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fal-ai/ernie-image/turbo

High-quality text-to-image model by Baidu. Supports English, Chinese, and Japanese prompts with built-in prompt expansion.
Inference
Commercial use
Schema
LLMs
PlaygroundAPIExamples

Table of contents

About

Generate Turbo

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/ernie-image/turbo", {
  input: {
    prompt: "A serene mountain landscape at sunset with golden light"
  },
  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/ernie-image/turbo", {
  input: {
    prompt: "A serene mountain landscape at sunset with golden light"
  },
  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/ernie-image/turbo", {
  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/ernie-image/turbo", {
  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. Supports English, Chinese, and Japanese.

negative_prompt string

Negative prompt to guide what should not be in the image. Default value: ""

image_size ImageSize | Enum

The 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, square_uhd, portrait_3_2, landscape_3_2, portrait_hd, landscape_hd

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. Turbo model is optimized for 8 steps. Default value: 8

guidance_scale float

Classifier-free guidance scale. Default value: 1

seed integer

Random seed for reproducibility.

num_images integer

Number of images to generate. Default value: 1

enable_prompt_expansion boolean

If True, the prompt will be enhanced using an LLM for more detailed results. Default value: true

enable_safety_checker boolean

Enable NSFW safety checking on the generated images. Default value: true

output_format OutputFormatEnum

Output image format. Default value: "jpeg"

Possible enum values: jpeg, png

sync_mode boolean

If True, the image will be returned as a data URI instead of a URL.

{
  "prompt": "A serene mountain landscape at sunset with golden light",
  "image_size": "square_hd",
  "num_inference_steps": 8,
  "guidance_scale": 1,
  "num_images": 1,
  "enable_prompt_expansion": true,
  "enable_safety_checker": true,
  "output_format": "jpeg"
}

Output#

images list<Image>* required

List of generated images.

seed integer* required

Seed used for generation.

prompt string* required

The prompt used for generating the image.

timings Timings* required

Timing information.

{
  "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"

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

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