# Scail 2 API

> Ina-animate ang reference character larawan gamit ang motion mula sa driving video, o ipinapalit ito sa orihinal na eksena

Tumatanggap ng reference character `image_url` at driving `video_url` na nagpapakita ng tao, maraming tao o hayop. Sa `animation` mode, ginagawa ng character ang driving motion; sa `replacement` mode, pinapalitan nito ang subject habang pinananatili ang eksena. Ang resolution ay 512p o 704p, na pinipili ang orientation mula sa larawan. Maaaring gumamit ang `driving_type` ng direct end-to-end driving o tahasang pose 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/fil/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 |  |  | Prompt na tumutukoy sa gustong output video. |
| `image_url` | `image` | string (image URL) | yes |  |  | URL ng reference larawan ng character na nagbibigay ng character na ia-animate o ipapalit sa subject; tinutukoy ng driving video ang animation o pagpapalit. |
| `video_url` | `video` | string (video URL) | yes |  |  | Magbigay ng motion-driving video sa pamamagitan ng URL, na nagtatampok ng isang tao, ilang tao, o hayop. |
| `mode` |  | enum (string) | no | `animation` | `animation`, `replacement` | Piliin kung paano gagamitin ang reference character: pinananatili ng `replacement` ang orihinal na eksena ngunit pinapalitan ang character ng driving subject; inilalapat ng `animation` ang driving motion sa character. |
| `driving_type` |  | enum (string) | no | `end_to_end` | `end_to_end`, `pose` | Direktang nagmumula ang animation motion sa driving video na minask ng SAM3 gamit ang `end_to_end`, ang default at inirerekomendang opsyon para sa pinakamataas na robustness. Bilang alternatibo, ginagamit ng `pose` ang NLF/DWPose upang mag-render ng tahasang skeleton mula sa video, na nagbibigay ng higit na kontrol sa mahihirap na input. |
| `subject_type` |  | enum (string) | no | `human` | `human`, `animal` | Pagpili ng subject ng driving video, kung saan kino-configure ng `animal` ang detection prompt ng SAM3 para sa mga subject na hindi `human`. |
| `resolution` |  | enum (string) | no | `512p` | `512p`, `704p` | Output resolution na awtomatikong tinutukoy batay sa aspect ratio ng reference larawan. Sa landscape, ang 512p ay nagiging 896x512 at ang 704p ay 1280x704; sa portrait, ginagamit ang 512x896 at 704x1280 ayon sa pagkakasunod. |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Bilang ng diffusion sampling step. Pinapaganda ng pagtaas nito ang kalidad ngunit pinatatagal ang pagproseso. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Lakas ng classifier-free guidance, na nagbabalanse sa pagsunod sa prompt at creativity. |
| `shift` |  | number | no | `3` | 1 – 10 | Noise-schedule shift para sa flow matching, na may inirerekomendang setting na 3.0 kapag gumagamit ng 512p. |
| `seed` |  | integer \| null | no |  |  | Seed ng pagbuo na kasama sa response, ibinigay man nang tahasan o random na pinili dahil iniwang walang laman ang input. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Maaaring luwagan ang screening sa pamamagitan ng pagtatakda ng false, kung awtorisado ang tumatawag. |

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 file na ginawa sa pagbuo. |
| `seed` | integer | Seed na ginagamit para sa pagbuo ng video. |
| `preprocessing_video` | object {url, content_type, file_name, file_size} \| null | Debug video na naglalaman ng Stage-A pose-conditioning input na ibinigay sa diffusion modelo, available lamang kapag `output_preprocessing=true`. Nakadepende ang laman nito sa `driving_type`: gumagamit ang `end_to_end` ng driving footage na minask ng SAM3, habang gumagamit ang `driving_type=pose` ng skeleton na ni-render ng NLF/DWPose. |
| `preprocessing_mask_video` | object {url, content_type, file_name, file_size} \| null | Stage-A driving mask video para sa debugging, available lamang kapag `output_preprocessing=true`. |

## 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