# Scail 2 API

> একটি ড্রাইভিং ভিডিওর গতি দিয়ে রেফারেন্স চরিত্রের ছবিকে অ্যানিমেট করে, অথবা মূল দৃশ্যে সেটি প্রতিস্থাপন করে

একটি রেফারেন্স চরিত্রের `image_url` এবং একজন মানুষ, একাধিক মানুষ বা কোনো প্রাণীর গতিবিধি দেখানো একটি `video_url` নেয়। `animation` মোডে চরিত্রটি ভিডিওর গতিবিধি অনুসরণ করে; `replacement` মোডে দৃশ্য অক্ষুণ্ণ রেখে মূল মানুষ বা প্রাণীর জায়গায় চরিত্রটিকে বসায়। রেজোলিউশন 512p বা 704p, আর ছবির ভিত্তিতে ওরিয়েন্টেশন নির্ধারিত হয়। `driving_type` সরাসরি এন্ড-টু-এন্ড গতিবিধি অনুসরণ অথবা সুস্পষ্ট পোজ স্কেলেটন ব্যবহার করতে পারে।

- 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/bn/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 |  |  | পছন্দসই আউটপুট ভিডিও নির্দিষ্ট করা প্রম্পট। |
| `image_url` | `image` | string (image URL) | yes |  |  | animate বা subject-এর বিকল্প হিসেবে ব্যবহারের character-সহ reference character ছবি URL; driving ভিডিও animation বা replacement নির্ধারণ করে। |
| `video_url` | `video` | string (video URL) | yes |  |  | URL-এর মাধ্যমে motion-driving ভিডিও দিন, যাতে একজন মানুষ, একাধিক মানুষ বা একটি প্রাণী থাকতে পারে। |
| `mode` |  | enum (string) | no | `animation` | `animation`, `replacement` | reference character কীভাবে ব্যবহার হবে তা নির্বাচন করুন: `replacement` মূল scene বজায় রেখে driving subject-এর বদলে character বসায়; `animation` driving motion character-এর ওপর প্রয়োগ করে। |
| `driving_type` |  | enum (string) | no | `end_to_end` | `end_to_end`, `pose` | Animation motion সরাসরি `end_to_end`-সহ SAM3 দিয়ে mask করা driving ভিডিও থেকে আসে, যা সর্বোচ্চ robustness-এর জন্য ডিফল্ট ও সুপারিশকৃত পছন্দ। বিকল্পভাবে, `pose` NLF/DWPose ব্যবহার করে ওই ভিডিও থেকে explicit skeleton render করে, যা challenging ইনপুট-এ বেশি নিয়ন্ত্রণ দেয়। |
| `subject_type` |  | enum (string) | no | `human` | `human`, `animal` | Driving-ভিডিও subject selection, যেখানে `animal` non-`human` subject-এর জন্য SAM3-এর detection প্রম্পট কনফিগার করে। |
| `resolution` |  | enum (string) | no | `512p` | `512p`, `704p` | Reference ছবির aspect ratio অনুযায়ী orientation স্বয়ংক্রিয়ভাবে নির্ধারিত আউটপুট রেজোলিউশন। Landscape-এ 512p হলো 896x512 এবং 704p হলো 1280x704; portrait-এ যথাক্রমে 512x896 এবং 704x1280 ব্যবহার করা হয়। |
| `num_inference_steps` |  | integer | no | `40` | 2 – 50 | Diffusion sampling step-এর সংখ্যা। এটি বাড়ালে quality উন্নত হয়, তবে বেশি সময় লাগে। |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | ক্লাসিফায়ার-মুক্ত গাইডেন্সের শক্তি, যা প্রম্পট অনুসরণ এবং সৃজনশীলতার মধ্যে ভারসাম্য বজায় রাখে। |
| `shift` |  | number | no | `3` | 1 – 10 | Flow matching-এর noise-schedule shift; 512p ব্যবহার করলে 3.0 সেটিং সুপারিশ করা হয়। |
| `seed` |  | integer \| null | no |  |  | রেসপন্সে অন্তর্ভুক্ত জেনারেশন seed, যা স্পষ্টভাবে দেওয়া হতে পারে অথবা ইনপুট খালি থাকলে এলোমেলোভাবে নির্বাচন করা হতে পারে। |
| `enable_safety_checker` |  | boolean | no | `true` |  | কলকারী অনুমোদিত হলে false সেট করে স্ক্রিনিং শিথিল করা যায়। |

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} | জেনারেশনের মাধ্যমে তৈরি ভিডিও ফাইল। |
| `seed` | integer | ভিডিও জেনারেশনের জন্য ব্যবহৃত seed। |
| `preprocessing_video` | object {url, content_type, file_name, file_size} \| null | `output_preprocessing=true` থাকলেই পাওয়া যায় এমন debug ভিডিও, যাতে diffusion মডেল-এ দেওয়া Stage-A pose-conditioning ইনপুট থাকে। এর content `driving_type`-এর ওপর নির্ভর করে: `end_to_end` SAM3 দিয়ে mask করা driving footage ব্যবহার করে, আর `driving_type=pose` NLF/DWPose দিয়ে render করা skeleton ব্যবহার করে। |
| `preprocessing_mask_video` | object {url, content_type, file_name, file_size} \| null | Debugging-এর জন্য Stage-A driving mask ভিডিও, শুধু `output_preprocessing=true` থাকলেই পাওয়া যায়। |

## 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