Generate
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/omnigen-v2", {
input: {
prompt: "Make the dress blue"
},
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/omnigen-v2", {
input: {
prompt: "Make the dress blue"
},
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/omnigen-v2", {
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/omnigen-v2", {
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 generate or edit an image. Use specific language like 'Add the bird from image 1 to the desk in image 2' for better results.
URLs of input images to use for image editing or multi-image generation. Support up to 3 images.
The 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 integerThe number of inference steps to perform. Default value: 50
seed integerThe same seed and the same prompt given to the same version of the model will output the same image every time.
text_guidance_scale floatThe Text Guidance scale controls how closely the model follows the text prompt.
Higher values make the model stick more closely to the prompt. Default value: 5
image_guidance_scale floatThe Image Guidance scale controls how closely the model follows the input images.
For image editing: 1.3-2.0, for in-context generation: 2.0-3.0 Default value: 2
negative_prompt stringNegative prompt to guide what should not be in the image. Default value: "(((deformed))), blurry, over saturation, bad anatomy, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), fused fingers, messy drawing, broken legs censor, censored, censor_bar"
cfg_range_start floatCFG range start value.
cfg_range_end floatCFG range end value. Default value: 1
scheduler SchedulerEnumThe scheduler to use for the diffusion process. Default value: "euler"
Possible enum values: euler, dpmsolver
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. Default value: 1
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: "jpeg"
Possible enum values: jpeg, png
{
"prompt": "Make the dress blue",
"input_image_urls": [
"https://storage.googleapis.com/falserverless/omnigen/input.png"
],
"image_size": "square_hd",
"num_inference_steps": 50,
"text_guidance_scale": 5,
"image_guidance_scale": 2,
"negative_prompt": "(((deformed))), blurry, over saturation, bad anatomy, disfigured, poorly drawn face, mutation, mutated, (extra_limb), (ugly), (poorly drawn hands), fused fingers, messy drawing, broken legs censor, censored, censor_bar",
"cfg_range_end": 1,
"scheduler": "euler",
"num_images": 1,
"enable_safety_checker": true,
"output_format": "jpeg"
}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": ""
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
url string* requiredwidth integer* requiredheight integer* requiredcontent_type stringDefault value: "image/jpeg"