Skip to main content
The client.queue.submit() method submits a job for asynchronous processing and returns immediately with a job ID.

​
Method Signature

submit: <T extends VideoModelDefinition>(
  options: QueueSubmitOptions<T>
) => Promise<JobSubmitResponse>

​
Parameters

​
options.model
VideoModelDefinition
required
The video model to use. Get model definitions using models.video().
​
options.signal
AbortSignal
Optional AbortSignal for canceling the request.
Additional parameters depend on the model type (see examples below).

​
Return Value

type JobSubmitResponse = {
  job_id: string;  // Unique identifier for the job
  status: JobStatus;  // Initial status (usually "pending")
}

​
Text-to-Video (T2V)

Generate video from a text prompt: 
import { createDecartClient, models } from "@decart/sdk";

const client = createDecartClient({
  apiKey: process.env.DECART_API_KEY,
});

const job = await client.queue.submit({
  model: models.video("lucy-pro-t2v"),
  prompt: "A serene lake at sunset with mountains in the background",
  resolution: "720p",  // "720p" | "480p" (default: "720p")
  seed: 42,  // Optional: for reproducible results
});

console.log("Job ID:", job.job_id);
console.log("Status:", job.status);

​
Image-to-Video (I2V)

Animate a static image: 
const job = await client.queue.submit({
  model: models.video("lucy-pro-i2v"),
  prompt: "Camera slowly zooms in",
  data: "https://example.com/image.jpg",  // URL, File, or Blob
  resolution: "720p",
  seed: 42,
});

console.log("Job ID:", job.job_id);

​
File Input Options

The data parameter accepts multiple input types: 
// URL string
data: "https://example.com/image.jpg"

// File object (browser)
data: fileInputElement.files[0]

// Blob
data: new Blob([arrayBuffer], { type: "image/jpeg" })

// URL object
data: new URL("https://example.com/image.jpg")

// ReadableStream
data: response.body

// React Native file object
data: {
  uri: "file:///path/to/image.jpg",
  type: "image/jpeg",
  name: "image.jpg"
}

​
Video-to-Video (V2V)

Transform existing video with a prompt: 
const job = await client.queue.submit({
  model: models.video("lucy-pro-v2v"),
  prompt: "Transform into a watercolor painting style",
  data: "https://example.com/video.mp4",
  resolution: "720p",
  seed: 42,
  enhance_prompt: true,  // Optional: enhance the prompt automatically
});

​
With Reference Image

Use a reference image to guide the transformation: 
const job = await client.queue.submit({
  model: models.video("lucy-pro-v2v"),
  prompt: "Add fireworks to the night sky",
  data: "https://example.com/video.mp4",
  reference_image: "https://example.com/fireworks.jpg",  // Optional reference
  resolution: "720p",
  seed: 42,
});

​
First-Last-Frame-to-Video (FLF2V)

Generate video interpolation between two frames: 
const job = await client.queue.submit({
  model: models.video("lucy-pro-flf2v"),
  prompt: "Smooth transition from day to night",
  start: "https://example.com/day.jpg",  // First frame
  end: "https://example.com/night.jpg",  // Last frame
  resolution: "720p",
  seed: 42,
});

​
Motion-Based Animation

Animate an image with trajectory-guided motion: 
const job = await client.queue.submit({
  model: models.video("lucy-motion"),
  data: "https://example.com/character.jpg",
  trajectory: [
    { frame: 0, x: 100, y: 100 },   // Starting position
    { frame: 60, x: 500, y: 300 },  // Middle position
    { frame: 120, x: 900, y: 100 }, // End position
  ],
  resolution: "720p",
  seed: 42,
});
The trajectory defines the path of motion for an object in the image:
  • frame: Frame number (0-based)
  • x: Horizontal position in pixels
  • y: Vertical position in pixels

​
Video Restyling

Restyle video using either a text prompt or reference image:

​
With Text Prompt

const job = await client.queue.submit({
  model: models.video("lucy-restyle-v2v"),
  prompt: "Turn into anime style",
  data: "https://example.com/video.mp4",
  resolution: "720p",
  enhance_prompt: true,
  seed: 42,
});

​
With Reference Image

const job = await client.queue.submit({
  model: models.video("lucy-restyle-v2v"),
  reference_image: "https://example.com/style-reference.jpg",
  data: "https://example.com/video.mp4",
  resolution: "720p",
  seed: 42,
});
For lucy-restyle-v2v, you must provide either prompt or reference_image, but not both. The enhance_prompt parameter is only valid when using a text prompt.

​
Error Handling

The submit method validates inputs before sending the request: 
try {
  const job = await client.queue.submit({
    model: models.video("lucy-pro-t2v"),
    prompt: "",  // Invalid: empty prompt
  });
} catch (error) {
  console.error("Invalid input:", error.message);
  // Error: Invalid inputs for lucy-pro-t2v: String must contain at least 1 character(s)
}

​
Next Steps

Polling

Learn how to poll for job completion

Status & Errors

Understand job status and error handling

Build docs developers (and LLMs) love

Get started for freeTalk to us