Hunyuan Image | Text to Image

fal-ai/hunyuan-image/v3/text-to-image

Leverage the state-of-the-art capabilities of Hunyuan Image 3.0 to generate visual content that effectively conveys the messaging of your written material.

Inference

Commercial use

Schema

LLMs

Playground API Examples

About

Generate Image V3

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/hunyuan-image/v3/text-to-image", {
  input: {
    prompt: "200mm telephoto through crowd gaps; subject laughing, candid; creamy background compression, color pop from a single bold garment, catchlight in eyes."
  },
  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/hunyuan-image/v3/text-to-image", {
  input: {
    prompt: "200mm telephoto through crowd gaps; subject laughing, candid; creamy background compression, color pop from a single bold garment, catchlight in eyes."
  },
  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/hunyuan-image/v3/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("fal-ai/hunyuan-image/v3/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

The text prompt for image-to-image.

negative_prompt string

The negative prompt to guide the image generation away from certain concepts. Default value: ""

image_size ImageSize | Enum

The desired size of the generated image. 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_images integer

The number of images to generate. Default value: 1

num_inference_steps integer

Number of denoising steps. Default value: 28

guidance_scale float

Controls how much the model adheres to the prompt. Higher values mean stricter adherence. Default value: 7.5

seed integer

Random seed for reproducible results. If None, a random seed is used.

enable_safety_checker boolean

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

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.

output_format OutputFormatEnum

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

Possible enum values: jpeg, png

enable_prompt_expansion boolean

Whether to enable prompt expansion. This will use a large language model to expand the prompt with additional details while maintaining the original meaning.

{
  "prompt": "200mm telephoto through crowd gaps; subject laughing, candid; creamy background compression, color pop from a single bold garment, catchlight in eyes.",
  "negative_prompt": "blurry, low quality, watermark, signature",
  "image_size": "square_hd",
  "num_images": 1,
  "num_inference_steps": 28,
  "guidance_scale": 7.5,
  "enable_safety_checker": true,
  "output_format": "png",
  "enable_prompt_expansion": true
}

Output#

images list<Image>* required

A list of the generated images.

seed integer* required

The base seed used for the generation process.

{
  "images": [
    {
      "content_type": "image/png",
      "url": "https://v3b.fal.media/files/b/kangaroo/uIKrZHT6LaGqgXoxtBSn7.png"
    }
  ]
}

Other types#

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

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.

Hunyuan Image 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#

ImageSize#

Image#