# Ltx 2.3 Quality · Outpaint · LoRA API

> Uygulanan en fazla 3 özel LoRA ile en-boy oranına göre video dış boyama

Videoyu daha büyük bir tuvale genişletir ve her biri 3 GB olan en fazla 3 özel LoRA içeren bir `loras` listesi gerektirir. `aspect_ratio` (21:9 through 9:21) ve `output_resolution` (480p, 720p or 1080p) değerlerini, yeni alanlar için bir `prompt` ile birlikte ayarlayın. `source_scale` 0.25 to 1 arasındadır ve `video_strength` orijinal içeriği korur.

- Model id: `ltx-2.3-quality/outpaint/lora`
- Made by: Lightricks
- Category: Video to Video
- Output: video
- Price per megapixel of your output video: $0.00271 / megapixel of output video (cheapest run $0.003 (3 API credits))
- Run: `POST https://api.doitong.com/v1/run/ltx-2.3-quality/outpaint/lora`
- Quote: `POST https://api.doitong.com/v1/quote/ltx-2.3-quality/outpaint/lora`
- Docs page: https://doitong.com/tr/developers/models/ltx-2.3-quality/outpaint/lora

## Pricing

Price: **$0.00271 / megapixel of output video**. Price per megapixel of your output 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 $0.304 = 304 API credits (112 MP output video × $0.002708).

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/ltx-2.3-quality/outpaint/lora` 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 |  |  | Videonun dışa boyanan bölgelerinin üretimine yön veren metin. |
| `video_url` | `video` | string (video URL) | yes |  |  | Mekânsal sınırları dışa boyama yoluyla genişletilecek kaynak video. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16`, `9:21` | Dışa boyama en-boy oranı; örneğin 4:3 girdi 16:9'a genişletilebilir. Kareyi temiz biçimde genişletmek için kaynağınkinden farklı bir oran seçin. |
| `output_resolution` |  | enum (string) | no | `720p` | `480p`, `720p`, `1080p` | Varsayılan olarak dengeli 720p seçeneğini kullanan çıktı çözünürlük düzeyi. Daha hızlı üretim için 480p veya LTX sınırları içinde kalması koşuluyla daha büyük bir tuval için 1080p seçin. |
| `resolution` |  | object {width, height} \| enum (string) | no | `landscape_16_9` | `auto`, `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Geriye dönük uyumluluk için korunan eski ayarı kullanarak kesin tuval boyutları. Yeni isteklerde bunun yerine `aspect_ratio` ile birlikte `output_resolution` kullanılmalıdır. |
| `source_scale` |  | number | no | `1` | 0.25 – 1 | Outpainting öncesinde hedef tuval içindeki kaynak video ölçeği; azaltılması uzaklaştırma kenarlığı ekler ve sonuçları daha kararsız hale getirir. 4:3'ten 16:9'a geçiş gibi gerçek en-boy oranı genişletmeleri için önerilen 1.0 ayarı, kaynağı tuval içinde mümkün olan en büyük boyuta sığdırır. |
| `video_strength` |  | number | no | `1` | 0 – 1 | IC-LoRA video yönlendirmesiyle outpaint edilmiş tuvalde orijinal videonun korunma düzeyini kontrol eder; değerin artırılması kaynağı daha yakından korur. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Üretilen çıktının kare sayısı. |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | Saniyedeki kare sayısıyla ölçülen çıktı video kare hızı. |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | Çalıştırılacak çıkarım adımı sayısını en fazla 30 olacak şekilde ayarlayın; değiştirilmediğinde 15 kullanılır. |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | Bu ölçeği kullanarak classifier-free guidance'ı ayarlayın; varsayılan ayarı yüksek kaliteyi ve hızlı üretimi hedefler. |
| `generate_audio` |  | boolean | no | `true` |  | Döndürülen MP4 için ses parçası geçişi: kapalı olduğunda yalnızca video dosyası, açık olduğunda ses içeren dosya üretir. |
| `negative_prompt` |  | string | no | `color distortion, overexposure, static, blurry details, subtitles, style, artwork, painting, frame, still, dim overall tone, worst quality, low quality, JPEG compression artifacts, ugly, mutilated, extra fingers, poorly drawn hands, poorly drawn face, deformed, disfigured, malformed limbs, fused fingers, motionless frame, cluttered background, three legs, crowded background, walking backwards` |  | Üretimin kaçınması gerekenleri belirten negatif istem. |
| `seed` |  | integer \| null | no |  |  | Üretimi tekrarlanabilir kılan seed. None olarak ayarlanması seed'in rastgele seçilmesini sağlar. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | İstem genişletmenin etkin olup olmadığını denetler. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Güvenlik denetiminin etkin olup olmadığını denetler. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Çıktı videoya uygulanan kalite ön ayarı. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Sonuç videosunun yazma modu. |
| `loras` |  | array of object {path, scale, transformer} | yes |  | ≤ 3 items | LTX-2.3 için her biri 3 GB ile sınırlı ve en fazla 3 öğeye izin verilen LoRA eklemeleri. Yükleme yalnızca registry'nin SSRF güvenli indiricisi her yolu aldıktan sonra gerçekleşir. |
| `loras[].path` |  | string | yes |  | ≤ 2048 characters | 3 GB'dan büyük olmayan bir LoRA .safetensors dosyası için doğrudan HTTP(S) URL'si. Yüklemeden önce SSRF güvenli indiriciyle alma işlemi yapılır. |
| `loras[].scale` |  | number | no | `1` | 0 – 2 | Bu güç 0.0–2.0 aralığında arttıkça LoRA'nın üretilen video üzerindeki etkisi artar. |
| `loras[].transformer` |  | enum (string) | no | `both` | `high`, `low`, `both` | Transformer seçim işareti: 'both', yalnızca bir transformer'a sahip model nedeniyle LTX-2.3 kullanan hemen herkes için uygundur. İşaret, birden çok transformer içeren gelecekteki mimarileri desteklemek için vardır. |

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
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "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"
}
```

A fuller example:

```json
{
  "loras": [
    {
      "path": "https://example.com/your-file.safetensors"
    }
  ],
  "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"
}
```

## 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/ltx-2.3-quality/outpaint/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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"
  }'

# 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/ltx-2.3-quality/outpaint/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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"
  }),
});
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 = {
    "loras": [
        {
            "path": "https://example.com/your-file.safetensors",
        },
    ],
    "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",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx-2.3-quality/outpaint/lora", 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": "ltx-2.3-quality/outpaint/lora",
      "input": {
        "loras": [
          {
            "path": "https://example.com/your-file.safetensors"
          }
        ],
        "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"
      },
      "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": "ltx-2.3-quality/outpaint/lora",
  "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": 304,
    "usd": "0.304",
    "charged": 304,
    "refunded": 0
  },
  "input": {
    "loras": [
      {
        "path": "https://example.com/your-file.safetensors"
      }
    ],
    "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"
  },
  "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,
    "prompt": "string"
  },
  "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} | Model tarafından üretilen video. |
| `seed` | integer | Üretim sırasında uygulanan gerçek seed. |
| `prompt` | string | Kullanımdan önce uygulanan tüm genişletmeleri içeren üretim istemi. |

## Related models

- [Ltx 2.3 Quality · Text to Video](https://doitong.com/developers/models/ltx-2.3-quality/text-to-video.md) (`ltx-2.3-quality/text-to-video`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Text to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-quality/text-to-video/lora.md) (`ltx-2.3-quality/text-to-video/lora`): $0.00271 / megapixel of output video
- [Ltx 2.3 Quality · Image to Video](https://doitong.com/developers/models/ltx-2.3-quality/image-to-video.md) (`ltx-2.3-quality/image-to-video`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Image to Video · LoRA](https://doitong.com/developers/models/ltx-2.3-quality/image-to-video/lora.md) (`ltx-2.3-quality/image-to-video/lora`): $0.00271 / megapixel of output video
- [Ltx 2.3 Quality · Ingredient](https://doitong.com/developers/models/ltx-2.3-quality/ingredient.md) (`ltx-2.3-quality/ingredient`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Clean Plate](https://doitong.com/developers/models/ltx-2.3-quality/clean-plate.md) (`ltx-2.3-quality/clean-plate`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Colorization](https://doitong.com/developers/models/ltx-2.3-quality/colorization.md) (`ltx-2.3-quality/colorization`): $0.00241 / megapixel of output video
- [Ltx 2.3 Quality · Cross Eyed](https://doitong.com/developers/models/ltx-2.3-quality/cross-eyed.md) (`ltx-2.3-quality/cross-eyed`): $0.00241 / megapixel of output video

## Links

- HTML page: https://doitong.com/developers/models/ltx-2.3-quality/outpaint/lora
- 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=ltx-2.3-quality/outpaint/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/ltx-2.3-quality/outpaint/lora