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.
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"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);The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_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.
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",
});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,
});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);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.
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.
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.
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);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.
content_image_url string* requiredURL of the content image — the image whose subject and structure are preserved while the style is applied.
style_image_url string* requiredURL of the style reference image — the artistic style, material, lighting and color of this image are transferred onto the content image.
lora_scale floatStrength of the TeleStyleV2 style adapter. 1.0 matches the reference implementation; lower values apply the style more subtly. Default value: 1
use_lightning_lora booleanIf true, use the Lightning LoRA in addition to the default LoRA. Default value: true
lightning_lora_scale floatStrength of the Lightning LoRA. 1.0 matches the reference implementation; lower values apply the style more subtly. Default value: 1
use_content_description booleanIf true, describe the content image with a VLM and add the description to the prompt. Default value: true
use_style_description booleanIf true, describe the style image with a VLM and add the description to the prompt. Default value: true
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 stringThe negative prompt for the generation. Default value: ""
num_inference_steps integerThe number of inference steps to perform. Default value: 4
guidance_scale floatThe CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt. Default value: 1
acceleration AccelerationEnumAcceleration 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 integerThe number of images to generate. Default value: 1
seed integerThe same seed and the same inputs given to the same version of the model will output the same image every time.
sync_mode booleanIf 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 booleanIf set to true, the safety checker will be enabled. Default value: true
output_format OutputFormatEnumThe 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"
}The stylized image(s).
Whether the generated image contains NSFW concepts.
prompt stringThe prompt derived from the content and style images. Default value: ""
seed integer* requiredThe seed used for generation.
{
"images": [
{
"url": "https://v3.fal.media/files/zebra/mMW8_S5PeGuDXLTfIKCpG.png",
"width": 1024,
"height": 1024,
"content_type": "image/png"
}
],
"has_nsfw_concepts": [
false
]
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
width integerThe width of the image
height integerThe height of the image