Flow-Edit | Text to Image

fal-ai/flowedit

The model provides you high quality image editing capabilities.

Inference

Commercial use

Schema

Playground API

About

Generate Image

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/flowedit", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/FlowEdit/lighthouse.png",
    source_prompt: "The image features a tall white lighthouse standing prominently
        on a hill, with a beautiful blue sky in the background. The lighthouse is illuminated
        by a bright light, making it a prominent landmark in the scene.",
    target_prompt: "The image features Big ben clock tower standing prominently
        on a hill, with a beautiful blue sky in the background. The Big ben clock tower is illuminated
        by a bright light, making it a prominent landmark in the scene."
  },
  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/flowedit", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/model_tests/FlowEdit/lighthouse.png",
    source_prompt: "The image features a tall white lighthouse standing prominently
        on a hill, with a beautiful blue sky in the background. The lighthouse is illuminated
        by a bright light, making it a prominent landmark in the scene.",
    target_prompt: "The image features Big ben clock tower standing prominently
        on a hill, with a beautiful blue sky in the background. The Big ben clock tower is illuminated
        by a bright light, making it a prominent landmark in the scene."
  },
  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/flowedit", {
  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/flowedit", {
  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 image to be used for relighting

source_prompt string* required

Prompt of the image to be used.

target_prompt string* required

Prompt of the image to be made.

seed integer

Random seed for reproducible generation. If set none, a random seed will be used.

num_inference_steps integer

Steps for which the model should run. Default value: 28

src_guidance_scale integer

Guidance scale for the source. Default value: 1.5

tar_guidance_scale integer

Guidance scale for target. Default value: 5.5

n_avg integer

Average step count Default value: 1

n_max integer

Control the strength of the edit Default value: 23

n_min integer

Minimum step for improved style edits

{
  "image_url": "https://storage.googleapis.com/falserverless/model_tests/FlowEdit/lighthouse.png",
  "source_prompt": "The image features a tall white lighthouse standing prominently\n      on a hill, with a beautiful blue sky in the background. The lighthouse is illuminated\n      by a bright light, making it a prominent landmark in the scene.",
  "target_prompt": "The image features Big ben clock tower standing prominently\n      on a hill, with a beautiful blue sky in the background. The Big ben clock tower is illuminated\n      by a bright light, making it a prominent landmark in the scene.",
  "num_inference_steps": 28,
  "src_guidance_scale": 1.5,
  "tar_guidance_scale": 5.5,
  "n_avg": 1,
  "n_max": 23
}

Output#

image Image* required

The generated image file info.

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.

{
  "image": {
    "file_size": 423052,
    "height": 1024,
    "file_name": "36d3ca4791a647678b2ff01a35c87f5a.png",
    "content_type": "image/png",
    "url": "https://storage.googleapis.com/falserverless/model_tests/FlowEdit/aa5c3d028ad04800a54f70f928198d91.png",
    "width": 1024
  }
}

Other types#

Image#

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 in pixels.

height integer

The height of the image in pixels.

Flow-Edit Text to Image

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#