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Generate videos from prompts using LTX Video 0.9.1
fal-ai/ltx-video
Generate videos from prompts using LTX Video 0.9.1
Inference
Research only
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LTX Video - Text to Video generation
See examples for more inspiration.
When writing prompts, focus on detailed, chronological descriptions of actions and scenes. Include specific movements, appearances, camera angles, and environmental details - all in a single flowing paragraph. Start directly with the action, and keep descriptions literal and precise. Think like a cinematographer describing a shot list. Keep within 200 words. For best results, build your prompts using this structure:
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @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.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"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-video", {
input: {
prompt: "A man stands waist-deep in a crystal-clear mountain pool, his back turned to a massive, thundering waterfall that cascades down jagged cliffs behind him. He wears a dark blue swimming shorts and his muscular back glistens with water droplets. The camera moves in a dynamic circular motion around him, starting from his right side and sweeping left, maintaining a slightly low angle that emphasizes the towering height of the waterfall. As the camera moves, the man slowly turns his head to follow its movement, his expression one of awe as he gazes up at the natural wonder. The waterfall creates a misty atmosphere, with sunlight filtering through the spray to create rainbow refractions. The water churns and ripples around him, reflecting the dramatic landscape. The handheld camera movement adds a subtle shake that enhances the raw, untamed energy of the scene. The lighting is natural and bright, with the sun positioned behind the waterfall, creating a backlit effect that silhouettes the falling water and illuminates the mist."
},
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);The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_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.
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-video", {
input: {
prompt: "A man stands waist-deep in a crystal-clear mountain pool, his back turned to a massive, thundering waterfall that cascades down jagged cliffs behind him. He wears a dark blue swimming shorts and his muscular back glistens with water droplets. The camera moves in a dynamic circular motion around him, starting from his right side and sweeping left, maintaining a slightly low angle that emphasizes the towering height of the waterfall. As the camera moves, the man slowly turns his head to follow its movement, his expression one of awe as he gazes up at the natural wonder. The waterfall creates a misty atmosphere, with sunlight filtering through the spray to create rainbow refractions. The water churns and ripples around him, reflecting the dramatic landscape. The handheld camera movement adds a subtle shake that enhances the raw, untamed energy of the scene. The lighting is natural and bright, with the sun positioned behind the waterfall, creating a backlit effect that silhouettes the falling water and illuminates the mist."
},
webhookUrl: "https://optional.webhook.url/for/results",
});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-video", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});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-video", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);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.
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.
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.
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);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.
prompt string* requiredThe prompt to generate the video from.
negative_prompt stringThe negative prompt to generate the video from. Default value: "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly"
seed integerThe seed to use for random number generation.
num_inference_steps integerThe number of inference steps to take. Default value: 30
guidance_scale floatThe guidance scale to use. Default value: 3
enable_safety_checker booleanAuthorized callers may set false to request relaxed screening. Default value: true
{
"prompt": "A man stands waist-deep in a crystal-clear mountain pool, his back turned to a massive, thundering waterfall that cascades down jagged cliffs behind him. He wears a dark blue swimming shorts and his muscular back glistens with water droplets. The camera moves in a dynamic circular motion around him, starting from his right side and sweeping left, maintaining a slightly low angle that emphasizes the towering height of the waterfall. As the camera moves, the man slowly turns his head to follow its movement, his expression one of awe as he gazes up at the natural wonder. The waterfall creates a misty atmosphere, with sunlight filtering through the spray to create rainbow refractions. The water churns and ripples around him, reflecting the dramatic landscape. The handheld camera movement adds a subtle shake that enhances the raw, untamed energy of the scene. The lighting is natural and bright, with the sun positioned behind the waterfall, creating a backlit effect that silhouettes the falling water and illuminates the mist.",
"negative_prompt": "low quality, worst quality, deformed, distorted, disfigured, motion smear, motion artifacts, fused fingers, bad anatomy, weird hand, ugly",
"num_inference_steps": 30,
"guidance_scale": 3,
"enable_safety_checker": true
}The generated video.
seed integer* requiredThe seed used for random number generation.
{
"video": {
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019
}
}url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.