Caption
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"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/marlin", {
input: {
video_url: "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
prompt: "Provide a spatial description of this clip followed by time-ranged events.
For each event, give the time range as <start - end> and a short description."
},
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);The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_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.
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/marlin", {
input: {
video_url: "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
prompt: "Provide a spatial description of this clip followed by time-ranged events.
For each event, give the time range as <start - end> and a short description."
},
webhookUrl: "https://optional.webhook.url/for/results",
});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/marlin", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});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/marlin", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);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.
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.
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.
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);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.
video_url string* requiredURL of the video to caption. Up to ~2 minutes is supported.
prompt string* requiredCaption prompt sent to the model. The example value is Marlin's canonical training prompt — overriding usually degrades output quality.
max_tokens integerMaximum number of tokens to generate for the caption. Default value: 2048
do_sample booleanIf true, sample with temperature/top_p; if false, use greedy decoding.
temperature floatSampling temperature. Only used when do_sample is true. Default value: 1
top_p floatNucleus sampling threshold. Only used when do_sample is true. Default value: 1
{
"video_url": "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
"prompt": "Provide a spatial description of this clip followed by time-ranged events.\nFor each event, give the time range as <start - end> and a short description.",
"max_tokens": 2048,
"temperature": 1,
"top_p": 1
}scene string* requiredSpatial description of the clip.
Time-ranged events parsed from the caption.
text string* requiredFull post-thinking caption text (Scene + Events) as returned by the model.
{
"scene": "",
"events": [
{
"start": 0,
"text": "a person waves",
"end": 1.5
}
],
"text": ""
}start float* requiredStart time in seconds.
end float* requiredEnd time in seconds.
text stringShort description of the event (caption mode only).