# Wan 2.2 14B Image Trainer API

> Yn hyfforddi Wan 2.2 14B LoRA ar eich delweddau ar gyfer pwnc neu steil, gan ddychwelyd ffeiliau LoRA sŵn isel ac uchel

Yn mireinio LoRA ar gyfer Wan 2.2 text-to-image o set ddata yn `training_data_url`, wedi'i chysylltu â `trigger_phrase` gofynnol. Mae `steps` yn amrywio o 10 i 6000 a `learning_rate` o 1e-6 i 0.1. Gellir toglo canfod wynebau, torri wynebau a masgiau, ac mae `is_style` yn diffodd yr opsiynau wyneb-benodol. Mae'r allbwn yn cynnwys ffeil ffurfweddu ynghyd â ffeiliau LoRA sŵn isel ac uchel ar wahân.

- Model id: `wan-22-image-trainer`
- Made by: Alibaba
- Category: Training
- Output: file
- Price per run: from $0.45 / run (cheapest run $0.45 (450 API credits))
- Run: `POST https://api.doitong.ru/v1/run/wan-22-image-trainer`
- Quote: `POST https://api.doitong.ru/v1/quote/wan-22-image-trainer`
- Docs page: https://doitong.com/cy/developers/models/wan-22-image-trainer

## Pricing

Price: **from $0.45 / run** (the lowest tier; the quote prices your exact input). Price per run: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $4.50 = 4500 API credits (1 run × $4.50).

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-22-image-trainer` 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 |
|---|---|---|---|---|---|---|
| `training_data_url` |  | string | yes |  |  | Lleoliad data hyfforddi fel URL. |
| `trigger_phrase` |  | string | yes |  |  | Ymadrodd a ddefnyddir i sbarduno'r model. |
| `include_synthetic_captions` |  | boolean | no | `false` |  | Yn rheoli cynnwys capsiynau synthetig. |
| `use_face_detection` |  | boolean | no | `true` |  | Toglo newid maint wedi'i ganoli ar yr wyneb ar gyfer delweddau hyfforddi: mae galluogi canfod wyneb yn gwneud canol yr wyneb a ganfuwyd yn ganol y ddelwedd wrth newid maint. |
| `use_face_cropping` |  | boolean | no | `false` |  | Toglo cnydio wyneb ar gyfer delweddau hyfforddi, gan ychwanegu cnwd o amgylch yr wyneb cyn y cam newid maint pan gaiff ei alluogi. |
| `use_masks` |  | boolean | no | `true` |  | Yn rheoli defnydd masgiau ar gyfer data hyfforddi. |
| `steps` |  | integer | no | `1000` | 10 – 6,000 | Cyfanswm y camau hyfforddi. |
| `learning_rate` |  | number | no | `0.0007` | 0.000001 – 0.1 | Cyfradd dysgu yn ystod hyfforddi. |
| `is_style` |  | boolean | no | `false` |  | Dynodiad data arddull ar gyfer hyfforddi; mae ei osod i true yn diffodd nodweddion penodol i wynebau, gan gynnwys masgio a chanfod wynebau. |

## Example input

Required parameters only:

```json
{
  "training_data_url": "https://example.com/your-file.zip",
  "trigger_phrase": "example"
}
```

A fuller example:

```json
{
  "training_data_url": "https://example.com/your-file.zip",
  "trigger_phrase": "example"
}
```

## 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-22-image-trainer?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "training_data_url": "https://example.com/your-file.zip",
    "trigger_phrase": "example"
  }'

# 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-22-image-trainer?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "training_data_url": "https://example.com/your-file.zip",
    "trigger_phrase": "example"
  }),
});
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 = {
    "training_data_url": "https://example.com/your-file.zip",
    "trigger_phrase": "example",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/wan-22-image-trainer", 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-22-image-trainer",
      "input": {
        "training_data_url": "https://example.com/your-file.zip",
        "trigger_phrase": "example"
      },
      "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-22-image-trainer",
  "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": 4500,
    "usd": "4.50",
    "charged": 4500,
    "refunded": 0
  },
  "input": {
    "training_data_url": "https://example.com/your-file.zip",
    "trigger_phrase": "example"
  },
  "output": {
    "diffusers_lora_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "high_noise_lora": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    },
    "config_file": {
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_name": "0-output.jpeg",
      "file_size": 1843200
    }
  },
  "outputs": [
    {
      "type": "file",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "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 |
|---|---|---|
| `diffusers_lora_file` | object {url, content_type, file_name, file_size} | Ffeil LoRA ar gyfer sŵn isel. |
| `high_noise_lora` | object {url, content_type, file_name, file_size} | Ffeil LoRA ar gyfer sŵn uchel. |
| `config_file` | object {url, content_type, file_name, file_size} | Ffeil ffurfweddiad sy'n cefnogi diweddbwyntiau casgliad ar ôl hyfforddi. |

## Related models

- [Qwen Image 2512 Trainer](https://doitong.com/developers/models/qwen-image-2512-trainer.md) (`qwen-image-2512-trainer`): from $0.75 / run
- [Qwen Image Edit 2509 Trainer](https://doitong.com/developers/models/qwen-image-edit-2509-trainer.md) (`qwen-image-edit-2509-trainer`): from $0.40 / run
- [Wan-2.1 LoRA Trainer · I2V 720p](https://doitong.com/developers/models/wan-trainer/i2v-720p.md) (`wan-trainer/i2v-720p`): $0.005 / step
- [Wan-2.1 LoRA Trainer · T2V](https://doitong.com/developers/models/wan-trainer/t2v.md) (`wan-trainer/t2v`): $0.005 / step
- [Wan-2.1 LoRA Trainer · T2V 14b](https://doitong.com/developers/models/wan-trainer/t2v-14b.md) (`wan-trainer/t2v-14b`): $0.005 / step
- [Wan-2.2 LoRA Trainer · I2V A14b](https://doitong.com/developers/models/wan-22-trainer/i2v-a14b.md) (`wan-22-trainer/i2v-a14b`): $0.005 / step
- [Wan-2.2 LoRA Trainer · T2V A14b](https://doitong.com/developers/models/wan-22-trainer/t2v-a14b.md) (`wan-22-trainer/t2v-a14b`): $0.004 / step
- [Z Image Trainer](https://doitong.com/developers/models/z-image-trainer.md) (`z-image-trainer`): $0.00226 / step

## Links

- HTML page: https://doitong.com/developers/models/wan-22-image-trainer
- 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-22-image-trainer
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.ru/v1/models/wan-22-image-trainer