imagineart/imagineart-2.0-preview/text-to-image

ImagineArt 2.0 is ImagineArt's latest state-of-the-art visual reasoning text-to-image model, generating high-fidelity, professional-grade visuals with lifelike realism, cinematic effects, and strong aesthetic quality.

Inference

Commercial use

Partner

Schema

LLMs

Playground API

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

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("imagineart/imagineart-2.0-preview/text-to-image", {
  input: {
    prompt: "Photorealistic cinematic portrait of a stressed young woman with dark skin and long brown dreadlocks styled in a messy high bun, wearing black-rimmed glasses and a peach-colored collared shirt. She is sitting at a desk, sipping coffee from a white ceramic mug held in her right hand, with a focused and slightly overwhelmed expression while looking at a silver laptop in front of her.

  Her face, hair, glasses, and entire upper body are completely covered with dozens of colorful sticky notes in yellow, pink, blue, orange, red, and green, many with no written text. Sticky notes are stuck to her forehead, cheeks, dreadlocks, and all over her shirt.

  The scene is set in a modern office with soft cool blue-toned natural lighting coming from the side. Blurred green plants are visible in the background and \"ImagineArt\" is written on the Wall. On the desk in the foreground there is another white mug, scattered papers, and more sticky notes.

  Highly detailed, sharp focus on the woman, shallow depth of field, realistic skin texture, natural fabric folds, cinematic lighting, moody atmosphere capturing information overload and multitasking, 8k resolution, photorealistic."
  },
  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("imagineart/imagineart-2.0-preview/text-to-image", {
  input: {
    prompt: "Photorealistic cinematic portrait of a stressed young woman with dark skin and long brown dreadlocks styled in a messy high bun, wearing black-rimmed glasses and a peach-colored collared shirt. She is sitting at a desk, sipping coffee from a white ceramic mug held in her right hand, with a focused and slightly overwhelmed expression while looking at a silver laptop in front of her.

  Her face, hair, glasses, and entire upper body are completely covered with dozens of colorful sticky notes in yellow, pink, blue, orange, red, and green, many with no written text. Sticky notes are stuck to her forehead, cheeks, dreadlocks, and all over her shirt.

  The scene is set in a modern office with soft cool blue-toned natural lighting coming from the side. Blurred green plants are visible in the background and \"ImagineArt\" is written on the Wall. On the desk in the foreground there is another white mug, scattered papers, and more sticky notes.

  Highly detailed, sharp focus on the woman, shallow depth of field, realistic skin texture, natural fabric folds, cinematic lighting, moody atmosphere capturing information overload and multitasking, 8k resolution, photorealistic."
  },
  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("imagineart/imagineart-2.0-preview/text-to-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("imagineart/imagineart-2.0-preview/text-to-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);

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 describing the desired image

aspect_ratio AspectRatioEnum

Image aspect ratio: 1:1, 3:1, 1:3, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9, 4:5, 5:4, 4:1, 1:4 Default value: "1:1"

Possible enum values: 1:1, 16:9, 9:16, 4:3, 3:4, 3:1, 1:3, 3:2, 2:3, 21:9, 4:5, 5:4, 4:1, 1:4

resolution ResolutionEnum

Output resolution: '1K' targets ~1024px and will be faster. '2K' targets ~2048px image size and will be slower but with higher quality. Default value: "2K"

Possible enum values: 1K, 2K

seed integer

Default is random (0 and -1 are treated as random)

reasoning ReasoningEnum

Visual Understanding Level: low (default) or high. High reasoning takes more time but generates better images. Default value: "low"

Possible enum values: high, low

{
  "prompt": "Photorealistic cinematic portrait of a stressed young woman with dark skin and long brown dreadlocks styled in a messy high bun, wearing black-rimmed glasses and a peach-colored collared shirt. She is sitting at a desk, sipping coffee from a white ceramic mug held in her right hand, with a focused and slightly overwhelmed expression while looking at a silver laptop in front of her.\n\nHer face, hair, glasses, and entire upper body are completely covered with dozens of colorful sticky notes in yellow, pink, blue, orange, red, and green, many with no written text. Sticky notes are stuck to her forehead, cheeks, dreadlocks, and all over her shirt.\n\nThe scene is set in a modern office with soft cool blue-toned natural lighting coming from the side. Blurred green plants are visible in the background and \"ImagineArt\" is written on the Wall. On the desk in the foreground there is another white mug, scattered papers, and more sticky notes.\n\nHighly detailed, sharp focus on the woman, shallow depth of field, realistic skin texture, natural fabric folds, cinematic lighting, moody atmosphere capturing information overload and multitasking, 8k resolution, photorealistic.",
  "aspect_ratio": "1:1",
  "resolution": "2K",
  "seed": 0,
  "reasoning": "low"
}

Output#

images list<Image>* required

Generated image

{
  "images": [
    {
      "height": 2048,
      "content_type": "image/png",
      "width": 2048,
      "url": "https://v3b.fal.media/files/b/0a9513b1/to-rcKHMkC7e9jQFN7tZE_U8VLyc50wRU6V_UbIh0Hi_generated_ImagineArt_2_0.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.

imagineart/imagineart-2.0-preview/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#