fal-ai/id-v2v/relight

Change a video’s lighting using a relit reference frame while preserving the scene, subjects, and original performance. ID-V2V Relight propagates the new illumination across the video.

Inference

Commercial use

Schema

LLMs

Playground API Examples

About

Relight

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. Install the new package and update your imports — see client setup.

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/id-v2v/relight", {
  input: {
    prompt: "An astronaut walking through an autumn forest",
    video_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/mmaudio_input.mp4",
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/ltxv-image-input.jpg"
  },
  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 an environment where you cannot set environment variables, you can configure the API key manually on the client.

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/id-v2v/relight", {
  input: {
    prompt: "An astronaut walking through an autumn forest",
    video_url: "https://storage.googleapis.com/falserverless/model_tests/video_models/mmaudio_input.mp4",
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/ltxv-image-input.jpg"
  },
  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/id-v2v/relight", {
  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/id-v2v/relight", {
  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 prompt describing the restyled video to generate.

video_url string* required

URL of the source video whose motion and framing drive the generation.

image_url string* required

URL of the restyled first frame. The video is regenerated in this frame's identity/style.

keyframes list<Keyframe>

Optional restyled keyframes pinned at specific output frame indices to anchor identity over long videos.

resolution ResolutionEnum

Output resolution tier. Orientation follows the source video (720p is 1280x720 or 720x1280; 480p is 832x480 or 480x832). Default value: "720p"

Possible enum values: 480p, 720p

num_frames integer

Maximum number of output frames. Capped at the source video's frame count. Default value: 81

num_inference_steps integer

Number of diffusion sampling steps per clip. Higher improves quality but is slower. Default value: 30

guidance_scale float

Classifier-free guidance scale. Controls prompt adherence versus creativity. Default value: 5

vace_scale float

VACE conditioning scale. Controls how strongly the source video's structure constrains the generation. Default value: 1

seed integer

Random seed for reproducibility. The same seed is used for every clip of a multi-clip generation.

enable_safety_checker boolean

Enable safety checking of inputs and outputs. Default value: true

{
  "prompt": "An astronaut walking through an autumn forest",
  "video_url": "https://storage.googleapis.com/falserverless/model_tests/video_models/mmaudio_input.mp4",
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/ltxv-image-input.jpg",
  "keyframes": [
    {
      "image_url": "https://storage.googleapis.com/falserverless/example_inputs/ltxv-image-input.jpg",
      "frame_index": 80
    }
  ],
  "resolution": "720p",
  "num_frames": 81,
  "num_inference_steps": 30,
  "guidance_scale": 5,
  "vace_scale": 1,
  "enable_safety_checker": true
}

Output#

video File* required

The generated video file.

seed integer* required

The seed used for generation.

{
  "video": {
    "content_type": "video/mp4",
    "file_name": "output.mp4",
    "file_size": 1048576,
    "url": "https://storage.googleapis.com/falserverless/example_outputs/scail2-output.mp4"
  }
}

Other types#

Keyframe#

image_url string* required

URL of a restyled keyframe image. It is pinned verbatim at frame_index to anchor identity over long videos. Its aspect ratio must match the output aspect ratio within 0.1.

frame_index integer* required

0-based output frame index for this keyframe. Must be >= 1 (frame 0 is the restyled first frame from image_url) and less than the output frame count.

File#

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.

IDV2VRequest#

prompt string* required

The prompt describing the restyled video to generate.

video_url string* required

URL of the source video whose motion and framing drive the generation.

image_url string* required

URL of the restyled first frame. The video is regenerated in this frame's identity/style.

keyframes list<Keyframe>

Optional restyled keyframes pinned at specific output frame indices to anchor identity over long videos.

resolution ResolutionEnum

Output resolution tier. Orientation follows the source video (720p is 1280x720 or 720x1280; 480p is 832x480 or 480x832). Default value: "720p"

Possible enum values: 480p, 720p

num_frames integer

Maximum number of output frames. Capped at the source video's frame count. Default value: 81

segmentation_prompt string

Text prompt for SAM-3 subject segmentation. The segmented subject's pixels condition the generation; the rest of the frame is regenerated freely. Default value: "person"

num_inference_steps integer

Number of diffusion sampling steps per clip. Higher improves quality but is slower. Default value: 30

guidance_scale float

Classifier-free guidance scale. Controls prompt adherence versus creativity. Default value: 5

vace_scale float

VACE conditioning scale. Controls how strongly the source video's structure constrains the generation. Default value: 1

seed integer

Random seed for reproducibility. The same seed is used for every clip of a multi-clip generation.

enable_safety_checker boolean

Enable safety checking of inputs and outputs. Default value: true

fal-ai/id-v2v/relight

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#

Keyframe#

File#

IDV2VRequest#

Related Models