# Scail 2 API

> Animuil referentno karakterosko imadžos le motioneha katar driving-video, vaj paruvavel les ando originalo scena

Lel referencakro karakterosko `image_url` thaj lidžardo `video_url` savo sikavel jekhe manušes, bute manušen vaj jekhe džukles. Ande `animation` mode karaktero kerel o lidžardo movemento; ande `replacement` mode paruvel e temu thaj rakhavel e scenа. Rezolucija si 512p vaj 704p, orientacija si ćidime katar o kipo. `driving_type` šaj te ovel direct end-to-end driving vaj eksplicitno poza skeleton.

- Model id: `scail-2`
- Made by: Open model
- Category: Video to Video
- Output: video
- Price per second of your input video: $0.20 / second of input video (cheapest run $0.20 (200 API credits))
- Run: `POST https://api.doitong.com/v1/run/scail-2`
- Quote: `POST https://api.doitong.com/v1/quote/scail-2`
- Docs page: https://doitong.com/rom/developers/models/scail-2

## Pricing

Price: **$0.20 / second of input video**. Price per second of your input video: 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 $2.00 = 2000 API credits (10 s input video × $0.20).

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/scail-2` 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 |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Prompto savo specifikuil o manglo rezultatosko video. |
| `image_url` | `image` | string (image URL) | yes |  |  | Karakterosko referencako kipo URL savo del o karaktero vaško animacija vaj zamenka e subjektoski; o driving video dikhel e animacijasa vaj zamenkasa. |
| `video_url` | `video` | string (video URL) | yes |  |  | Dino URL-esa video savo dikhel e motion, jek manušesa, but manušenca vaj životinasa. |
| `mode` |  | enum (string) | no | `animation` | `animation`, `replacement` | Alosar sar te užil pes o referencako karaktero: `replacement` astarel originalno scena numa paruvavel o karaktero vaško driving subject; `animation` aplicaril o driving motion pe karaktero. |
| `driving_type` |  | enum (string) | no | `end_to_end` | `end_to_end`, `pose` | Animacijaki motion avel direktno andar driving video maskirimo SAM3-esa e `end_to_end`-esa, standardno thaj preporučime alosaripen vaško maksimalno robustnosto. Alternativno, `pose` užil NLF/DWPose te renderil eksplicitno skeleton andar kada video, delindoj buter kontrola e pharesa inputonça. |
| `subject_type` |  | enum (string) | no | `human` | `human`, `animal` | Driving-videosko subjectosko alosaripen, kaj `animal` konfiguruil SAM3-esko detekcijako prompto vaške na-`human` subjektora. |
| `resolution` |  | enum (string) | no | `512p` | `512p`, `704p` | Rezultatoski rezolucija, orientacija automatikane dindi palal referencake kipesko aspect ratio. Landscapeθe, 512p si 896x512 thaj 704p si 1280x704; portraitθe si 512x896 thaj 704x1280. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Diffusion sampling-ako kadronqo gin. Kana bararel les, lačharel pes o kvalitet numa lel buter vaxto. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Classifier-free guidance zuralipen, balansirindoj promptoski vernosta thaj kreativita. |
| `shift` |  | number | no | `3` | 1 – 10 | Noise-schedule shift vaško flow matching, preporučime setipe 3.0 kana užil pes 512p. |
| `seed` |  | integer \| null | no |  |  | Keripesko seed savo si ande rezultato, bi te del pes eksplicitno vaj te alosarel pes random kana o inputo ačhel prazno. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Screening šaj te avel relaksirime te postavil pes false, numa kana o manglo si autorizuime. |

File parameters (`image`, `video`) 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",
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

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",
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
}
```

## 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/scail-2?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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }'

# 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/scail-2?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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  }),
});
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",
    "image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/scail-2", 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": "scail-2",
      "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",
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
      },
      "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": "scail-2",
  "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": 2000,
    "usd": "2.00",
    "charged": 2000,
    "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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
  },
  "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,
    "preprocessing_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
    },
    "preprocessing_mask_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
    }
  },
  "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-fajlo kerdino generiripeça. |
| `seed` | integer | Seed užito vaško videosko keripe. |
| `preprocessing_video` | object {url, content_type, file_name, file_size} \| null | Debug video savo si Stage-A pose-conditioning inputo dino e diffusion modeloske, dostupno numa e `output_preprocessing=true`-sa. Lesko sadržaj dependuil pe `driving_type`: `end_to_end` užil driving footage maskirimo SAM3-esa, kana `driving_type=pose` užil skeleton renderimo NLF/DWPose-esa. |
| `preprocessing_mask_video` | object {url, content_type, file_name, file_size} \| null | Stage-A driving maskako video vaško debugging, dostupno numa e `output_preprocessing=true`-sa. |

## Related models

- [AMT Interpolation](https://doitong.com/developers/models/amt-interpolation.md) (`amt-interpolation`): $0.000575 / second of processing time
- [AnimateDiff Turbo · Video to Video](https://doitong.com/developers/models/fast-animatediff/turbo/video-to-video.md) (`fast-animatediff/turbo/video-to-video`): $0.00125 / second of processing time
- [AnimateDiff · Video to Video](https://doitong.com/developers/models/fast-animatediff/video-to-video.md) (`fast-animatediff/video-to-video`): $0.00125 / second of processing time
- [Bernini-R Edit Video](https://doitong.com/developers/models/bernini-r/edit-video.md) (`bernini-r/edit-video`): from $0.04 / second of output video
- [Bernini-R Reference Edit Video](https://doitong.com/developers/models/bernini-r/reference-edit-video.md) (`bernini-r/reference-edit-video`): from $0.04 / second of output video
- [DWPose Pose Prediction · Video](https://doitong.com/developers/models/dwpose/video.md) (`dwpose/video`): $0.0006 / second of processing time
- [Editto](https://doitong.com/developers/models/editto.md) (`editto`): from $0.04 / second of output video
- [ID-V2V](https://doitong.com/developers/models/id-v2v.md) (`id-v2v`): $0.20 / second of output video

## Links

- HTML page: https://doitong.com/developers/models/scail-2
- 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=scail-2
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/scail-2