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Leffa Predict Vt
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientSet 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/leffa/virtual-tryon", {
input: {
human_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg",
garment_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg",
garment_type: "upper_body"
},
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"
});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/leffa/virtual-tryon", {
input: {
human_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg",
garment_image_url: "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg",
garment_type: "upper_body"
},
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/leffa/virtual-tryon", {
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/leffa/virtual-tryon", {
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);Read more about file handling in our file upload guide.
num_inference_steps integerThe number of inference steps to perform. Default value: 50
seed integerThe same seed and the same input given to the same version of the model 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 input when generating the image. Default value: 2.5
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.
enable_safety_checker booleanIf set to true, the safety checker will be enabled. Disabling it requires account authorization; unauthorized requests are always checked, and images flagged as unsafe are returned as black images. Default value: true
output_format OutputFormatEnumThe format of the generated image. Default value: "png"
Possible enum values: jpeg, png
human_image_url string* requiredUrl for the human image.
garment_image_url string* requiredUrl to the garment image.
garment_type GarmentTypeEnum* requiredThe type of the garment used for virtual try-on.
Possible enum values: upper_body, lower_body, dresses
{
"num_inference_steps": 50,
"guidance_scale": 2.5,
"enable_safety_checker": true,
"output_format": "png",
"human_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/person_image.jpg",
"garment_image_url": "https://storage.googleapis.com/falserverless/model_tests/leffa/tshirt_image.jpg",
"garment_type": "upper_body"
}The output image.
seed integer* requiredThe seed for the inference.
has_nsfw_concepts boolean* requiredWhether the image contains NSFW concepts.
{
"image": {
"content_type": "image/jpeg",
"width": 768,
"url": "https://fal.media/files/elephant/9NTQQNo9eyiQUSLa6cYBW.png",
"height": 1024
}
}url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
width integerThe width of the image in pixels.
height integerThe height of the image in pixels.