FLUX.1 Fill [pro] API, next generation inpainting/outpainting model.
All usages of this model must comply with FLUX.1 PRO Terms of Service.
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-pro/v1/fill-finetuned", {
input: {
prompt: "A knight in shining armour holding a greatshield with \"FAL\" on it",
image_url: "https://storage.googleapis.com/falserverless/flux-lora/example-images/knight.jpeg",
mask_url: "https://storage.googleapis.com/falserverless/flux-lora/example-images/mask_knight.jpeg",
finetune_id: ""
},
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/flux-pro/v1/fill-finetuned", {
input: {
prompt: "A knight in shining armour holding a greatshield with \"FAL\" on it",
image_url: "https://storage.googleapis.com/falserverless/flux-lora/example-images/knight.jpeg",
mask_url: "https://storage.googleapis.com/falserverless/flux-lora/example-images/mask_knight.jpeg",
finetune_id: ""
},
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-pro/v1/fill-finetuned", {
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-pro/v1/fill-finetuned", {
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 fill the masked part of the image.
seed integerThe same seed and the same prompt given to the same version of the model will output the same image every time.
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
output_format OutputFormatEnumThe format of the generated image. Default value: "jpeg"
Possible enum values: jpeg, png
safety_tolerance SafetyToleranceEnumThe safety tolerance level for the generated image. 1 being the most strict and 5 being the most permissive. Default value: "2"
Possible enum values: 1, 2, 3, 4, 5, 6
Note: This property is only available through API calls.
enhance_prompt booleanWhether to enhance the prompt for better results.
image_url string* requiredThe image URL to generate an image from. Needs to match the dimensions of the mask.
mask_url string* requiredThe mask URL to inpaint the image. Needs to match the dimensions of the input image.
finetune_id string* requiredReferences your specific model
finetune_strength float* requiredControls finetune influence. Increase this value if your target concept isn't showing up strongly enough. The optimal setting depends on your finetune and prompt
{
"prompt": "A knight in shining armour holding a greatshield with \"FAL\" on it",
"num_images": 1,
"output_format": "jpeg",
"safety_tolerance": "2",
"image_url": "https://storage.googleapis.com/falserverless/flux-lora/example-images/knight.jpeg",
"mask_url": "https://storage.googleapis.com/falserverless/flux-lora/example-images/mask_knight.jpeg",
"finetune_id": ""
}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": ""
}url string* requiredwidth integer* requiredheight integer* requiredcontent_type stringDefault value: "image/jpeg"