Outpaint high-quality video using LTX-2.3 with Lora

fal-ai/ltx-2.3-quality/outpaint/lora

Outpaint high-quality video using LTX-2.3 with Lora

Inference

Commercial use

Schema

LLMs

Playground API Examples

About

Outpaint with up to 3 user-supplied LoRAs.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/ltx-2.3-quality/outpaint/lora", {
  input: {
    prompt: "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
    video_url: "",
    loras: [{
      path: "https://example.com/path/to/lora.safetensors",
      scale: 1,
      transformer: "both"
    }]
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/ltx-2.3-quality/outpaint/lora", {
  input: {
    prompt: "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
    video_url: "",
    loras: [{
      path: "https://example.com/path/to/lora.safetensors",
      scale: 1,
      transformer: "both"
    }]
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/ltx-2.3-quality/outpaint/lora", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/ltx-2.3-quality/outpaint/lora", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to guide the outpainted video generation.

video_url string* required

The source video to spatially outpaint.

aspect_ratio AspectRatioEnum

Target aspect ratio for the outpainted video. Choose a different ratio than the input video to extend the frame cleanly, e.g. use 16:9 for a 4:3 source. Default value: "16:9"

Possible enum values: 21:9, 16:9, 4:3, 1:1, 3:4, 9:16, 9:21

output_resolution OutputResolutionEnum

Output resolution tier. 480p is faster, 720p is the default balance, and 1080p gives a larger canvas when it fits LTX limits. Default value: "720p"

Possible enum values: 480p, 720p, 1080p

resolution ImageSize | Enum

Legacy exact target canvas size. For new requests, prefer aspect_ratio with output_resolution; this field remains supported for backwards compatibility. Default value: landscape_16_9

Possible enum values: auto, square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}

source_scale float

Scale of the source video inside the target canvas before outpainting. 1.0 uses the largest source size that fits the target canvas, which is recommended for true aspect-ratio outpainting such as 4:3 to 16:9. Lower values create a zoom-out border around the source and are less stable. Default value: 1

video_strength float

Strength of the IC-LoRA video guide for the original content. Higher values preserve the source video more strongly inside the outpainted canvas. Default value: 1

num_frames integer

The number of frames to generate. Default value: 121

frames_per_second float

Frames per second of the generated video. Default value: 24

num_inference_steps integer

Number of inference steps. Defaults to 15 and can be increased up to 30. Default value: 15

guidance_scale float

Classifier-free guidance scale. The default is tuned for fast, high-quality generation. Default value: 1

generate_audio boolean

Whether to include audio in the returned video. When disabled, the final MP4 is returned without an audio track. Default value: true

negative_prompt string

The negative prompt to steer generation away from. Default value: "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"

seed integer

Random seed for reproducibility. If None, a random seed is chosen.

enable_prompt_expansion boolean

Whether to enable prompt expansion. Default value: true

enable_safety_checker boolean

Whether to enable the safety checker. Default value: true

video_quality VideoQualityEnum

The quality preset of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

sync_mode boolean

If True, the media is returned as a data URI inline in the response. Useful for short-lived requests and tests.

loras list<LoRAInput>* required

Up to 3 LoRAs to apply on top of LTX-2.3. Each path is downloaded through the registry SSRF-safe downloader before it is loaded. Max size: 3 GB per LoRA.

{
  "prompt": "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
  "video_url": "",
  "aspect_ratio": "16:9",
  "output_resolution": "720p",
  "resolution": "landscape_16_9",
  "source_scale": 1,
  "video_strength": 1,
  "num_frames": 121,
  "frames_per_second": 24,
  "num_inference_steps": 15,
  "guidance_scale": 1,
  "generate_audio": true,
  "negative_prompt": "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",
  "enable_prompt_expansion": true,
  "enable_safety_checker": true,
  "video_quality": "high",
  "video_write_mode": "balanced",
  "loras": [
    {
      "path": "https://example.com/path/to/lora.safetensors",
      "scale": 1,
      "transformer": "both"
    }
  ]
}

Output#

video File* required

The generated video.

seed integer* required

The seed actually used for generation.

prompt string* required

The prompt used for generation (after any expansion).

{
  "video": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "prompt": ""
}

Other types#

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

LoRAInput#

path string* required

Direct HTTP(S) download URL of the LoRA file (.safetensors). The file is downloaded through an SSRF-safe downloader before it is loaded. Max size: 3 GB.

scale float

Strength of the LoRA application (0.0 to 2.0). Higher values = stronger effect on the generated video. Default value: 1

transformer TransformerEnum

Forward-compatibility flag for multi-transformer architectures. LTX-2.3 has a single transformer, so 'both' is the right choice for almost all users. Default value: "both"

Possible enum values: high, low, both

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

Related Models

Loading API documentation…

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Outpaint with up to 3 user-supplied LoRAs.

1. Calling the API#

Install the client#

The client provides a convenient way to interact with the model API.

npm install --save @fal-ai/client

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.

Setup your API Key#

Set FAL_KEY as an environment variable in your runtime.

export FAL_KEY="YOUR_API_KEY"

Submit a request#

The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.

import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/ltx-2.3-quality/outpaint/lora", {
  input: {
    prompt: "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
    video_url: "",
    loras: [{
      path: "https://example.com/path/to/lora.safetensors",
      scale: 1,
      transformer: "both"
    }]
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);

2. Authentication#

The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.

API Key#

In an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

The client API provides a convenient way to submit requests to the model.

import { fal } from "@fal-ai/client";

const { request_id } = await fal.queue.submit("fal-ai/ltx-2.3-quality/outpaint/lora", {
  input: {
    prompt: "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
    video_url: "",
    loras: [{
      path: "https://example.com/path/to/lora.safetensors",
      scale: 1,
      transformer: "both"
    }]
  },
  webhookUrl: "https://optional.webhook.url/for/results",
});

Fetch request status#

You can fetch the status of a request to check if it is completed or still in progress.

import { fal } from "@fal-ai/client";

const status = await fal.queue.status("fal-ai/ltx-2.3-quality/outpaint/lora", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
  logs: true,
});

Get the result#

Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.

import { fal } from "@fal-ai/client";

const result = await fal.queue.result("fal-ai/ltx-2.3-quality/outpaint/lora", {
  requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);

4. Files#

Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.

Data URI (base64)#

Hosted files (URL)#

You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.

Uploading files#

We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.

import { fal } from "@fal-ai/client";

const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);

Auto uploads

The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to guide the outpainted video generation.

video_url string* required

The source video to spatially outpaint.

aspect_ratio AspectRatioEnum

Target aspect ratio for the outpainted video. Choose a different ratio than the input video to extend the frame cleanly, e.g. use 16:9 for a 4:3 source. Default value: "16:9"

Possible enum values: 21:9, 16:9, 4:3, 1:1, 3:4, 9:16, 9:21

output_resolution OutputResolutionEnum

Output resolution tier. 480p is faster, 720p is the default balance, and 1080p gives a larger canvas when it fits LTX limits. Default value: "720p"

Possible enum values: 480p, 720p, 1080p

resolution ImageSize | Enum

Legacy exact target canvas size. For new requests, prefer aspect_ratio with output_resolution; this field remains supported for backwards compatibility. Default value: landscape_16_9

Possible enum values: auto, square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}

source_scale float

video_strength float

Strength of the IC-LoRA video guide for the original content. Higher values preserve the source video more strongly inside the outpainted canvas. Default value: 1

num_frames integer

The number of frames to generate. Default value: 121

frames_per_second float

Frames per second of the generated video. Default value: 24

num_inference_steps integer

Number of inference steps. Defaults to 15 and can be increased up to 30. Default value: 15

guidance_scale float

Classifier-free guidance scale. The default is tuned for fast, high-quality generation. Default value: 1

generate_audio boolean

Whether to include audio in the returned video. When disabled, the final MP4 is returned without an audio track. Default value: true

negative_prompt string

seed integer

Random seed for reproducibility. If None, a random seed is chosen.

enable_prompt_expansion boolean

Whether to enable prompt expansion. Default value: true

enable_safety_checker boolean

Whether to enable the safety checker. Default value: true

video_quality VideoQualityEnum

The quality preset of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

sync_mode boolean

If True, the media is returned as a data URI inline in the response. Useful for short-lived requests and tests.

loras list<LoRAInput>* required

Up to 3 LoRAs to apply on top of LTX-2.3. Each path is downloaded through the registry SSRF-safe downloader before it is loaded. Max size: 3 GB per LoRA.

{
  "prompt": "A cinematic wide shot of the same scene, extending the environment naturally beyond the original frame.",
  "video_url": "",
  "aspect_ratio": "16:9",
  "output_resolution": "720p",
  "resolution": "landscape_16_9",
  "source_scale": 1,
  "video_strength": 1,
  "num_frames": 121,
  "frames_per_second": 24,
  "num_inference_steps": 15,
  "guidance_scale": 1,
  "generate_audio": true,
  "negative_prompt": "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",
  "enable_prompt_expansion": true,
  "enable_safety_checker": true,
  "video_quality": "high",
  "video_write_mode": "balanced",
  "loras": [
    {
      "path": "https://example.com/path/to/lora.safetensors",
      "scale": 1,
      "transformer": "both"
    }
  ]
}

Output#

video File* required

The generated video.

seed integer* required

The seed actually used for generation.

prompt string* required

The prompt used for generation (after any expansion).

{
  "video": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019
  },
  "prompt": ""
}

Other types#

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

LoRAInput#

path string* required

Direct HTTP(S) download URL of the LoRA file (.safetensors). The file is downloaded through an SSRF-safe downloader before it is loaded. Max size: 3 GB.

scale float

Strength of the LoRA application (0.0 to 2.0). Higher values = stronger effect on the generated video. Default value: 1

transformer TransformerEnum

Forward-compatibility flag for multi-transformer architectures. LTX-2.3 has a single transformer, so 'both' is the right choice for almost all users. Default value: "both"

Possible enum values: high, low, both

File#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

Related Models

Ltx 2.3 Quality Video to Video API Docs | fal

fal-ai/ltx-2.3-quality/outpaint/lora

fal-ai/ltx-2.3-quality/outpaint/lora

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

ImageSize#

LoRAInput#

File#

Related Models

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

ImageSize#

LoRAInput#

File#

Related Models