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fal-ai/scail-2

SCAIL-2 is an end-to-end character animation model that drives a reference character from a source video without relying on intermediate pose representations like skeleton maps.
Inference
Commercial use
Schema
LLMs
PlaygroundAPI

Table of contents

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/scail-2", {
  input: {
    prompt: "A person dancing gracefully in a sunlit studio",
    image_url: "https://v3b.fal.media/files/b/panda/-oMlZo9Yyj_Nzoza_tgds_GmLF86r5bOt50eMMKCszy_eacc949b3933443c9915a83c98fbe85e.png",
    video_url: "https://v3b.fal.media/files/b/panda/a6SvJg96V8eoglMlYFShU_5385885-hd_1080_1920_25fps.mp4"
  },
  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/scail-2", {
  input: {
    prompt: "A person dancing gracefully in a sunlit studio",
    image_url: "https://v3b.fal.media/files/b/panda/-oMlZo9Yyj_Nzoza_tgds_GmLF86r5bOt50eMMKCszy_eacc949b3933443c9915a83c98fbe85e.png",
    video_url: "https://v3b.fal.media/files/b/panda/a6SvJg96V8eoglMlYFShU_5385885-hd_1080_1920_25fps.mp4"
  },
  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/scail-2", {
  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/scail-2", {
  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

The prompt describing the final video to generate.

image_url string* required

URL of the reference character image. The character in this image is animated (or used to replace a subject) according to the driving video.

video_url string* required

URL of the driving (motion) video. The subject can be a human, multiple humans, or an animal.

mode ModeEnum

animation animates the reference character with the driving motion. replacement replaces the driving subject with the reference character while keeping the original scene. Default value: "animation"

Possible enum values: animation, replacement

driving_type DrivingTypeEnum

Driving signal for animation mode. end_to_end (default) drives directly from the SAM3-masked driving video and is the recommended, most robust path. pose renders an explicit NLF/DWPose skeleton from the driving video (more control for challenging inputs). Default value: "end_to_end"

Possible enum values: end_to_end, pose

subject_type SubjectTypeEnum

Type of subject in the driving video. animal switches the SAM3 detection prompt to non-human subjects. Default value: "human"

Possible enum values: human, animal

resolution ResolutionEnum

Output resolution. 512p outputs 896x512 (landscape) or 512x896 (portrait); 704p outputs 1280x704 or 704x1280. Orientation is chosen automatically from the reference image aspect ratio. Default value: "512p"

Possible enum values: 512p, 704p

num_inference_steps integer

Number of diffusion sampling steps. Higher improves quality but is slower. Default value: 40

guidance_scale float

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

shift float

Flow-matching noise schedule shift. 3.0 is recommended for the 512p tier. Default value: 3

seed integer

Random seed. Leave empty for a random seed. The seed used is returned in the response.

{
  "prompt": "A person dancing gracefully in a sunlit studio",
  "image_url": "https://v3b.fal.media/files/b/panda/-oMlZo9Yyj_Nzoza_tgds_GmLF86r5bOt50eMMKCszy_eacc949b3933443c9915a83c98fbe85e.png",
  "video_url": "https://v3b.fal.media/files/b/panda/a6SvJg96V8eoglMlYFShU_5385885-hd_1080_1920_25fps.mp4",
  "mode": "animation",
  "driving_type": "end_to_end",
  "subject_type": "human",
  "resolution": "512p",
  "num_inference_steps": 40,
  "guidance_scale": 5,
  "shift": 3
}

Output#

video File* required

The generated video file.

seed integer* required

The seed used to generate the video.

preprocessing_video File

Debug (only when output_preprocessing=true): the Stage-A pose-conditioning video fed to the diffusion model — the rendered NLF/DWPose skeleton for driving_type=pose, or the SAM3-masked driving video for end_to_end.

preprocessing_mask_video File

Debug (only when output_preprocessing=true): the Stage-A driving mask video.

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

Other types#

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.