LTX-2 19B Distilled Text to Video API Docs | fal

Generate video with audio from text using LTX-2 Distilled and custom LoRA

fal-ai/ltx-2-19b/distilled/text-to-video/lora

Generate video with audio from text using LTX-2 Distilled and custom LoRA

Inference

Commercial use

Schema

LLMs

Playground API

About

Generate a video from a text prompt using distilled LoRA.

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-2-19b/distilled/text-to-video/lora", {
  input: {
    prompt: "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
    loras: [{
      path: "",
      scale: 1
    }]
  },
  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-2-19b/distilled/text-to-video/lora", {
  input: {
    prompt: "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
    loras: [{
      path: "",
      scale: 1
    }]
  },
  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-2-19b/distilled/text-to-video/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-2-19b/distilled/text-to-video/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 generate the video from.

num_frames integer

The number of frames to generate. Default value: 121

video_size ImageSize | Enum

The size of the generated video. Default value: landscape_4_3

Possible enum values: 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
}

generate_audio boolean

Whether to generate audio for the video. Default value: true

use_multiscale boolean

Whether to use multi-scale generation. If True, the model will generate the video at a smaller scale first, then use the smaller video to guide the generation of a video at or above your requested size. This results in better coherence and details. Default value: true

fps float

The frames per second of the generated video. Default value: 25

acceleration AccelerationEnum

The acceleration level to use. Default value: "none"

Possible enum values: none, regular, high, full

camera_lora CameraLoRAEnum

The camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Default value: "none"

Possible enum values: dolly_in, dolly_out, dolly_left, dolly_right, jib_up, jib_down, static, none

camera_lora_scale float

The scale of the camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Default value: 1

negative_prompt string

The negative prompt to generate the video from. Default value: "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio,incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts."

seed integer

The seed for the random number generator.

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_output_type VideoOutputTypeEnum

The output type of the generated video. Default value: "X264 (.mp4)"

Possible enum values: X264 (.mp4), VP9 (.webm), PRORES4444 (.mov), GIF (.gif)

video_quality VideoQualityEnum

The quality 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 will be returned as a data URI and the output data won't be available in the request history.

loras list<LoRAInput>* required

The LoRAs to use for the generation.

{
  "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
  "num_frames": 121,
  "video_size": "landscape_4_3",
  "generate_audio": true,
  "use_multiscale": true,
  "fps": 25,
  "acceleration": "none",
  "camera_lora": "none",
  "camera_lora_scale": 1,
  "negative_prompt": "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio,incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts.",
  "enable_prompt_expansion": true,
  "enable_safety_checker": true,
  "video_output_type": "X264 (.mp4)",
  "video_quality": "high",
  "video_write_mode": "balanced",
  "loras": [
    {
      "path": "",
      "scale": 1
    }
  ]
}

Output#

video VideoFile* required

The generated video.

seed integer* required

The seed used for the random number generator.

prompt string* required

The prompt used for the generation.

{
  "video": {
    "url": "https://v3b.fal.media/files/b/0a8824b1/sdm0KfmenrlywesfzY1Y1_if6euPp1.mp4",
    "fps": 25,
    "duration": 6.44,
    "num_frames": 161,
    "width": 1248,
    "file_name": "sdm0KfmenrlywesfzY1Y1_if6euPp1.mp4",
    "height": 704,
    "content_type": "video/mp4"
  },
  "seed": 149063119,
  "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain."
}

Other types#

LoRAInput#

path string* required

URL, HuggingFace repo ID (owner/repo) to lora weights.

weight_name string

Name of the LoRA weight. Only used if path is a HuggingFace repository, and is only required when the repository contains multiple LoRA weights.

scale float

Scale factor for LoRA application (0.0 to 4.0). Default value: 1

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

VideoFile#

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.

width integer

The width of the video

height integer

The height of the video

fps float

The FPS of the video

duration float

The duration of the video

num_frames integer

The number of frames in the video

Related Models

Loading API documentation…

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Generate a video from a text prompt using distilled LoRA.

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-2-19b/distilled/text-to-video/lora", {
  input: {
    prompt: "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
    loras: [{
      path: "",
      scale: 1
    }]
  },
  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-2-19b/distilled/text-to-video/lora", {
  input: {
    prompt: "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
    loras: [{
      path: "",
      scale: 1
    }]
  },
  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-2-19b/distilled/text-to-video/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-2-19b/distilled/text-to-video/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 generate the video from.

num_frames integer

The number of frames to generate. Default value: 121

video_size ImageSize | Enum

The size of the generated video. Default value: landscape_4_3

Possible enum values: 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
}

generate_audio boolean

Whether to generate audio for the video. Default value: true

use_multiscale boolean

fps float

The frames per second of the generated video. Default value: 25

acceleration AccelerationEnum

The acceleration level to use. Default value: "none"

Possible enum values: none, regular, high, full

camera_lora CameraLoRAEnum

The camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Default value: "none"

Possible enum values: dolly_in, dolly_out, dolly_left, dolly_right, jib_up, jib_down, static, none

camera_lora_scale float

The scale of the camera LoRA to use. This allows you to control the camera movement of the generated video more accurately than just prompting the model to move the camera. Default value: 1

negative_prompt string

seed integer

The seed for the random number generator.

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_output_type VideoOutputTypeEnum

The output type of the generated video. Default value: "X264 (.mp4)"

Possible enum values: X264 (.mp4), VP9 (.webm), PRORES4444 (.mov), GIF (.gif)

video_quality VideoQualityEnum

The quality 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 will be returned as a data URI and the output data won't be available in the request history.

loras list<LoRAInput>* required

The LoRAs to use for the generation.

{
  "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain.",
  "num_frames": 121,
  "video_size": "landscape_4_3",
  "generate_audio": true,
  "use_multiscale": true,
  "fps": 25,
  "acceleration": "none",
  "camera_lora": "none",
  "camera_lora_scale": 1,
  "negative_prompt": "blurry, out of focus, overexposed, underexposed, low contrast, washed out colors, excessive noise, grainy texture, poor lighting, flickering, motion blur, distorted proportions, unnatural skin tones, deformed facial features, asymmetrical face, missing facial features, extra limbs, disfigured hands, wrong hand count, artifacts around text, inconsistent perspective, camera shake, incorrect depth of field, background too sharp, background clutter, distracting reflections, harsh shadows, inconsistent lighting direction, color banding, cartoonish rendering, 3D CGI look, unrealistic materials, uncanny valley effect, incorrect ethnicity, wrong gender, exaggerated expressions, wrong gaze direction, mismatched lip sync, silent or muted audio, distorted voice, robotic voice, echo, background noise, off-sync audio,incorrect dialogue, added dialogue, repetitive speech, jittery movement, awkward pauses, incorrect timing, unnatural transitions, inconsistent framing, tilted camera, flat lighting, inconsistent tone, cinematic oversaturation, stylized filters, or AI artifacts.",
  "enable_prompt_expansion": true,
  "enable_safety_checker": true,
  "video_output_type": "X264 (.mp4)",
  "video_quality": "high",
  "video_write_mode": "balanced",
  "loras": [
    {
      "path": "",
      "scale": 1
    }
  ]
}

Output#

video VideoFile* required

The generated video.

seed integer* required

The seed used for the random number generator.

prompt string* required

The prompt used for the generation.

{
  "video": {
    "url": "https://v3b.fal.media/files/b/0a8824b1/sdm0KfmenrlywesfzY1Y1_if6euPp1.mp4",
    "fps": 25,
    "duration": 6.44,
    "num_frames": 161,
    "width": 1248,
    "file_name": "sdm0KfmenrlywesfzY1Y1_if6euPp1.mp4",
    "height": 704,
    "content_type": "video/mp4"
  },
  "seed": 149063119,
  "prompt": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K film grain."
}

Other types#

LoRAInput#

path string* required

URL, HuggingFace repo ID (owner/repo) to lora weights.

weight_name string

Name of the LoRA weight. Only used if path is a HuggingFace repository, and is only required when the repository contains multiple LoRA weights.

scale float

Scale factor for LoRA application (0.0 to 4.0). Default value: 1

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

VideoFile#

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.

width integer

The width of the video

height integer

The height of the video

fps float

The FPS of the video

duration float

The duration of the video

num_frames integer

The number of frames in the video

fal-ai/ltx-2-19b/distilled/text-to-video/lora

fal-ai/ltx-2-19b/distilled/text-to-video/lora

fal-ai/ltx-2-19b/distilled/text-to-video/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#

LoRAInput#

ImageSize#

VideoFile#

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#

LoRAInput#

ImageSize#

VideoFile#

Related Models