# Ltx 2.3 Quality · Outpaint · LoRA API

> Outpainting video con rapporto d'aspetto e fino a 3 LoRA personalizzate applicate

Esegue l'outpainting di un video su una tela più grande e richiede un elenco `loras` contenente fino a 3 LoRA personalizzate (3 GB ciascuna). Imposta `aspect_ratio` (21:9 through 9:21) e `output_resolution` (480p, 720p or 1080p), oltre a un `prompt` per le nuove aree. `source_scale` va da 0.25 a 1 e `video_strength` mantiene intatto il contenuto originale.

- 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/it/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 |  |  | Testo che dirige la generazione delle regioni del video ottenute tramite outpainting. |
| `video_url` | `video` | string (video URL) | yes |  |  | Video sorgente i cui confini spaziali verranno estesi tramite outpainting. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16`, `9:21` | Rapporto d'aspetto dell'outpainting; ad esempio, un input 4:3 può essere espanso a 16:9. Seleziona un rapporto diverso da quello della sorgente per estendere il fotogramma in modo uniforme. |
| `output_resolution` |  | enum (string) | no | `720p` | `480p`, `720p`, `1080p` | Livello di risoluzione dell'output, predefinito sull'opzione bilanciata 720p. Scegli 480p per una generazione più rapida o 1080p per un canvas più grande, purché rientri nei limiti di LTX. |
| `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` | Dimensioni esatte del canvas usando l'impostazione legacy, mantenuta per la compatibilità con le versioni precedenti. Le nuove richieste devono invece usare `aspect_ratio` insieme a `output_resolution`. |
| `source_scale` |  | number | no | `1` | 0.25 – 1 | Scala del video sorgente all'interno del canvas di destinazione prima dell'outpainting; ridurla introduce un bordo dovuto allo zoom indietro e rende i risultati meno stabili. Per una vera espansione del rapporto d'aspetto, ad esempio da 4:3 a 16:9, l'impostazione consigliata 1.0 adatta il sorgente alle dimensioni massime possibili del canvas. |
| `video_strength` |  | number | no | `1` | 0 – 1 | Controlla il mantenimento del video originale nel canvas sottoposto a outpainting tramite la guida video IC-LoRA; aumentandone l'intensità si preserva più fedelmente il sorgente. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Numero di fotogrammi dell'output generato. |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | Fotogramma rate del video di output, misurato in fotogrammi al secondo. |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | Imposta quanti passaggi di inferenza eseguire, fino a 30; se lasciato invariato, usa 15. |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | Regola la guidance classifier-free usando questa scala; la sua regolazione predefinita mira a un'elevata qualità e a una generazione rapida. |
| `generate_audio` |  | boolean | no | `true` |  | Interruttore della traccia audio per l'MP4 restituito: disattivato produce un file solo video, mentre attivato include l'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` |  | Prompt negativo che specifica cosa la generazione deve evitare. |
| `seed` |  | integer \| null | no |  |  | Seed che rende riproducibile la generazione. Impostarlo su None seleziona casualmente un seed. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Controlla se l'espansione del prompt è abilitata. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Controlla se il controllo di sicurezza è abilitato. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Preset di qualità applicato al video di output. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Modalità di scrittura del video risultante. |
| `loras` |  | array of object {path, scale, transformer} | yes |  | ≤ 3 items | Aggiunte LoRA per LTX-2.3, ciascuna limitata a 3 GB, con un massimo di 3 elementi consentiti. Il caricamento avviene solo dopo che il downloader del registro, sicuro contro SSRF, ha recuperato ogni percorso. |
| `loras[].path` |  | string | yes |  | ≤ 2048 characters | URL HTTP(S) diretto a un file LoRA .safetensors non più grande di 3 GB. Il caricamento è preceduto dal recupero tramite un downloader sicuro contro SSRF. |
| `loras[].scale` |  | number | no | `1` | 0 – 2 | L'influenza della LoRA sul video generato aumenta all'aumentare di questa intensità nell'intervallo 0.0–2.0. |
| `loras[].transformer` |  | enum (string) | no | `both` | `high`, `low`, `both` | Flag di selezione del Transformer: 'both' è adatto quasi a tutti gli utenti di LTX-2.3 perché il modello ha un solo transformer. Il flag esiste per supportare architetture future con più transformer. |

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 prodotto dal modello. |
| `seed` | integer | Seed effettivamente applicato durante la generazione. |
| `prompt` | string | Prompt di generazione, inclusa qualsiasi espansione applicata prima dell'uso. |

## 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