# Luma Ray 3.2 Reframe API

> 최대 10초의 기존 비디오를 새 화면 비율로 재구성하고 프롬프트로 추가 캔버스를 아웃페인팅합니다

`video_url` (10초 이하), 대상 `aspect_ratio` 및 새로 노출된 영역에 그릴 내용을 설명하는 `prompt`를 받습니다. 화면 비율은 3:4~21:9이고 `resolution`은 540p, 720p 또는 1080p입니다. `duration`은 기본적으로 소스 길이를 따르며 5s 또는 10s로 설정할 수 있습니다. `source_position`은 새 캔버스에서 원본 영상의 위치를 지정합니다.

- Model id: `luma/agent/ray/v3.2/reframe`
- Made by: Luma AI
- Category: Video to Video
- Output: video
- Price per second of your input video: from $0.06 / second of input video (cheapest run $0.06 (60 API credits))
- Run: `POST https://api.doitong.com/v1/run/luma/agent/ray/v3.2/reframe`
- Quote: `POST https://api.doitong.com/v1/quote/luma/agent/ray/v3.2/reframe`
- Docs page: https://doitong.com/ko/developers/models/luma/agent/ray/v3.2/reframe

## Pricing

Price: **from $0.06 / second of input video** (the lowest tier; the quote prices your exact input). 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.

Price by tier:

- 540p: $0.06 / second of input video
- 720p: $0.12 / second of input video
- 1080p: $0.36 / second of input video

The full example input below costs $0.60 = 600 API credits (10 s input video × $0.06 (540p)).

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/luma/agent/ray/v3.2/reframe` 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 |  | 1 – 6000 characters | 프레임 재구성 중 대상 가로세로 비율 변경으로 드러난 추가 캔버스를 채우기 위한 콘텐츠 지침입니다. |
| `video_url` | `video` | string (video URL) | yes |  | ≥ 1 characters | 10초 이하의 동영상으로 제한되는 프레임 재구성 소스 URL입니다. |
| `aspect_ratio` |  | enum (string) | yes |  | `3:4`, `4:3`, `1:1`, `9:16`, `16:9`, `21:9` | 프레임을 다시 구성한 출력에 사용할 가로세로 비율입니다. |
| `resolution` |  | enum (string) | no | `540p` | `540p`, `720p`, `1080p` | 프레임 재구성 후 출력 해상도입니다. |
| `duration` |  | enum (string) \| null | no |  | `5s`, `10s` | 프레임 재구성 출력 길이 재정의입니다. 5s 또는 10s를 선택하거나 생략하여 소스 동영상 길이를 유지합니다. |
| `source_position` |  | object {x_norm, y_norm, w_norm, h_norm} \| null | no |  |  | 출력 캔버스 내 소스 동영상의 선택적 배치입니다. 정규화된 사각형으로 지정합니다. |
| `source_position.x_norm` |  | number | yes |  | -2 – 2 | 가로 소스 사각형 좌표입니다. 왼쪽 가장자리 위치를 출력 너비로 나누어 계산합니다. |
| `source_position.y_norm` |  | number | yes |  | -2 – 2 | 세로 소스 사각형 좌표입니다. 위쪽 가장자리 위치를 출력 높이로 나누어 계산합니다. |
| `source_position.w_norm` |  | number | yes |  | ≤ 2, > 0 | 소스 사각형의 너비입니다. 출력 너비를 기준으로 상대적으로 표현합니다. |
| `source_position.h_norm` |  | number | yes |  | ≤ 2, > 0 | 소스 사각형의 높이입니다. 출력 높이를 기준으로 상대적으로 표현합니다. |
| `enable_safety_checker` |  | boolean | no | `true` |  | 호출자에게 권한이 있으면 false로 설정해 검사를 완화할 수 있습니다. |

File parameters (`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",
  "video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
  "aspect_ratio": "3:4"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
  "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
  "aspect_ratio": "3:4"
}
```

## 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/luma/agent/ray/v3.2/reframe?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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "aspect_ratio": "3:4"
  }'

# 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/luma/agent/ray/v3.2/reframe?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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "aspect_ratio": "3:4"
  }),
});
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",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "aspect_ratio": "3:4",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/luma/agent/ray/v3.2/reframe", 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": "luma/agent/ray/v3.2/reframe",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
        "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
        "aspect_ratio": "3:4"
      },
      "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": "luma/agent/ray/v3.2/reframe",
  "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": 600,
    "usd": "0.60",
    "charged": 600,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
    "video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
    "aspect_ratio": "3:4"
  },
  "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
    },
    "exr_file": {
      "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} | 모델이 생성한 동영상입니다. |
| `exr_file` | object {url, content_type, file_name, file_size} \| null | Luma가 내보내는 형식의 EXR 사이드카입니다. 하나의 EXR 파일 또는 ZIP 아카이브일 수 있으며 exr_export가 true일 때 생성됩니다. |

## Related models

- [Luma Ray 3.2 Text to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/text-to-video.md) (`luma/agent/ray/v3.2/text-to-video`): from $0.10 / second
- [Luma Ray 3.2 Image to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/image-to-video.md) (`luma/agent/ray/v3.2/image-to-video`): from $0.03 / second
- [Luma Ray 3.2 Video to Video](https://doitong.com/developers/models/luma/agent/ray/v3.2/video-to-video.md) (`luma/agent/ray/v3.2/video-to-video`): from $0.144 / second
- [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
- [Auto-Captioner](https://doitong.com/developers/models/auto-caption.md) (`auto-caption`): $0.10 / video
- [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

## Links

- HTML page: https://doitong.com/developers/models/luma/agent/ray/v3.2/reframe
- 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=luma/agent/ray/v3.2/reframe
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/luma/agent/ray/v3.2/reframe