Luma Dream Machine | Text to Video | API Documentation

fal-ai/luma-dream-machine

Generate video clips from your prompts using Luma Dream Machine v1.5

Inference

Partner

Commercial use

Schema

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#

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"
});

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/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* required

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)

{
  "prompt": "A teddy bear in sunglasses playing electric guitar and dancing",
  "aspect_ratio": "16:9"
}

Output#

video File* required

The generated video

{
  "video": {
    "url": "https://v2.fal.media/files/807e842c734f4127a36de9262a2d292c_output.mp4"
  }
}

Other types#

Ray2ImageToVideoRequest#

prompt string* required

image_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, 1080p costs 4x more) Default value: "540p"

Possible enum values: 540p, 720p, 1080p

duration DurationEnum

The duration of the generated video Default value: "5s"

Possible enum values: 5s

Ray2TextToVideoRequest#

prompt string* required

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, 1080p costs 4x more) Default value: "540p"

Possible enum values: 540p, 720p, 1080p

duration DurationEnum

The duration of the generated video (9s costs 2x more) Default value: "5s"

Possible enum values: 5s, 9s

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

ImageToVideoRequest#

prompt string* required

image_url string* required

end_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

fal-ai/ltx-video

text-to-video

Generate videos from prompts using LTX Video

fal-ai/kling-video/v1.5/pro/effects

text-to-video

Generate video clips from your prompts using Kling 1.5 (pro)

new

fal-ai/wan-t2v

text-to-video

Wan-2.1 is a text-to-video model that generates high-quality videos with high visual quality and motion diversity from text prompts

new

text to video

motion

Luma Dream Machine Text to Video

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#

Ray2ImageToVideoRequest#

Ray2TextToVideoRequest#

File#

ImageToVideoRequest#

Related Models