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

> စိတ်ကြိုက် LoRA Weights၊ အမြန်စနစ်နှင့် ရွေးချယ်နိုင်သော reversal ကို လက်ခံသည့် Wan 2.1 စာသားမှဗီဒီယို

စာသား `prompt` မှ ဗီဒီယိုကို ဖန်တီးပြီး `loras` တွင် စာရင်းပြုထားသော စိတ်ကြိုက် LoRA များကို အသုံးပြုသည်။ ရုပ်ထွက်အရည်အသွေးမှာ 480p၊ 580p သို့မဟုတ် 720p ဖြစ်ပြီး အချိုးအစားမှာ 16:9 သို့မဟုတ် 9:16 ဖြစ်သည်။ `num_frames` သည် 81 မှ 100 အထိ၊ `frames_per_second` သည် 5 မှ 24 အထိ ဖြစ်သည်။ `turbo_mode` ကို မူလတန်ဖိုးအဖြစ် ဖွင့်ထားပြီး `reverse_video` သည် ရလဒ်ကို နောက်ပြန်ဖွင့်သည်။

- 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/my/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 |  |  | ဗီဒီယိုဖန်တီးမှုကို လမ်းညွှန်သည့် စာသားညွှန်ကြားချက်များ။ |
| `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` |  | ဗီဒီယိုဖန်တီးရာတွင် အသုံးပြုသည့် အနုတ်လက္ခဏာပရောမ့်။ |
| `num_frames` |  | integer \| null | no | `81` | 81 – 100 | ဖန်တီးမှုအတွက် ဖရိမ်အရေအတွက်ဖြစ်ပြီး 81 မှ 100 အထိ ပါဝင်သည်။ |
| `frames_per_second` |  | integer \| null | no | `16` | 5 – 24 | ဖန်တီးထားသောဗီဒီယို၏ တစ်စက္ကန့်လျှင် ဖရိမ်အရေအတွက်ဖြစ်ပြီး 5 မှ 24 အထိ ဖြစ်သည်။ |
| `seed` |  | integer \| null | no |  |  | ဖန်တီးမှုကို ထပ်တူပြန်လည်ပြုလုပ်နိုင်စေသည့် seed။ None သတ်မှတ်ပါက seed ကို ကျပန်းရွေးချယ်သည်။ |
| `resolution` |  | enum (string) | no | `480p` | `480p`, `580p`, `720p` | ထွက်ရလဒ်ဗီဒီယို ရုပ်ထွက်အရည်အသွေး: 480p၊ 580p သို့မဟုတ် 720p။ |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `9:16`, `16:9` | ထွက်ရလဒ်ဗီဒီယို၏ aspect ratio၊ 16:9 သို့မဟုတ် 9:16 ဖြစ်နိုင်သည်။ |
| `num_inference_steps` |  | integer | no | `30` | 2 – 40 | နမူနာယူမှု အဆင့်အရေအတွက်။ အရေအတွက်မြင့်လာသည်နှင့်အမျှ လုပ်ဆောင်ချိန် ပိုကြာသော်လည်း အရည်အသွေး ပိုကောင်းလာသည်။ |
| `enable_safety_checker` |  | boolean | no | `false` |  | ပိတ်ထားသော setting အတွက် အကောင့်အတည်ပြုချက် လိုအပ်သော ဘေးကင်းရေးစစ်ဆေးမှု switch ဖြစ်သည်။ ထိုအတည်ပြုချက်မရှိပါက setting မည်သို့ပင်ဖြစ်စေ တောင်းဆိုချက်တိုင်းကို စစ်ဆေးမည်။ true သည် စစ်ဆေးမှုကို ဖွင့်ပေးသည်။ |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | ပရောမ့်ချဲ့ထွင်မှု ဖွင့်ထားခြင်း ရှိ၊ မရှိ ထိန်းချုပ်သည်။ |
| `turbo_mode` |  | boolean | no | `true` |  | ပိုမိုမြန်ဆန်သော ဗီဒီယိုဖန်တီးမှုခလုတ်။ ဖွင့်ထားပါက မြင်သာသောအရည်အသွေး မကျဆင်းဘဲ ဖန်တီးချိန်ကို လျှော့ချပေးသည်။ |
| `loras` |  | array of object {path, weight_name, scale} | no | `[]` |  | Inference အတွင်း အသုံးပြုသည့် LoRA အလေးချိန်များ။ |
| `loras[].path` |  | string | yes |  |  | URL သို့မဟုတ် path အဖြစ် သတ်မှတ်ထားသော LoRA weights တည်နေရာ။ |
| `loras[].weight_name` |  | string \| null | no |  |  | Hugging Face repository တွင် safetensors ဖိုင် 1 ခုထက်ပိုပါကသာ လိုအပ်သော LoRA weight name။ `path` က ထိုသို့သော repository ကို သတ်မှတ်သည့်အခါတွင်သာ ဤအမည်ကို အသုံးပြုသည်။ |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | အခြေခံမော်ဒယ်သို့ မပေါင်းစပ်မီ LoRA weight တွင် အသုံးပြုသော multiplier။ |
| `reverse_video` |  | boolean | no | `false` |  | ဗီဒီယိုပြောင်းပြန်ဖွင့်ရန် ခလုတ်ဖြစ်ပြီး true ဖြစ်ပါက ပြန်လှန်ဖွင့်သည်။ |

## 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} | ဖန်တီးမှုမှ ထွက်ရှိသည့် ဗီဒီယိုဖိုင်။ |
| `seed` | integer | ဖန်တီးမှုအတွင်း အသုံးပြုသည့် seed တန်ဖိုး။ |

## 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