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Flux 2 Text to Image

fal-ai/flux-2/lora/edit
Image-to-image editing with LoRA support for FLUX.2 [dev] from Black Forest Labs. Specialized style transfer and domain-specific modifications.
Inference
Commercial use
Streaming
Schema

About

Image-to-image editing with LoRA support for FLUX.2 [dev] from Black Forest Labs. Specialized style transfer and domain-specific modifications.

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

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/flux-2/lora/edit", {
  input: {
    prompt: "Make this donut realistic",
    image_urls: ["https://storage.googleapis.com/falserverless/example_inputs/flux2_dev_lora_edit_input.png"]
  },
  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);

Streaming#

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/edit", {
  input: {
    prompt: "Make this donut realistic",
    image_urls: ["https://storage.googleapis.com/falserverless/example_inputs/flux2_dev_lora_edit_input.png"]
  }
});

for await (const event of stream) {
  console.log(event);
}

const result = await stream.done();

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#

In case your app is running in an environment where you cannot set environment variables, you can set the API Key manually as a client configuration.
import { fal } from "@fal-ai/client";

fal.config({
  credentials: "YOUR_FAL_KEY"
});

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/flux-2/lora/edit", {
  input: {
    prompt: "Make this donut realistic",
    image_urls: ["https://storage.googleapis.com/falserverless/example_inputs/flux2_dev_lora_edit_input.png"]
  },
  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/flux-2/lora/edit", {
  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/flux-2/lora/edit", {
  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);

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to generate an image from.

guidance_scale float

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: 2.5

seed integer

The seed to use for the generation. If not provided, a random seed will be used.

num_inference_steps integer

The number of inference steps to perform. Default value: 28

image_size ImageSize | Enum

The size of the image to generate. The width and height must be between 512 and 2048 pixels.

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 integer

The number of images to generate. Default value: 1

acceleration AccelerationEnum

The acceleration level to use for the image generation. Default value: "regular"

Possible enum values: none, regular, high

enable_prompt_expansion boolean

If set to true, the prompt will be expanded for better results.

sync_mode boolean

If 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 boolean

If set to true, the safety checker will be enabled. Default value: true

output_format OutputFormatEnum

The format of the generated image. Default value: "png"

Possible enum values: jpeg, png, webp

image_urls list<string>* required

The URsL of the images for editing. A maximum of 3 images are allowed, if more are provided, only the first 3 will be used.

loras list<LoRAInput>

List of LoRA weights to apply (maximum 3). Each LoRA can be a URL, HuggingFace repo ID, or local path.

{
  "prompt": "Make this donut realistic",
  "guidance_scale": 2.5,
  "num_inference_steps": 28,
  "image_size": {
    "height": 1152,
    "width": 2016
  },
  "num_images": 1,
  "acceleration": "regular",
  "enable_safety_checker": true,
  "output_format": "png",
  "image_urls": [
    "https://storage.googleapis.com/falserverless/example_inputs/flux2_dev_lora_edit_input.png"
  ],
  "loras": []
}

Output#

images list<ImageFile>* required

The edited images

timings Timings* required
seed integer* required

Seed 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.

has_nsfw_concepts list<boolean>* required

Whether the generated images contain NSFW concepts.

prompt string* required

The prompt used for generating the image.

{
  "images": [
    {
      "url": "https://storage.googleapis.com/falserverless/example_outputs/flux2_dev_lora_edit_output.png"
    }
  ],
  "prompt": ""
}

Other types#

ImageFile#

url string* required

The URL where the file can be downloaded from.

content_type string

The mime type of the file.

file_name string

The name of the file. It will be auto-generated if not provided.

file_size integer

The size of the file in bytes.

file_data string

File data

width integer

The width of the image

height integer

The height of the image

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

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