fal-ai/hidream-o1-image/edit

Unified image generation with HiDream-O1-Image. Create, edit, and personalize high-resolution images up to 2K—single native model handles text-to-image, editing, and custom subjects without external components.

Inference

Commercial use

Schema

LLMs

Playground API

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Edit

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/hidream-o1-image/edit", {
  input: {
    prompt: "A cinematic product photo of a ceramic mug on a marble counter with the words \"fal loves HiDream\" printed on the mug.",
    reference_image_urls: ["https://storage.googleapis.com/falserverless/model_tests/hidream/woman.png"]
  },
  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/hidream-o1-image/edit", {
  input: {
    prompt: "A cinematic product photo of a ceramic mug on a marble counter with the words \"fal loves HiDream\" printed on the mug.",
    reference_image_urls: ["https://storage.googleapis.com/falserverless/model_tests/hidream/woman.png"]
  },
  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/hidream-o1-image/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("fal-ai/hidream-o1-image/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#

prompt string* required

Text prompt for image generation, editing, or subject-driven personalization.

reference_image_urls list<string>* required

Reference images for image editing or subject-driven personalization.

image_size ImageSize | Enum

Requested output image size. The model snaps this to the closest supported resolution up to about 2048x2048 pixels.

Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9

Note: For custom image sizes, you can pass the width and height as an object:

"image_size": {
  "width": 1280,
  "height": 720
}

num_inference_steps integer

Number of denoising steps. Default value: 50

guidance_scale float

Classifier-free guidance scale. The full model uses 5.0 by default. Default value: 5

seed integer

Random seed for reproducible generation.

num_images integer

Number of images to generate. Default value: 1

output_format OutputFormatEnum

The format of the generated image. Default value: "png"

Possible enum values: jpeg, png, webp

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

enable_safety_checker boolean

Enable the safety checker on generated images. Default value: true

keep_original_aspect boolean

When exactly one reference image is provided, preserve its aspect ratio for the output image.

{
  "prompt": "A cinematic product photo of a ceramic mug on a marble counter with the words \"fal loves HiDream\" printed on the mug.",
  "reference_image_urls": [
    "https://storage.googleapis.com/falserverless/model_tests/hidream/woman.png"
  ],
  "image_size": {
    "width": 2048,
    "height": 2048
  },
  "num_inference_steps": 50,
  "guidance_scale": 5,
  "num_images": 1,
  "output_format": "png",
  "enable_safety_checker": true
}

Output#

images list<ImageFile>* required

Generated images.

seed integer* required

The seed used for generation.

has_nsfw_concepts list<boolean>* required

Whether each generated image was flagged by the safety checker.

prompt string* required

The prompt used for generation.

timings Timings* required

Generation timings.

{
  "images": [
    {
      "url": "",
      "content_type": "image/png",
      "file_name": "z9RV14K95DvU.png",
      "file_size": 4404019
    }
  ],
  "prompt": ""
}

Other types#

ImageFile#

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

height integer

The height of the image

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

fal-ai/hidream-o1-image/edit

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#

ImageFile#

ImageSize#