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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/lightning-models", {
input: {
prompt: "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting,"
},
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/lightning-models", {
input: {
prompt: "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting,"
},
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/lightning-models", {
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/lightning-models", {
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 use for generating the image. Be as descriptive as possible for best results.
negative_prompt stringThe negative prompt to use. Use it to address details that you don't want in the image. Default value: "(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)"
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: 5
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: 2
The list of LoRA weights to use.
The list of embeddings to use.
expand_prompt booleanIf set to true, the prompt will be expanded with additional prompts.
num_images integerThe number of images to generate. Default value: 1
seed integerThe same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time.
enable_safety_checker booleanIf set to true, the safety checker will be enabled. Default value: true
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.
format FormatEnumThe format of the generated image. Default value: "jpeg"
Possible enum values: jpeg, png
safety_checker_version SafetyCheckerVersionEnumThe 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
request_id stringAn id bound to a request, can be used with response to identify the request
itself. Default value: ""
{
"prompt": "A hyperdetailed photograph of a Cat dressed as a mafia boss holding a fish walking down a Japanese fish market with an angry face, 8k resolution, best quality, beautiful photograph, dynamic lighting,",
"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)",
"image_size": {
"height": 1024,
"width": 1024
},
"num_inference_steps": 5,
"guidance_scale": 2,
"loras": [],
"embeddings": [],
"num_images": 1,
"enable_safety_checker": true,
"format": "jpeg",
"safety_checker_version": "v1"
}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": ""
}height integerThe height of the generated image. Default value: 512
width integerThe width of the generated image. Default value: 512
force booleanIf set to true, the embedding will be forced to be used.
path string* requiredURL or path to a LoRA safetensors file. Or HF model name that resolves to safetensors 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: 1
path string* requiredURL or the path to the embedding weights.
The list of tokens to use for the embedding. When omitted, tokens are generated as <s0>, <s1>, ... to match the number of vectors in the embedding file.
url string* requiredwidth integer* requiredheight integer* requiredcontent_type stringDefault value: "image/jpeg"