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fal-ai/nucleus-image

Nucleus-Image is a text-to-image generation model built on a sparse mixture-of-experts (MoE) diffusion transformer architecture.
Inference
Commercial use
Schema
LLMs
PlaygroundAPIExamples

Table of contents

About

Text To 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

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/nucleus-image", {
  input: {
    prompt: "A weathered lighthouse on a rocky coastline at golden hour, waves crashing below, dramatic amber clouds, cinematic realism"
  },
  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"
});

3. Queue#

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/nucleus-image", {
  input: {
    prompt: "A weathered lighthouse on a rocky coastline at golden hour, waves crashing below, dramatic amber clouds, cinematic realism"
  },
  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/nucleus-image", {
  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/nucleus-image", {
  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);

Read more about file handling in our file upload guide.

5. Schema#

Input#

prompt string* required

The prompt to use for generating the image.

negative_prompt string

The negative prompt to use for generation. Default value: ""

aspect_ratio AspectRatioEnum

The output aspect ratio. Nucleus-Image supports a fixed set of aspect-ratio presets. Default value: "1:1"

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

num_inference_steps integer

The number of inference steps to perform. Default value: 50

guidance_scale float

The classifier-free guidance scale. Default value: 8

seed integer

Seed for reproducible generation.

num_images integer

The number of images to generate. Default value: 1

sync_mode boolean

If True, return media as data URIs instead of persisted CDN files.

enable_safety_checker boolean

If set to true, the safety checker will be enabled. Default value: true

output_format OutputFormatEnum

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

Possible enum values: jpeg, png

{
  "prompt": "A weathered lighthouse on a rocky coastline at golden hour, waves crashing below, dramatic amber clouds, cinematic realism",
  "negative_prompt": "blurry, low quality, distorted text",
  "aspect_ratio": "1:1",
  "num_inference_steps": 50,
  "guidance_scale": 8,
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "png"
}

Output#

images list<Image>* required

The generated image files info.

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": [
    {
      "url": "",
      "content_type": "image/jpeg"
    }
  ],
  "prompt": ""
}

Other types#

Image#

url string* required
width integer* required
height integer* required
content_type string

Default value: "image/jpeg"