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Bitdance Text to Image

fal-ai/bitdance
Image generation with BitDance. Fast, high-resolution photorealistic images using an autoregressive LLM— for efficient, high-quality results.
Inference
Commercial use
Schema
LLMs
PlaygroundAPI

About

Generate

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/bitdance", {
  input: {
    prompt: "A close-up portrait of a cat wearing a tiny top hat, cinematic photography style"
  },
  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/bitdance", {
  input: {
    prompt: "A close-up portrait of a cat wearing a tiny top hat, cinematic photography style"
  },
  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/bitdance", {
  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/bitdance", {
  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

Text prompt for image generation.

image_size ImageSize | Enum

The size of the generated image. Will be snapped to the nearest supported resolution. Default value: square_hd

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 diffusion sampling steps per decoding step. Higher values (e.g. 50) improve quality at the cost of speed. Default value: 25

guidance_scale float

Classifier-free guidance scale. Higher values follow the prompt more closely. Default value: 7.5

seed integer

Random seed for reproducibility. The same seed and prompt will produce the same image.

num_images integer

Number of images to generate. Default value: 1

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: "jpeg"

Possible enum values: jpeg, png

sync_mode boolean

If true, the media will be returned as a data URI.

{
  "prompt": "A close-up portrait of a cat wearing a tiny top hat, cinematic photography style",
  "image_size": "square_hd",
  "num_inference_steps": 25,
  "guidance_scale": 7.5,
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "jpeg"
}

Output#

images list<Image>* required

The generated image files info.

seed integer* required

Seed of the generated image.

has_nsfw_concepts list<boolean>* required

Whether the generated images contain NSFW concepts.

prompt string* required

The prompt used for generating the image.

{
  "images": [
    {
      "height": 1024,
      "content_type": "image/jpeg",
      "url": "https://v3b.fal.media/files/b/0a8f4d70/JxZtUW5HcyjcZAEOSzJEl.jpg",
      "width": 1024
    }
  ],
  "prompt": "A close-up portrait of a cat wearing a tiny top hat, cinematic photography style"
}

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.

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512