API reference · Lightricks

lightricks/ltx-2.3-pro/text-to-video

Integrate this model through SandBase's unified API, with production-ready schemas and examples.

VIDEOAsyncOpen model
Production endpoint

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OpenAI-compatible endpoint with unified authentication and usage tracking.

POSThttps://api.sandbase.ai/v1/run
Model IDlightricks/ltx-2.3-pro/text-to-video
01

Input Schema

5 parameters · 1 required · 4 optional

ParameterTypeRequiredDescription
promptstringRequiredThe prompt to use for the generated video · Min length: 1 · Max length: 5000
durationintegerOptionalThe duration of the generated video in seconds · Options: 6, 8, 10 · Default: 6
6810
resolutionstringOptionalThe resolution of the generated video · Options: 1080p, 1440p, 2160p · Default: "1080p"
1080p1440p2160p
aspect_ratiostringOptionalThe aspect ratio of the generated image. · Options: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16
21:916:93:24:35:41:14:53:42:39:16
generate_audiobooleanOptionalWhether to generate audio for the generated video · Default: true
02

Output Schema

FieldTypeDescription
idstringUnique identifier for the generation task
statusstringTask status: pending, running, completed, failed, timeout
modelstringModel used for the generation
outputsarrayArray of output items
outputs[].urlstringURL of the generated artifact
outputs[].content_typestringMIME type (e.g. image/png, video/mp4)
errorobject | nullError details if failed, null on success
error.typestringMachine-readable error type code
error.messagestringHuman-readable error description

Async Workflow

This model uses asynchronous execution. Submit a request and poll for the result.

  1. Submit — POST to /v1/run, receive an id
  2. Poll — GET /v1/run/{id} until status is completed, failed, or timeout
  3. Retrieve — Read outputs from the completed response
03

Code Examples

Ready-to-run snippets

const apiKey = process.env.SANDBASE_API_KEY;
const response = await fetch("https://api.sandbase.ai/v1/run", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "lightricks/ltx-2.3-pro/text-to-video",
    "prompt": "Through-the-veil shot of a bride's face during an Indian wedding ceremony, camera positioned behind the sheer red dupatta fabric, the embroidered pattern creating a textured overlay on her face, her eyes lined with kohl looking down at henna-covered hands, marigold garlands in soft background bokeh, 85mm f/1.2 focused through the fabric layer, warm tungsten and candlelight, Mira Nair Monsoon Wedding intimacy",
    "duration": 6,
    "resolution": "1080p",
    "generate_audio": true
  }),
});

if (!response.ok) throw new Error(await response.text());
let result = await response.json();
for (let attempt = 0; attempt < 120 && !["completed", "failed", "timeout"].includes(result.status); attempt++) {
  await new Promise((resolve) => setTimeout(resolve, 2_000));
  const poll = await fetch(`https://api.sandbase.ai/v1/run/${result.id}`, {
    headers: { Authorization: `Bearer ${apiKey}` },
  });
  if (!poll.ok) throw new Error(await poll.text());
  result = await poll.json();
}
if (result.status !== "completed") throw new Error(`Generation ended: ${result.status}`);
console.log(result);