `both` | Lengwa la transformer kwa uzito wa LoRA. Chagua 'high' kwa transformer yenye kelele nyingi, 'low' kwa transformer yenye kelele kidogo, au 'both' kupakia uzito kwenye transformer zote mbili. |
| `reverse_video` |  | boolean | no | `false` |  | Kigeuzi cha kurudisha video nyuma; true hurudisha uchezaji nyuma. |

## 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-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"
  }'

# 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-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"
  }),
});
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-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/text-to-video/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-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": 507,
    "usd": "0.507",
    "charged": 507,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "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": "A close-up of a young woman smiling gently in the rain, raindrops glistening on her face and eyelashes. The video captures the delicate details of her expression and the water droplets, with soft light reflecting off her skin in the rainy atmosphere.",
    "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} | Faili ya video iliyozalishwa. |
| `prompt` | string | Kidokezo cha maandishi kilichotumika kuzalisha video. |
| `seed` | integer | Thamani ya seed inayotumika wakati wa uzalishaji. |

## 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 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
- [Wan 3.0 Text to Video](https://doitong.com/developers/models/alibaba/wan-3.0/text-to-video.md) (`alibaba/wan-3.0/text-to-video`): from $0.05 / second
- [FLUX 3 Max Text to Video](https://doitong.com/developers/models/blackforestlabs/flux-3-max/text-to-video.md) (`blackforestlabs/flux-3-max/text-to-video`): from $0.0425 / second of output video
- [Grok Imagine Video 1.5 Text to Video](https://doitong.com/developers/models/xai/grok-imagine-video/v1.5/text-to-video.md) (`xai/grok-imagine-video/v1.5/text-to-video`): from $0.08 / second
- [Kling 3.0 Pro Text to Video](https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md) (`kling-video/v3/pro/text-to-video`): from $0.112 / second
- [LTX 2.5 Pro Text to Video](https://doitong.com/developers/models/lightricks/ltx-2.5/text-to-video/pro.md) (`lightricks/ltx-2.5/text-to-video/pro`): from $0.12 / second
- [MiniMax H3 Text to Video](https://doitong.com/developers/models/minimax/h3/text-to-video.md) (`minimax/h3/text-to-video`): from $0.05 / second

## Links

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