fal-ai/onereward

OneReward is a finetuned version of Flux 1.0 Fill with intelligent editing capabilities.

Inference

Commercial use

Schema

LLMs

Playground API

About

Edit images using OneReward: mask-guided inpainting, outpainting, object removal, and text rendering.

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/onereward", {
  input: {
    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"
  },
  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);

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"
});

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#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

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/onereward", {
  input: {
    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"
  },
  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/onereward", {
  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/onereward", {
  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* required

URL of the source image to edit.

mask_url string* required

URL of the mask image. White pixels indicate the area to fill or modify; black pixels preserve the original content.

prompt string

Text description of what to generate in the masked area.

negative_prompt string

Text describing what to avoid in the generated output. Default value: "nsfw"

guidance_scale float

Guidance scale for the base diffusion process. The model uses true_cfg for classifier-free guidance; this controls the distillation guidance. Default value: 1

true_cfg float

True classifier-free guidance scale. Controls how strongly the model follows the prompt. Values above 1.0 enable CFG. Default value: 4

num_inference_steps integer

Number of denoising steps. More steps generally produce higher quality results. Default value: 28

acceleration AccelerationEnum

Acceleration level for image generation. Default value: "regular"

Possible enum values: none, regular, high

num_images integer

Number of images to generate. Default value: 1

output_format OutputFormatEnum

Format of the output image. Default value: "jpeg"

Possible enum values: jpeg, png

seed integer

Random seed for reproducibility. If None, a random seed is used.

sync_mode boolean

If True, returns the image as a data URI instead of uploading to CDN. The image will not be available in the request history.

enable_safety_checker boolean

If True, runs a safety checker on the output and filters NSFW content. Default value: true

{
  "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",
  "prompt": "A knight holding a plaque with the words 'OneReward' written on it",
  "negative_prompt": "nsfw",
  "guidance_scale": 1,
  "true_cfg": 4,
  "num_inference_steps": 28,
  "acceleration": "regular",
  "num_images": 1,
  "output_format": "jpeg",
  "enable_safety_checker": true
}

Output#

images list<Image>* required

The edited image files.

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": [
    {
      "height": 1024,
      "content_type": "image/jpeg",
      "url": "https://v3b.fal.media/files/b/0a90fdd0/wrnlNlrLJxbLDKsW2W2jn.jpg",
      "width": 1024
    }
  ],
  "prompt": ""
}

Other types#

Image#

url string* required

width integer* required

height integer* required

content_type string

Default value: "image/jpeg"

fal-ai/onereward

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

Image#