# Ltx 2.3 Quality · Outpaint · LoRA API

> Video-Outpainting mat Aspektverhältnis an bis zu 3 applizéierte personaliséierte LoRAs

Outpaint e Video op e méi grousse Canvas a verlaangt eng `loras`-Lëscht mat bis zu 3 personaliséierte LoRAs (3 GB pro Stéck). Setzt `aspect_ratio` (21:9 through 9:21) an `output_resolution` (480p, 720p or 1080p), plus e `prompt` fir déi nei Beräicher. `source_scale` geet vun 0.25 bis 1, an `video_strength` behält den originellen Inhalt.

- 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/lb/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 |  |  | Text, deen d'Generatioun vun den Outpainting-Beräicher vum Video steiert. |
| `video_url` | `video` | string (video URL) | yes |  |  | Quellvideo, deem seng raimlech Grenze mam Outpainting verlängert ginn. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16`, `9:21` | Outpainting-Bildformat; zum Beispill kann en 4:3-Input op 16:9 erweidert ginn. Wielt e Verhältnis, dat vum Quellverhältnis ofwäicht, fir de Frame propper ze verlängeren. |
| `output_resolution` |  | enum (string) | no | `720p` | `480p`, `720p`, `1080p` | Opléisungsklass vum Output, Standard ass déi equilibréiert 720p-Optioun. Wielt 480p fir méi séier Generatioun oder 1080p fir e méi grousse Canvas, wann et an d'LTX-Limite passt. |
| `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` | Exakt Canvas-Dimensioune mat der legacy-Astellung, déi fir Réckkompatibilitéit bäibehale gëtt. Nei Ufroe sollten amplaz `aspect_ratio` zesumme mat `output_resolution` benotzen. |
| `source_scale` |  | number | no | `1` | 0.25 – 1 | Skaléierung vum Quellvideo bannent dem Zil-Canvas virum Outpainting; eng Reduktioun féiert zu engem Zoom-out-Rand a mécht d'Resultater manner stabil. Fir eng richteg Erweiderung vum Aspektverhältnis, zum Beispill vun 4:3 op 16:9, passt déi recommandéiert Astellung 1.0 d'Quell mat der gréisstméiglecher Gréisst an de Canvas un. |
| `video_strength` |  | number | no | `1` | 0 – 1 | Steiert, wéi vill vum originale Video am ausgefëllte Canvas iwwer d'IC-LoRA-Video-Guidance erhale bleift; eng Erhéijung vun der Stäerkt erhält d'Quell méi genee. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Frame-Zuel vum generéierten Output. |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | Output-Video-Frame-Rate, gemooss a Frames pro Sekonn. |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | Setzt d'Zuel vun den Inference-Schrëtt op bis zu 30; wann onverännert, ginn 15 benotzt. |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | Passt classifier-free guidance mat dëser Skala un; de Standard ass op héich Qualitéit a séier Generatioun ofgestëmmt. |
| `generate_audio` |  | boolean | no | `true` |  | Audio-Spur-Toggle fir den zeréckginnene MP4: ausgeschalt produzéiert eng Video-nëmmen-Datei, ageschalt enthält Audio. |
| `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` |  | Negativen Prompt, deen ugëtt, wat d'Generatioun vermeide soll. |
| `seed` |  | integer \| null | no |  |  | Seed, deen d'Generatioun reproduzéierbar mécht. Wann et op None gesat gëtt, gëtt e Seed zoufälleg gewielt. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Steiert, ob d'Prompt-Erweiderung aktivéiert ass. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Steiert, ob d'Sécherheetskontroll aktivéiert ass. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Qualitéitsvirstellung, déi op den Output-Video applizéiert gëtt. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Schreifmodus vum resultéierende Video. |
| `loras` |  | array of object {path, scale, transformer} | yes |  | ≤ 3 items | LoRA-Zousätz fir LTX-2.3, all op 3 GB limitéiert, mat maximal 3 Entréeën. D'Lueden geschitt eréischt, nodeems de SSRF-sécheren Downloader vum Registry all Pad ofgeruff huet. |
| `loras[].path` |  | string | yes |  | ≤ 2048 characters | Direkt HTTP(S)-URL fir eng LoRA-.safetensors-Datei vu maximal 3 GB. Virum Lueden gëtt se mat engem SSRF-sécheren Downloader ofgeruff. |
| `loras[].scale` |  | number | no | `1` | 0 – 2 | Den Afloss vun der LoRA op de generéierte Video klëmmt, wann dës Stäerkt am Beräich 0.0–2.0 klëmmt. |
| `loras[].transformer` |  | enum (string) | no | `both` | `high`, `low`, `both` | Transformer-Auswiel-Flag: 'both' passt fir bal all Benotzer vu LTX-2.3, well d'Modell nëmmen een Transformer huet. De Flag ënnerstëtzt zukünfteg Architekture mat méi Transformeren. |

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} | Video, dee vum Modell produzéiert gëtt. |
| `seed` | integer | Tatsächlech Seed, deen wärend der Generatioun applizéiert gëtt. |
| `prompt` | string | Generatiouns-Prompt, inklusiv all Erweiderung, déi virun der Benotzung applizéiert gouf. |

## 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