LTX Video-0.9.7 LoRA Text to Video
This endpoint is deprecated
This model is no longer supported.
This endpoint is deprecated
This model is no longer supported.
About
Generate a video from a text 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
Migrate to @fal-ai/client
The @fal-ai/serverless-client
package has been deprecated in favor of @fal-ai/client
. Please check the migration guide for more information.
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-lora", {
input: {
prompt: "A close-up reveals a fluffy ginger tabby cat, its fur a vibrant mix of orange, cream, and black, walking delicately along a sun-drenched sidewalk. Medium shot shows the cat's paws stepping lightly on the warm grey concrete, each pad a soft, almost imperceptible pink. The sidewalk's texture is rough, with small pebbles embedded in the cement. A slight shadow stretches from the cat, indicating a high sun angle. The surrounding environment blurs subtly, suggesting a quiet residential street with hints of green foliage in the background. The overall mood is peaceful and serene, bathed in the warm glow of late afternoon sun. The cat's amber eyes gleam with curiosity. High resolution 4k"
},
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#
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#
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-lora", {
input: {
prompt: "A close-up reveals a fluffy ginger tabby cat, its fur a vibrant mix of orange, cream, and black, walking delicately along a sun-drenched sidewalk. Medium shot shows the cat's paws stepping lightly on the warm grey concrete, each pad a soft, almost imperceptible pink. The sidewalk's texture is rough, with small pebbles embedded in the cement. A slight shadow stretches from the cat, indicating a high sun angle. The surrounding environment blurs subtly, suggesting a quiet residential street with hints of green foliage in the background. The overall mood is peaceful and serene, bathed in the warm glow of late afternoon sun. The cat's amber eyes gleam with curiosity. High resolution 4k"
},
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-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-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
* requiredThe prompt to generate the video from.
negative_prompt
string
The negative prompt to use. Default value: "blurry, low quality, low resolution, inconsistent motion, jittery, distorted"
The LoRA weights to use for generation. Default value: ``
resolution
ResolutionEnum
The resolution of the video. Default value: "720p"
Possible enum values: 480p, 720p
aspect_ratio
AspectRatioEnum
The aspect ratio of the video. Default value: "16:9"
Possible enum values: 16:9, 1:1, 9:16
number_of_frames
integer
The number of frames in the video. Default value: 89
number_of_steps
integer
The number of inference steps to use. Default value: 30
frame_rate
integer
The frame rate of the video. Default value: 25
seed
integer
The seed to use for generation.
expand_prompt
boolean
Whether to expand the prompt using the LLM.
reverse_video
boolean
Whether to reverse the video.
enable_safety_checker
boolean
Whether to enable the safety checker. Default value: true
{
"prompt": "A close-up reveals a fluffy ginger tabby cat, its fur a vibrant mix of orange, cream, and black, walking delicately along a sun-drenched sidewalk. Medium shot shows the cat's paws stepping lightly on the warm grey concrete, each pad a soft, almost imperceptible pink. The sidewalk's texture is rough, with small pebbles embedded in the cement. A slight shadow stretches from the cat, indicating a high sun angle. The surrounding environment blurs subtly, suggesting a quiet residential street with hints of green foliage in the background. The overall mood is peaceful and serene, bathed in the warm glow of late afternoon sun. The cat's amber eyes gleam with curiosity. High resolution 4k",
"negative_prompt": "blurry, low quality, low resolution, inconsistent motion, jittery, distorted",
"loras": [],
"resolution": "720p",
"aspect_ratio": "16:9",
"number_of_frames": 89,
"number_of_steps": 30,
"frame_rate": 25,
"expand_prompt": false,
"reverse_video": false,
"enable_safety_checker": true
}
Output#
prompt
string
* requiredThe prompt used for generation.
seed
integer
* requiredThe seed used for generation.
The generated video.
{
"prompt": "A cute cat walking on a sidewalk",
"video": {
"url": "https://storage.googleapis.com/falserverless/example_outputs/ltx-t2v_output.mp4"
}
}
Other types#
VideoCondition#
video_url
string
* requiredThe URL of the video to use as input.
start_frame_number
integer
The frame number to start the condition on.
strength
float
The strength of the condition. Default value: 1
File#
url
string
* requiredThe 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
LoRAWeight#
path
string
* requiredURL or path to the 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 of the LoRA weight. This is a multiplier applied to the LoRA weight when loading it. Default value: 1
ImageCondition#
image_url
string
* requiredThe URL of the image to use as input.
start_frame_number
integer
The frame number to start the condition on.
strength
float
The strength of the condition. Default value: 1