Fooocus Text to Image
About
Image 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/fast-fooocus-sdxl/image-to-image", {
input: {
image_url: "https://fal-cdn.batuhan-941.workers.dev/files/tiger/IExuP-WICqaIesLZAZPur.jpeg",
prompt: "an island near sea, with seagulls, moon shining over the sea, light house, boats int he background, fish flying over the sea"
},
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);
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/fast-fooocus-sdxl/image-to-image", {
input: {
image_url: "https://fal-cdn.batuhan-941.workers.dev/files/tiger/IExuP-WICqaIesLZAZPur.jpeg",
prompt: "an island near sea, with seagulls, moon shining over the sea, light house, boats int he background, fish flying over the sea"
},
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/fast-fooocus-sdxl/image-to-image", {
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/fast-fooocus-sdxl/image-to-image", {
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#
image_url
string
* requiredThe URL of the image to use as a starting point for the generation.
prompt
string
* requiredThe prompt to use for generating the image. Be as descriptive as possible for best results.
negative_prompt
string
The 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: ""
The size of the generated image. Leave it none to automatically infer from the prompt image.
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
integer
The number of inference steps to perform. Default value: 8
guidance_scale
float
The 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: 2
strength
float
determines how much the generated image resembles the initial image Default value: 0.95
seed
integer
The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
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
safety_checker_version
SafetyCheckerVersionEnum
The version of the safety checker to use. v1 is the default CompVis safety checker. v2 uses a custom ViT model. Default value: "v1"
Possible enum values: v1, v2
expand_prompt
boolean
If set to true, the prompt will be expanded with additional prompts. Default value: true
format
FormatEnum
The format of the generated image. Default value: "jpeg"
Possible enum values: jpeg, png
guidance_rescale
float
The rescale factor for the CFG.
enable_refiner
boolean
If set to true, a smaller model will try to refine the output after it was processed. Default value: true
{
"image_url": "https://fal-cdn.batuhan-941.workers.dev/files/tiger/IExuP-WICqaIesLZAZPur.jpeg",
"prompt": "an island near sea, with seagulls, moon shining over the sea, light house, boats int he background, fish flying over the sea",
"negative_prompt": "cartoon, illustration, animation. face. male, female",
"image_size": null,
"num_inference_steps": 8,
"guidance_scale": 2,
"strength": 0.95,
"num_images": 1,
"embeddings": [],
"enable_safety_checker": true,
"safety_checker_version": "v1",
"expand_prompt": true,
"format": "jpeg",
"enable_refiner": true
}
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
force
boolean
If set to true, the embedding will be forced to be used.
Image#
url
string
* requiredwidth
integer
* requiredheight
integer
* requiredcontent_type
string
Default value: "image/jpeg"
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