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

> Wan 2.1 za pretvorbo besedila v videoposnetek, ki sprejema prilagojene uteži LoRA ter podpira turbo način in izbirno obračanje

Ustvari videoposnetek iz besedilnega `prompt` in uporabi prilagojene LoRA, navedene v `loras`. Ločljivost je 480p, 580p ali 720p, razmerje stranic pa 16:9 ali 9:16. `num_frames` je od 81 do 100, `frames_per_second` od 5 do 24. `turbo_mode` je privzeto vklopljen, `reverse_video` pa rezultat predvaja nazaj.

- Model id: `wan-t2v-lora`
- Made by: Alibaba
- Category: Text to Video
- Output: video
- Price: $0.75 / video (cheapest run $0.75 (750 API credits))
- Run: `POST https://api.doitong.com/v1/run/wan-t2v-lora`
- Quote: `POST https://api.doitong.com/v1/quote/wan-t2v-lora`
- Docs page: https://doitong.com/sl/developers/models/wan-t2v-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-t2v-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 |  |  | Besedilna navodila, ki usmerjajo generiranje videa. |
| `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` |  | Negativni poziv, uporabljen pri generiranju videa. |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | Število sličic za generiranje, od 81 do vključno 100. |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | Hitrost sličic ustvarjenega videa v sličicah na sekundo, od 5 do 24. |
| `seed` |  | integer \| null | no |  |  | Seme, ki omogoča ponovljivo generiranje. Če ga nastavite na None, se seme izbere naključno. |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `580p`, `720p` | Ločljivost izhodnega videa: 480p, 580p ali 720p. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `16:9` | Razmerje stranic izhodnega videa, bodisi 16:9 bodisi 9:16. |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | Število korakov vzorčenja; večje število pomeni daljšo obdelavo in boljšo kakovost. |
| `enable_safety_checker` |  | boolean | no | `false` |  | Preklop preverjanja varnosti, pri katerem izklopljena nastavitev zahteva avtorizacijo računa. Brez te avtorizacije se vsaka zahteva preveri ne glede na nastavitev; true omogoči preverjanje. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Določa, ali je razširjanje poziva omogočeno. |
| `turbo_mode` |  | boolean | no | `true` |  | Preklop za hitrejše generiranje videa. Omogočitev skrajša čas generiranja brez opazne izgube vizualne kakovosti. |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Uteži LoRA, uporabljene med sklepanjem. |
| `loras[].path` |  | string | yes |  |  | Lokacija uteži LoRA, navedena kot URL ali pot. |
| `loras[].weight_name` |  | string \| null | no |  |  | Ime uteži LoRA, zahtevano samo, če repozitorij Hugging Face vsebuje več kot 1 datoteko safetensors. To ime se uporabi samo, ko `path` določa tak repozitorij. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Množilnik, uporabljen za utež LoRA, preden se združi z osnovnim modelom. |
| `reverse_video` |  | boolean | no | `false` |  | Preklop za obračanje videa; true obrne predvajanje. |

## 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.com/v1/run/wan-t2v-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.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-t2v-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.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",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/wan-t2v-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-t2v-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-t2v-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"
  },
  "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} | Video datoteka, ustvarjena z generiranjem. |
| `seed` | integer | Vrednost semena, uporabljena pri generiranju. |

## Related models

- [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
- [Seedance 2.0 Fast Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/fast/text-to-video.md) (`bytedance/seedance-2.0/fast/text-to-video`): from $0.113 / second
- [Seedance 2.0 Text to Video](https://doitong.com/developers/models/bytedance/seedance-2.0/text-to-video.md) (`bytedance/seedance-2.0/text-to-video`): from $0.141 / second

## Links

- HTML page: https://doitong.com/developers/models/wan-t2v-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-t2v-lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/wan-t2v-lora