Commercially safe, multi-reference image editing model. Follows natural language instructions alone or with up to 4 reference images, purpose-built for complex object and character combinations, virtual try-on, background replacement, style transfer, and more.

bria/fibo-edit-1.5/edit

Inference

Commercial use

Schema

Playground API Examples

bria/fibo-edit-1.5/edit

Schema

Fibo Edit 1.5 Image Editing Image to Image API Docs | fal

bria/fibo-edit-1.5/edit

Inference

Commercial use

Schema

Playground API Examples

About

Edit Open

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. Install the new package and update your imports — see client setup.

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("bria/fibo-edit-1.5/edit", {
  input: {},
  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 an environment where you cannot set environment variables, you can configure the API key manually on the client.

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("bria/fibo-edit-1.5/edit", {
  input: {},
  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("bria/fibo-edit-1.5/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("bria/fibo-edit-1.5/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);

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_urls list<string>

1-4 reference images (files or URLs). Order is significant: the instruction is resolved against the images in the order they are sent.

instruction string

Instruction for image editing.

aspect_ratio Enum

Output aspect ratio. Left unset, the output keeps the ratio of the first reference image. A chosen ratio applies only with two or more reference images; with a single reference the output keeps that image's ratio either way.

Possible enum values: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9

seed integer

Random seed for reproducibility. Default value: 5555

mask_url string

Mask (file or URL) marking the region to regenerate: white where the model should edit, black elsewhere. Single-reference requests only, and it must be the same size as that image. A masked edit comes back at the reference's own resolution.

sync_mode boolean

If true, returns the image directly in the response (increases latency).

structured_instruction StructuredInstruction

A pre-built structured prompt, used verbatim instead of having VGL build one when no instruction is sent. Accepts what a previous edit returned.

{
  "image_urls": [
    "https://v3b.fal.media/files/b/0aa69153/6d2UFjgrQCRM6BoWpXpZ3_126_1.jpg",
    "https://v3b.fal.media/files/b/0aa69153/Gy-fjFofCbQP9w3lsfc2e_126_2.jpg"
  ],
  "instruction": "Uncross her arms and place the serum bottle in her right hand raised beside her face, label toward the camera.",
  "seed": 5555
}

Output#

image Image* required

The edited image, in the source aspect ratio unless aspect_ratio was set.

images list<Image>

Single-element list holding the same image, kept for callers of the earlier Fibo Edit endpoint.

structured_instruction Structured Instruction* required

The structured instruction the model ran, expanded from the built-in instruction plus anything passed in instruction. Returned so you can see how the brief was interpreted.

{
  "image": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019,
    "width": 1024,
    "height": 1024
  },
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/0aa6910f/ie5dAn55wDh7Y1adCFGyE_85a45d82c6d141c2a28d92367596dfac.png"
    }
  ]
}

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.

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

StructuredInstruction#

short_description string

A short description of the image to be generated.

objects list<PromptObject>

A list of objects in the image to be generated, along with their attributes and relationships to other objects in the image.

background_setting string

The background setting of the image to be generated.

lighting Lighting

The lighting of the image to be generated.

aesthetics Aesthetics

The aesthetics of the image to be generated.

photographic_characteristics PhotographicCharacteristics

The photographic characteristics of the image to be generated.

style_medium string

The style medium of the image to be generated.

text_render list<void>

A list of text to be rendered in the image.

context string

The context of the image to be generated.

artistic_style string

The artistic style of the image to be generated.

edit_instruction string

The edit instruction for the image.

PromptObject#

description string

A description of the object to be generated.

location string

The location of the object in the image.

relationship string* required

The relationship of the object to other objects in the image.

relative_size string

The relative size of the object in the image.

shape_and_color string

The shape and color of the object.

texture string

The texture of the object.

appearance_details string

The appearance details of the object.

number_of_objects integer

The number of objects in the image.

pose string

The pose of the object in the image.

expression string

The expression of the object in the image.

clothing string

The clothing of the object in the image.

action string

The action of the object in the image.

gender string

The gender of the object in the image.

skin_tone_and_texture string

The skin tone and texture of the object in the image.

orientation string

The orientation of the object in the image.

Lighting#

conditions string

The conditions of the lighting in the image to be generated.

direction string

The direction of the lighting in the image to be generated.

shadows string

The shadows in the image to be generated.

PhotographicCharacteristics#

depth_of_field string

The depth of field in the image to be generated.

focus string

The focus in the image to be generated.

camera_angle string

The angle of the camera in the image to be generated.

lens_focal_length string

The focal length of the lens in the image to be generated.

Aesthetics#

composition string

The composition of the image to be generated.

color_scheme string

The color scheme of the image to be generated.

mood_atmosphere string

The mood and atmosphere of the image to be generated.

aesthetic_score string

The aesthetic score of the image to be generated.

preference_score string

The preference score of the image to be generated.

Related Models

About

Edit Open

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. Install the new package and update your imports — see client setup.

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("bria/fibo-edit-1.5/edit", {
  input: {},
  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 an environment where you cannot set environment variables, you can configure the API key manually on the client.

import { fal } from "@fal-ai/client";

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

Protect your API Key

3. Queue#

Long-running requests

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("bria/fibo-edit-1.5/edit", {
  input: {},
  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("bria/fibo-edit-1.5/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("bria/fibo-edit-1.5/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)#

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_urls list<string>

1-4 reference images (files or URLs). Order is significant: the instruction is resolved against the images in the order they are sent.

instruction string

Instruction for image editing.

aspect_ratio Enum

Possible enum values: 1:1, 2:3, 3:2, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9

seed integer

Random seed for reproducibility. Default value: 5555

mask_url string

sync_mode boolean

If true, returns the image directly in the response (increases latency).

structured_instruction StructuredInstruction

A pre-built structured prompt, used verbatim instead of having VGL build one when no instruction is sent. Accepts what a previous edit returned.

{
  "image_urls": [
    "https://v3b.fal.media/files/b/0aa69153/6d2UFjgrQCRM6BoWpXpZ3_126_1.jpg",
    "https://v3b.fal.media/files/b/0aa69153/Gy-fjFofCbQP9w3lsfc2e_126_2.jpg"
  ],
  "instruction": "Uncross her arms and place the serum bottle in her right hand raised beside her face, label toward the camera.",
  "seed": 5555
}

Output#

image Image* required

The edited image, in the source aspect ratio unless aspect_ratio was set.

images list<Image>

Single-element list holding the same image, kept for callers of the earlier Fibo Edit endpoint.

structured_instruction Structured Instruction* required

The structured instruction the model ran, expanded from the built-in instruction plus anything passed in instruction. Returned so you can see how the brief was interpreted.

{
  "image": {
    "url": "",
    "content_type": "image/png",
    "file_name": "z9RV14K95DvU.png",
    "file_size": 4404019,
    "width": 1024,
    "height": 1024
  },
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/0aa6910f/ie5dAn55wDh7Y1adCFGyE_85a45d82c6d141c2a28d92367596dfac.png"
    }
  ]
}

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.

width integer

The width of the image in pixels.

height integer

The height of the image in pixels.

StructuredInstruction#

short_description string

A short description of the image to be generated.

objects list<PromptObject>

A list of objects in the image to be generated, along with their attributes and relationships to other objects in the image.

background_setting string

The background setting of the image to be generated.

lighting Lighting

The lighting of the image to be generated.

aesthetics Aesthetics

The aesthetics of the image to be generated.

photographic_characteristics PhotographicCharacteristics

The photographic characteristics of the image to be generated.

style_medium string

The style medium of the image to be generated.

text_render list<void>

A list of text to be rendered in the image.

context string

The context of the image to be generated.

artistic_style string

The artistic style of the image to be generated.

edit_instruction string

The edit instruction for the image.

PromptObject#

description string

A description of the object to be generated.

location string

The location of the object in the image.

relationship string* required

The relationship of the object to other objects in the image.

relative_size string

The relative size of the object in the image.

shape_and_color string

The shape and color of the object.

texture string

The texture of the object.

appearance_details string

The appearance details of the object.

number_of_objects integer

The number of objects in the image.

pose string

The pose of the object in the image.

expression string

The expression of the object in the image.

clothing string

The clothing of the object in the image.

action string

The action of the object in the image.

gender string

The gender of the object in the image.

skin_tone_and_texture string

The skin tone and texture of the object in the image.

orientation string

The orientation of the object in the image.

Lighting#

conditions string

The conditions of the lighting in the image to be generated.

direction string

The direction of the lighting in the image to be generated.

shadows string

The shadows in the image to be generated.

PhotographicCharacteristics#

depth_of_field string

The depth of field in the image to be generated.

focus string

The focus in the image to be generated.

camera_angle string

The angle of the camera in the image to be generated.

lens_focal_length string

The focal length of the lens in the image to be generated.

Aesthetics#

composition string

The composition of the image to be generated.

color_scheme string

The color scheme of the image to be generated.

mood_atmosphere string

The mood and atmosphere of the image to be generated.

aesthetic_score string

The aesthetic score of the image to be generated.

preference_score string

The preference score of the image to be generated.

bria/fibo-edit-1.5/edit

Table of contents

Table of contents

bria/fibo-edit-1.5/edit

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#

StructuredInstruction#

PromptObject#

Lighting#

PhotographicCharacteristics#

Aesthetics#

Related Models

Table of contents

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#

StructuredInstruction#

PromptObject#

Lighting#

PhotographicCharacteristics#

Aesthetics#

Related Models