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Generic Fooocus
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/fooocus", {
input: {},
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/fooocus", {
input: {},
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/fooocus", {
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/fooocus", {
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 stringThe prompt to use for generating the image. Be as descriptive as possible for best results. Default value: ""
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: ""
The style to use.
performance PerformanceEnumYou can choose Speed or Quality Default value: "Extreme Speed"
Possible enum values: Speed, Quality, Extreme Speed, Lightning
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: 4
sharpness floatThe sharpness of the generated image. Use it to control how sharp the generated
image should be. Higher value means image and texture are sharper. Default value: 2
aspect_ratio stringThe size of the generated image. You can choose between some presets or
custom height and width that must be multiples of 8. Default value: "1024x1024"
num_images integerNumber of images to generate in one request Default value: 1
The LoRAs to use for the image generation. You can use up to 5 LoRAs and they will be merged together to generate the final image.
refiner_model RefinerModelEnumRefiner (SDXL or SD 1.5) Default value: "None"
Possible enum values: None, realisticVisionV60B1_v51VAE.safetensors
refiner_switch floatUse 0.4 for SD1.5 realistic models; 0.667 for SD1.5 anime models
0.8 for XL-refiners; or any value for switching two SDXL models. Default value: 0.8
output_format OutputFormatEnumThe format of the generated image. Default value: "jpeg"
Possible enum values: png, jpeg, webp
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.
seed integerThe same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
control_image_url stringThe image to use as a reference for the generated image.
control_type ControlTypeEnumThe type of image control Default value: "PyraCanny"
Possible enum values: ImagePrompt, PyraCanny, CPDS, FaceSwap
control_image_weight floatThe strength of the control image. Use it to control how much the generated image
should look like the control image. Default value: 1
control_image_stop_at floatThe stop at value of the control image. Use it to control how much the generated image
should look like the control image. Default value: 1
inpaint_image_url stringThe image to use as a reference for inpainting.
mask_image_url stringThe image to use as a mask for the generated image.
mixing_image_prompt_and_inpaint booleanenable_safety_checker booleanIf set to false, the safety checker will be disabled. Disabling it requires account authorization; unauthorized requests are always checked, and images flagged as unsafe are returned as black images. Default value: true
{
"prompt": "an astronaut in the jungle, cold color palette with butterflies in the background, highly detailed, 8k",
"negative_prompt": "(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)",
"styles": [
"Fooocus Enhance",
"Fooocus V2",
"Fooocus Sharp"
],
"performance": "Extreme Speed",
"guidance_scale": 4,
"sharpness": 2,
"aspect_ratio": "1024x1024",
"num_images": 1,
"loras": [
{
"path": "https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_offset_example-lora_1.0.safetensors",
"scale": 0.1
}
],
"refiner_model": "None",
"refiner_switch": 0.8,
"output_format": "jpeg",
"seed": 176400,
"control_type": "ImagePrompt",
"control_image_weight": 1,
"control_image_stop_at": 1,
"enable_safety_checker": true
}The generated image file info.
The time taken for the generation process.
Whether the generated images contain NSFW concepts.
{
"images": [
{
"url": "",
"content_type": "image/png",
"file_name": "z9RV14K95DvU.png",
"file_size": 4404019,
"width": 1024,
"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.
path string* requiredURL or the path to the LoRA weights.
scale floatThe scale of the LoRA weight. This is used to scale the LoRA weight
before merging it with the base model. Default value: 0.1