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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/lcm-sd15-i2i", {
input: {
prompt: "masterpiece, colorful, photo of a beach in hawaii, sun",
image_url: "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png"
},
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);This model has a real-time mode via WebSockets, supported by fal.realtime.connect.
import { fal } from "@fal-ai/client";
const connection = fal.realtime.connect("fal-ai/lcm-sd15-i2i", {
onResult: (result) => {
console.log(result);
},
onError: (error) => {
console.error(error);
},
// Fetch short-lived JWT token from your backend
tokenProvider: async (app) => {
const response = await fetch("/api/fal/realtime-token", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ app }),
});
return response.text();
},
tokenExpirationSeconds: 10,
});
connection.send({
prompt: "masterpiece, colorful, photo of a beach in hawaii, sun",
image_url: "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png"
});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/lcm-sd15-i2i", {
input: {
prompt: "masterpiece, colorful, photo of a beach in hawaii, sun",
image_url: "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png"
},
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/lcm-sd15-i2i", {
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/lcm-sd15-i2i", {
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.
prompt string* requiredThe prompt to use for generating the image. Be as descriptive as possible for best results.
image_url string* requiredThe image to use as a base.
mask_url stringMask URL for compatibility with generic LCM processing.
strength floatThe strength of the image. Default value: 0.8
negative_prompt stringThe negative prompt to use.Use it to address details that you don't want
in the image. This could be colors, objects, scenery and even the small details
(e.g. moustache, blurry, low resolution). Default value: ""
seed integerThe same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
guidance_scale floatThe CFG (Classifier Free Guidance) scale is a measure of how close you want
the model to stick to your prompt when looking for a related image to show you. Default value: 1
num_inference_steps integerThe number of inference steps to use for generating the image. The more steps
the better the image will be but it will also take longer to generate. Default value: 4
sync_mode booleanIf True, the media will be returned as a data URI and the output data won't be available in the request history.
num_images integerThe number of images to generate. The function will return a list of images
with the same prompt and negative prompt but different seeds. Default value: 1
enable_safety_checks booleanIf set to true, the resulting image will be checked whether it includes any
potentially unsafe content. If it does, it will be replaced with a black
image. Disabling safety checks requires account authorization; unauthorized
requests are always checked. Default value: true
request_id stringAn id bound to a request, can be used with response to identify the request
itself. Default value: ""
enable_safety_checker booleanAuthorized callers may set false to request relaxed screening. Default value: true
{
"prompt": "masterpiece, colorful, photo of a beach in hawaii, sun",
"image_url": "https://storage.googleapis.com/falserverless/model_tests/lcm/beach.png",
"strength": 0.8,
"negative_prompt": "cartoon, illustration, animation. face. male, female",
"seed": 42,
"guidance_scale": 1,
"num_inference_steps": 4,
"num_images": 1,
"enable_safety_checks": true,
"enable_safety_checker": true
}The generated image files info.
seed integer* requiredSeed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed.
num_inference_steps integerNumber of inference steps used to generate the image. It will be the same value of the one passed in the
input or the default one in case none was passed. Default value: 4
request_id stringAn id bound to a request, can be used with response to identify the request
itself. Default value: ""
A list of booleans indicating whether the generated image contains any potentially unsafe content. If the safety check is disabled, this field will have a false for each generated image.
{
"images": [
{
"url": "",
"content_type": "image/jpeg"
}
],
"num_inference_steps": 4
}url string* requiredwidth integer* requiredheight integer* requiredcontent_type stringDefault value: "image/jpeg"