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Lynx Image to Video

fal-ai/lynx
Generate subject consistent videos using Lynx from ByteDance!
Inference
Commercial use
Schema
LLMs
PlaygroundAPI

About

Generate

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/lynx", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/lynx/example_in.png",
    prompt: "A person carves a pumpkin on a porch in the evening. The camera captures their upper body as they draw a face with a marker, carefully cut along the lines, then lift the lid with both hands. Their face lights up with excitement as they peek inside"
  },
  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/lynx", {
  input: {
    image_url: "https://storage.googleapis.com/falserverless/example_inputs/lynx/example_in.png",
    prompt: "A person carves a pumpkin on a porch in the evening. The camera captures their upper body as they draw a face with a marker, carefully cut along the lines, then lift the lid with both hands. Their face lights up with excitement as they peek inside"
  },
  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/lynx", {
  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/lynx", {
  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#

image_url string* required

The URL of the subject image to be used for video generation

prompt string* required

Text prompt to guide video generation

negative_prompt string

Negative prompt to guide what should not appear in the generated video Default value: "Bright tones, overexposed, blurred background, static, subtitles, style, works, paintings, images, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards"

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 50

seed integer

Random seed for reproducibility. If None, a random seed is chosen.

resolution ResolutionEnum

Resolution of the generated video (480p, 580p, or 720p) Default value: "720p"

Possible enum values: 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video (16:9, 9:16, or 1:1) Default value: "16:9"

Possible enum values: 16:9, 9:16, 1:1

ip_scale float

Identity preservation scale. Controls how closely the generated video preserves the subject's identity from the reference image. Default value: 1

strength float

Reference image scale. Controls the influence of the reference image on the generated video. Default value: 1

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Default value: 16

guidance_scale float

Classifier-free guidance scale. Higher values give better adherence to the prompt but may decrease quality. Default value: 5

guidance_scale_2 float

Image guidance scale. Controls how closely the generated video follows the reference image. Higher values increase adherence to the reference image but may decrease quality. Default value: 2

num_frames integer

Number of frames in the generated video. Must be between 9 to 100. Default value: 81

{
  "image_url": "https://storage.googleapis.com/falserverless/example_inputs/lynx/example_in.png",
  "prompt": "A person carves a pumpkin on a porch in the evening. The camera captures their upper body as they draw a face with a marker, carefully cut along the lines, then lift the lid with both hands. Their face lights up with excitement as they peek inside",
  "negative_prompt": "Bright tones, overexposed, blurred background, static, subtitles, style, works, paintings, images, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards",
  "num_inference_steps": 50,
  "resolution": "720p",
  "aspect_ratio": "16:9",
  "ip_scale": 1,
  "strength": 1,
  "frames_per_second": 16,
  "guidance_scale": 5,
  "guidance_scale_2": 2,
  "num_frames": 81
}

Output#

video VideoFile* required

The generated video file

seed integer* required

The seed used for generation

{
  "video": {
    "content_type": "video/mp4",
    "url": "https://storage.googleapis.com/falserverless/example_outputs/lynx/example_out.mp4"
  }
}

Other types#

VideoFile#

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 video

height integer

The height of the video

fps float

The FPS of the video

duration float

The duration of the video

num_frames integer

The number of frames in the video