Luma Dream Machine Text to Video
About
Text To Video
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/luma-dream-machine", {
input: {
prompt: "A teddy bear in sunglasses playing electric guitar and dancing"
},
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/luma-dream-machine", {
input: {
prompt: "A teddy bear in sunglasses playing electric guitar and dancing"
},
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/luma-dream-machine", {
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/luma-dream-machine", {
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
* requiredaspect_ratio
AspectRatioEnum
The aspect ratio of the generated video Default value: "16:9"
Possible enum values: 16:9, 9:16, 4:3, 3:4, 21:9, 9:21
loop
boolean
Whether the video should loop (end of video is blended with the beginning)
{
"prompt": "A teddy bear in sunglasses playing electric guitar and dancing",
"aspect_ratio": "16:9"
}
Output#
The generated video
{
"video": {
"url": "https://v2.fal.media/files/807e842c734f4127a36de9262a2d292c_output.mp4"
}
}
Other types#
Ray2ImageToVideoRequest#
prompt
string
* requiredimage_url
string
Initial image to start the video from. Can be used together with end_image_url.
end_image_url
string
Final image to end the video with. Can be used together with image_url.
aspect_ratio
AspectRatioEnum
The aspect ratio of the generated video Default value: "16:9"
Possible enum values: 16:9, 9:16, 4:3, 3:4, 21:9, 9:21
loop
boolean
Whether the video should loop (end of video is blended with the beginning)
resolution
ResolutionEnum
The resolution of the generated video (720p costs 2x more) Default value: "540p"
Possible enum values: 540p, 720p
duration
DurationEnum
The duration of the generated video Default value: "5s"
Possible enum values: 5s
Ray2TextToVideoRequest#
prompt
string
* requiredaspect_ratio
AspectRatioEnum
The aspect ratio of the generated video Default value: "16:9"
Possible enum values: 16:9, 9:16, 4:3, 3:4, 21:9, 9:21
loop
boolean
Whether the video should loop (end of video is blended with the beginning)
resolution
ResolutionEnum
The resolution of the generated video (720p costs 2x more) Default value: "540p"
Possible enum values: 540p, 720p
duration
DurationEnum
The duration of the generated video (9s costs 2x more) Default value: "5s"
Possible enum values: 5s, 9s
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
ImageToVideoRequest#
prompt
string
* requiredimage_url
string
* requiredend_image_url
string
An image to blend the end of the video with
aspect_ratio
AspectRatioEnum
The aspect ratio of the generated video Default value: "16:9"
Possible enum values: 16:9, 9:16, 4:3, 3:4, 21:9, 9:21
loop
boolean
Whether the video should loop (end of video is blended with the beginning)
Related Models
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Generate video clips from your prompts using Kling 1.6 (std)
Generate high quality video clips from text prompts using PixVerse v3.5