Hyper SDXL Text to Image
About
Text To Image
1. Calling the API#
Install the client#
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/client
Migrate to @fal-ai/client
The @fal-ai/serverless-client
package has been deprecated in favor of @fal-ai/client
. Please check the migration guide for more information.
Setup your API Key#
Set FAL_KEY
as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"
Submit a request#
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/hyper-sdxl", {
input: {
prompt: "An ethereal, awe-inspiring vista: a snowy landscape with a majestic ice sculpture illuminated by a celestial aurora."
},
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);
Real-time via WebSockets#
This model has a real-time mode via websockets, this is supported via the fal.realtime
client.
import { fal } from "@fal-ai/client";
const connection = fal.realtime.connect("fal-ai/hyper-sdxl", {
onResult: (result) => {
console.log(result);
},
onError: (error) => {
console.error(error);
}
});
connection.send({
prompt: "An ethereal, awe-inspiring vista: a snowy landscape with a majestic ice sculpture illuminated by a celestial aurora."
});
2. Authentication#
The API uses an API Key for authentication. It is recommended you set the FAL_KEY
environment variable in your runtime when possible.
API Key#
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});
Protect your API 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.
3. Queue#
Submit a request#
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/hyper-sdxl", {
input: {
prompt: "An ethereal, awe-inspiring vista: a snowy landscape with a majestic ice sculpture illuminated by a celestial aurora."
},
webhookUrl: "https://optional.webhook.url/for/results",
});
Fetch request status#
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/hyper-sdxl", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});
Get the result#
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/hyper-sdxl", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);
4. Files#
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.
Data URI (base64)#
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.
Hosted files (URL)#
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.
Uploading files#
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);
Auto uploads
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.
5. Schema#
Input#
prompt
string
* requiredThe size of the generated image. Default value: square_hd
Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
Note: For custom image sizes, you can pass the width
and height
as an object:
"image_size": {
"width": 1280,
"height": 720
}
num_inference_steps
NumInferenceStepsEnum
The number of inference steps to perform. Default value: "1"
Possible enum values: 1, 2, 4
seed
integer
The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
sync_mode
boolean
If set to true, the function will wait for the image to be generated and uploaded before returning the response. This will increase the latency of the function but it allows you to get the image directly in the response without going through the CDN.
num_images
integer
The number of images to generate. Default value: 1
The list of embeddings to use. Default value: ``
enable_safety_checker
boolean
If set to true, the safety checker will be enabled. Default value: true
expand_prompt
boolean
If set to true, the prompt will be expanded with additional prompts.
format
FormatEnum
The format of the generated image. Default value: "jpeg"
Possible enum values: jpeg, png
{
"prompt": "An ethereal, awe-inspiring vista: a snowy landscape with a majestic ice sculpture illuminated by a celestial aurora.",
"image_size": "square_hd",
"num_inference_steps": 1,
"num_images": 1,
"embeddings": [],
"enable_safety_checker": true,
"format": "jpeg"
}
Output#
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.
Whether the generated images contain NSFW concepts.
prompt
string
* requiredThe prompt used for generating the image.
{
"images": [
{
"url": "",
"content_type": "image/jpeg"
}
],
"prompt": ""
}
Other types#
ImageSize#
width
integer
The width of the generated image. Default value: 512
height
integer
The height of the generated image. Default value: 512
LoraWeight#
path
string
* requiredURL or the path to the LoRA weights. Or HF model name.
scale
float
The scale of the LoRA weight. This is used to scale the LoRA weight
before merging it with the base model. Default value: 1
Embedding#
path
string
* requiredURL or the path to the embedding weights.
The list of tokens to use for the embedding. Default value: <s0>,<s1>
Image#
url
string
* requiredwidth
integer
* requiredheight
integer
* requiredcontent_type
string
Default value: "image/jpeg"
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