DocsBlogPricingEnterpriseCareersResearch Grants
Log-inSign-up

Ltx Video V097 Video to Video

fal-ai/ltx-video-v097/extend
Extend videos with prompts and videos using LTX Video-0.9.6
Inference
Commercial use
PlaygroundAPI

About

Generate a video from a prompt.

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

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-video-v097/extend", {
  input: {
    prompt: "Woman walking on a street in Tokyo",
    video: {
      video_url: "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4",
      start_frame_num: 24
    }
  },
  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 case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

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

3. Queue#

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-video-v097/extend", {
  input: {
    prompt: "Woman walking on a street in Tokyo",
    video: {
      video_url: "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4",
      start_frame_num: 24
    }
  },
  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-video-v097/extend", {
  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-video-v097/extend", {
  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);

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

Text prompt to guide generation

negative_prompt string

Negative prompt for generation Default value: "worst quality, inconsistent motion, blurry, jittery, distorted"

resolution ResolutionEnum

Resolution of the generated video (480p or 720p). Default value: "720p"

Possible enum values: 480p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video (16:9 or 9:16). Default value: "16:9"

Possible enum values: 9:16, 16:9

seed integer

Random seed for generation

num_inference_steps integer

Number of inference steps Default value: 40

expand_prompt boolean

Whether to expand the prompt using the model's own capabilities. Default value: true

video VideoConditioningInput* required

Video to be extended.

{
  "prompt": "Woman walking on a street in Tokyo",
  "negative_prompt": "worst quality, inconsistent motion, blurry, jittery, distorted",
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "num_inference_steps": 40,
  "expand_prompt": true,
  "video": {
    "video_url": "https://storage.googleapis.com/falserverless/web-examples/wan/t2v.mp4",
    "start_frame_num": 24
  }
}

Output#

video File* required

The generated video file.

seed integer* required

The seed used for generation.

{
  "video": {
    "url": "https://storage.googleapis.com/falserverless/example_outputs/ltx-v095_extend.mp4"
  }
}

Other types#

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.

file_data string

File data

Related Models