fal-ai/telestyle-v2

Restyle any image with TeleStyle v2 — provide an original image and a styling reference, and the model re-renders the original in the reference's visual style while preserving its content and composition.

Inference

Commercial use

Schema

LLMs

Playground API Examples

1. Calling the API

2. Authentication

API Key

3. Queue

4. Files

5. Schema

About

Restyle a content image using a style reference image with the TeleStyleV2 workflow on top of Qwen-Image-Edit-2509. The prompt is derived automatically from both images by a vision-language model — no prompt input is required.

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/telestyle-v2", {
  input: {
    content_image_url: "https://v3.fal.media/files/monkey/i3saq4bAPXSIl08nZtq9P_ec535747aefc4e31943136a6d8587075.png",
    style_image_url: "https://v3.fal.media/files/penguin/BCOZp6teRhSQFuOXpbBOa_da8ef9b4982347a2a62a516b737d4f21.png"
  },
  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/telestyle-v2", {
  input: {
    content_image_url: "https://v3.fal.media/files/monkey/i3saq4bAPXSIl08nZtq9P_ec535747aefc4e31943136a6d8587075.png",
    style_image_url: "https://v3.fal.media/files/penguin/BCOZp6teRhSQFuOXpbBOa_da8ef9b4982347a2a62a516b737d4f21.png"
  },
  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/telestyle-v2", {
  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/telestyle-v2", {
  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#

content_image_url string* required

URL of the content image — the image whose subject and structure are preserved while the style is applied.

style_image_url string* required

URL of the style reference image — the artistic style, material, lighting and color of this image are transferred onto the content image.

lora_scale float

Strength of the TeleStyleV2 style adapter. 1.0 matches the reference implementation; lower values apply the style more subtly. Default value: 1

use_lightning_lora boolean

If true, use the Lightning LoRA in addition to the default LoRA. Default value: true

lightning_lora_scale float

Strength of the Lightning LoRA. 1.0 matches the reference implementation; lower values apply the style more subtly. Default value: 1

use_content_description boolean

If true, describe the content image with a VLM and add the description to the prompt. Default value: true

use_style_description boolean

If true, describe the style image with a VLM and add the description to the prompt. Default value: true

image_size ImageSize | Enum

The size of the generated image. If not provided, the size of the content image is used.

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
}

negative_prompt string

The negative prompt for the generation. Default value: ""

num_inference_steps integer

The number of inference steps to perform. Default value: 4

guidance_scale float

The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt. Default value: 1

acceleration AccelerationEnum

Acceleration level for image generation. 'none' (the default) honors the requested num_inference_steps, so the default 4-step Lightning configuration runs in 4 steps. 'regular' engages the downstream accelerated path, which runs a fixed 10 steps regardless of num_inference_steps. Default value: "none"

Possible enum values: none, regular

num_images integer

The number of images to generate. Default value: 1

seed integer

The same seed and the same inputs given to the same version of the model will output the same image every time.

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.

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

{
  "content_image_url": "https://v3.fal.media/files/monkey/i3saq4bAPXSIl08nZtq9P_ec535747aefc4e31943136a6d8587075.png",
  "style_image_url": "https://v3.fal.media/files/penguin/BCOZp6teRhSQFuOXpbBOa_da8ef9b4982347a2a62a516b737d4f21.png",
  "lora_scale": 1,
  "use_lightning_lora": true,
  "lightning_lora_scale": 1,
  "use_content_description": true,
  "use_style_description": true,
  "negative_prompt": "",
  "num_inference_steps": 4,
  "guidance_scale": 1,
  "acceleration": "none",
  "num_images": 1,
  "enable_safety_checker": true,
  "output_format": "png"
}

Output#

images list<ImageFile>* required

The stylized image(s).

has_nsfw_concepts list<boolean>

Whether the generated image contains NSFW concepts.

prompt string

The prompt derived from the content and style images. Default value: ""

seed integer* required

The seed used for generation.

{
  "images": [
    {
      "height": 1024,
      "content_type": "image/png",
      "url": "https://v3.fal.media/files/zebra/mMW8_S5PeGuDXLTfIKCpG.png",
      "width": 1024
    }
  ],
  "has_nsfw_concepts": [
    false
  ]
}

Other types#

ImageFile#

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

height integer

The height of the image

ImageSize#

width integer

The width of the generated image. Default value: 512

height integer

The height of the generated image. Default value: 512

fal-ai/telestyle-v2

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#

ImageFile#

ImageSize#