# Ltx 2.3 Quality · Outpaint · LoRA API

> Outpainting vidéo selon le ratio avec jusqu'à 3 LoRAs personnalisées appliquées

Étend une vidéo sur une toile plus grande et nécessite une liste `loras` de jusqu'à 3 LoRAs personnalisées (3 GB chacune). Définissez `aspect_ratio` (21:9 à 9:21) et `output_resolution` (480p, 720p ou 1080p), ainsi qu'un `prompt` pour les nouvelles zones. `source_scale` va de 0.25 à 1 et `video_strength` préserve le contenu original.

- 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/fr/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 |  |  | Texte orientant la génération des régions extrapolées de la vidéo. |
| `video_url` | `video` | string (video URL) | yes |  |  | Vidéo source dont les limites spatiales seront prolongées par extrapolation. |
| `aspect_ratio` |  | enum (string) | no | `16:9` | `21:9`, `16:9`, `4:3`, `1:1`, `3:4`, `9:16`, `9:21` | Ratio d'aspect pour l'extrapolation ; par exemple, une entrée 4:3 peut être étendue en 16:9. Sélectionnez un ratio différent de celui de la source pour prolonger proprement l'image. |
| `output_resolution` |  | enum (string) | no | `720p` | `480p`, `720p`, `1080p` | Niveau de résolution de sortie, 720p équilibré par défaut. Choisissez 480p pour une génération plus rapide ou 1080p pour une toile plus grande, à condition de respecter les limites de 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` | Dimensions exactes du canevas avec l’ancien réglage, conservées pour assurer la rétrocompatibilité. Les nouvelles requêtes doivent plutôt utiliser `aspect_ratio` avec `output_resolution`. |
| `source_scale` |  | number | no | `1` | 0.25 – 1 | Échelle de la vidéo source dans le canevas cible avant l’extension ; la réduire ajoute une bordure de zoom arrière et rend les résultats moins stables. Pour une véritable extension du ratio d’aspect, par exemple de 4:3 à 16:9, le réglage recommandé de 1.0 ajuste la source à la plus grande taille possible dans le canevas. |
| `video_strength` |  | number | no | `1` | 0 – 1 | Contrôle la conservation de la vidéo originale dans le canevas étendu via le guidage vidéo IC-LoRA ; augmenter cette valeur préserve davantage la source. |
| `num_frames` |  | integer | no | `121` | 9 – 481 | Nombre d'images pour la sortie générée. |
| `frames_per_second` |  | number | no | `24` | 1 – 60 | Fréquence d'images de sortie vidéo, mesurée en images par seconde. |
| `num_inference_steps` |  | integer | no | `15` | 8 – 30 | Définissez le nombre d'étapes d'inférence à exécuter, jusqu'à 30 ; sans modification, la valeur est 15. |
| `guidance_scale` |  | number | no | `1` | 1 – 20 | Ajustez le guidage sans classifieur à l'aide de cette échelle ; son réglage par défaut vise à la fois une haute qualité et une génération rapide. |
| `generate_audio` |  | boolean | no | `true` |  | Paramètre de la piste audio du MP4 renvoyé : désactivé, il produit un fichier vidéo uniquement ; activé, il inclut 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 négatif précisant ce que la génération doit éviter. |
| `seed` |  | integer \| null | no |  |  | Seed rendant la génération reproductible. La valeur None sélectionne un seed aléatoire. |
| `enable_prompt_expansion` |  | boolean | no | `true` |  | Contrôle l’activation de l’expansion du prompt. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Contrôle si la vérification de sécurité est activée. |
| `video_quality` |  | enum (string) | no | `high` | `low`, `medium`, `high`, `maximum` | Préréglage de qualité appliqué à la vidéo de sortie. |
| `video_write_mode` |  | enum (string) | no | `balanced` | `fast`, `balanced`, `small` | Mode d’écriture de la vidéo résultante. |
| `loras` |  | array of object {path, scale, transformer} | yes |  | ≤ 3 items | Ajouts LoRA pour LTX-2.3, chacun limité à 3 GB, avec au plus 3 entrées autorisées. Le chargement a lieu uniquement après que le téléchargeur du registre, sécurisé contre les SSRF, a récupéré chaque chemin. |
| `loras[].path` |  | string | yes |  | ≤ 2048 characters | URL HTTP(S) directe vers un fichier LoRA .safetensors de 3 GB maximum. Le chargement est précédé d'une récupération par un téléchargeur sécurisé contre les SSRF. |
| `loras[].scale` |  | number | no | `1` | 0 – 2 | L'influence de la LoRA sur la vidéo générée augmente avec cette intensité dans la plage 0.0–2.0. |
| `loras[].transformer` |  | enum (string) | no | `both` | `high`, `low`, `both` | Indicateur de sélection du Transformer : 'both' convient à presque tous les utilisateurs de LTX-2.3, car le modèle ne possède qu'un seul Transformer. Cet indicateur prend en charge les futures architectures comportant plusieurs Transformers. |

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} | Vidéo produite par le modèle. |
| `seed` | integer | Seed effectivement appliqué pendant la génération. |
| `prompt` | string | Prompt de génération, y compris toute expansion appliquée avant son utilisation. |

## 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