Text-to-image generation with LoRA support for FLUX.2 [dev] from Black Forest Labs. Custom style adaptation and fine-tuned model variations.
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/flux-2/lora", {
input: {
prompt: "Close shot a pianist plays in a luxurious room with tall windows overlooking a rainy metropolis. Shot with a 50mm lens at a side profile angle, soft tungsten light highlighting hands moving over keys. Capture detailed reflections in polished black piano surfaces, raindrops sliding down glass, and atmospheric warm/cool lighting contrast."
},
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);This model supports streaming requests. You can stream data directly to the model and get the result in real-time.
import { fal } from "@fal-ai/client";
const stream = await fal.stream("fal-ai/flux-2/lora", {
input: {
prompt: "Close shot a pianist plays in a luxurious room with tall windows overlooking a rainy metropolis. Shot with a 50mm lens at a side profile angle, soft tungsten light highlighting hands moving over keys. Capture detailed reflections in polished black piano surfaces, raindrops sliding down glass, and atmospheric warm/cool lighting contrast."
}
});
for await (const event of stream) {
console.log(event);
}
const result = await stream.done();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/flux-2/lora", {
input: {
prompt: "Close shot a pianist plays in a luxurious room with tall windows overlooking a rainy metropolis. Shot with a 50mm lens at a side profile angle, soft tungsten light highlighting hands moving over keys. Capture detailed reflections in polished black piano surfaces, raindrops sliding down glass, and atmospheric warm/cool lighting contrast."
},
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/flux-2/lora", {
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/flux-2/lora", {
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 an image from.
guidance_scale floatGuidance 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: 2.5
seed integerThe seed to use for the generation. If not provided, a random seed will be used.
num_inference_steps integerThe number of inference steps to perform. Default value: 28
The size of the image to generate. The width and height must be between 512 and 2048 pixels. Default value: landscape_4_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_images integerThe number of images to generate. Default value: 1
acceleration AccelerationEnumThe acceleration level to use for the image generation. Default value: "regular"
Possible enum values: none, regular, high
enable_prompt_expansion booleanIf set to true, the prompt will be expanded for better results.
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.
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: "png"
Possible enum values: jpeg, png, webp
List of LoRA weights to apply (maximum 3). Each LoRA can be a URL, HuggingFace repo ID, or local path.
{
"prompt": "Close shot a pianist plays in a luxurious room with tall windows overlooking a rainy metropolis. Shot with a 50mm lens at a side profile angle, soft tungsten light highlighting hands moving over keys. Capture detailed reflections in polished black piano surfaces, raindrops sliding down glass, and atmospheric warm/cool lighting contrast.",
"guidance_scale": 2.5,
"num_inference_steps": 28,
"image_size": "landscape_4_3",
"num_images": 1,
"acceleration": "regular",
"enable_safety_checker": true,
"output_format": "png",
"loras": []
}The generated images
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": "https://storage.googleapis.com/falserverless/example_outputs/flux2_dev_lora_t2i_output.png"
}
],
"prompt": ""
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
path string* requiredURL, HuggingFace repo ID (owner/repo), or local path to LoRA weights.
scale floatScale factor for LoRA application (0.0 to 4.0). Default value: 1
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
height integerThe height of the image