Flux Kontext Lora Image to Image
About
FLUX.1 Kontext [dev] -- Frontier image editing model.
Kontext makes editing images easy! Specify what you want to change and Kontext will follow. It is capable of understanding the context of the image, making it easier to edit them without having to describe in details what you want to do.
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
Migrate to @fal-ai/client
The @fal-ai/serverless-client
package has been deprecated in favor of @fal-ai/client
. Please check the migration guide for more information.
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-kontext-lora", {
input: {
image_url: "https://storage.googleapis.com/falserverless/example_inputs/kontext_example_input.webp",
prompt: "change the setting to a day time, add a lot of people walking the sidewalk while maintaining the same style of the painting"
},
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-kontext-lora", {
input: {
image_url: "https://storage.googleapis.com/falserverless/example_inputs/kontext_example_input.webp",
prompt: "change the setting to a day time, add a lot of people walking the sidewalk while maintaining the same style of the painting"
}
});
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#
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});
Protect your API 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.
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-kontext-lora", {
input: {
image_url: "https://storage.googleapis.com/falserverless/example_inputs/kontext_example_input.webp",
prompt: "change the setting to a day time, add a lot of people walking the sidewalk while maintaining the same style of the painting"
},
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-kontext-lora", {
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-kontext-lora", {
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);
Auto uploads
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.
5. Schema#
Input#
image_url
string
* requiredThe URL of the image to edit.
prompt
string
* requiredThe prompt to edit the image.
num_inference_steps
integer
The number of inference steps to perform. Default value: 30
seed
integer
The same seed and the same prompt given to the same version of the model will output the same image every time.
guidance_scale
float
The 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: 2.5
sync_mode
boolean
If set to true, the function will wait for the image to be generated and uploaded before returning the response. This will increase the latency of the function but it allows you to get the image directly in the response without going through the CDN.
num_images
integer
The number of images to generate. Default value: 1
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
The LoRAs to use for the image generation. You can use any number of LoRAs and they will be merged together to generate the final image.
acceleration
AccelerationEnum
The speed of the generation. The higher the speed, the faster the generation. Default value: "none"
Possible enum values: none, regular, high
resolution_mode
ResolutionModeEnum
Determines how the output resolution is set for image editing.
auto
: The model selects an optimal resolution from a predefined set that best matches the input image's aspect ratio. This is the recommended setting for most use cases as it's what the model was trained on.match_input
: The model will attempt to use the same resolution as the input image. The resolution will be adjusted to be compatible with the model's requirements (e.g. dimensions must be multiples of 16 and within supported limits). Apart from these, a few aspect ratios are also supported. Default value:"match_input"
Possible enum values: auto, match_input, 1:1, 16:9, 21:9, 3:2, 2:3, 4:5, 5:4, 3:4, 4:3, 9:16, 9:21
{
"image_url": "https://storage.googleapis.com/falserverless/example_inputs/kontext_example_input.webp",
"prompt": "change the setting to a day time, add a lot of people walking the sidewalk while maintaining the same style of the painting",
"num_inference_steps": 30,
"guidance_scale": 2.5,
"num_images": 1,
"enable_safety_checker": true,
"output_format": "png",
"acceleration": "none",
"resolution_mode": "match_input"
}
Output#
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": [
{
"height": 768,
"content_type": "image/jpeg",
"url": "https://storage.googleapis.com/falserverless/example_outputs/kontext_example_output.jpeg",
"width": 1024
}
],
"prompt": ""
}
Other types#
LoraWeight#
path
string
* requiredURL or the path to the LoRA weights.
scale
float
The scale of the LoRA weight. This is used to scale the LoRA weight
before merging it with the base model. Default value: 1
Image#
url
string
* requiredwidth
integer
* requiredheight
integer
* requiredcontent_type
string
Default value: "image/jpeg"
ImageSize#
width
integer
The width of the generated image. Default value: 512
height
integer
The height of the generated image. Default value: 512