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Wan 2.2 Fun Control Video to Video

fal-ai/wan-fun-control
Generate pose or depth controlled video using Alibaba-PAI's Wan 2.2 Fun
Inference
Commercial use
PlaygroundAPI

About

Generate a video.

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/wan-fun-control", {
  input: {
    prompt: "A woman wearing a lavender floral dress spins around in a circle.",
    control_video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-fun-control-video-input.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/wan-fun-control", {
  input: {
    prompt: "A woman wearing a lavender floral dress spins around in a circle.",
    control_video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-fun-control-video-input.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/wan-fun-control", {
  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/wan-fun-control", {
  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 to generate the video.

negative_prompt string

The negative prompt to generate the video. Default value: ""

num_inference_steps integer

The number of inference steps. Default value: 27

guidance_scale float

The guidance scale. Default value: 6

shift float

The shift for the scheduler. Default value: 5

seed integer

The seed for the random number generator.

match_input_num_frames boolean

Whether to match the number of frames in the input video. Default value: true

num_frames integer

The number of frames to generate. Only used when match_input_num_frames is False. Default value: 81

match_input_fps boolean

Whether to match the fps in the input video. Default value: true

fps integer

The fps to generate. Only used when match_input_fps is False. Default value: 16

control_video_url string* required

The URL of the control video to use as a reference for the video generation.

preprocess_video boolean

Whether to preprocess the video. If True, the video will be preprocessed to depth or pose.

preprocess_type PreprocessTypeEnum

The type of preprocess to apply to the video. Only used when preprocess_video is True. Default value: "depth"

Possible enum values: depth, pose

reference_image_url string

The URL of the reference image to use as a reference for the video generation.

{
  "prompt": "A woman wearing a lavender floral dress spins around in a circle.",
  "num_inference_steps": 27,
  "guidance_scale": 6,
  "shift": 5,
  "match_input_num_frames": true,
  "num_frames": 81,
  "match_input_fps": true,
  "fps": 16,
  "control_video_url": "https://storage.googleapis.com/falserverless/example_inputs/wan-fun-control-video-input.mp4",
  "preprocess_type": "depth",
  "reference_image_url": "https://storage.googleapis.com/falserverless/example_inputs/wan-fun-input-reference-image.webp"
}

Output#

video File* required

The video generated by the model.

{
  "video": {
    "url": "https://storage.googleapis.com/falserverless/example_outputs/wan-fun-example-output.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.

file_data string

File data