This model is no longer supported.
This model is no longer supported.
Generate a video from a prompt.
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/wan-vace", {
input: {
prompt: "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse."
},
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/wan-vace", {
input: {
prompt: "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse."
},
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/wan-vace", {
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/wan-vace", {
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.
prompt string* requiredThe text prompt to guide video generation.
negative_prompt stringNegative prompt for video generation. Default value: "bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards"
num_frames integerNumber of frames to generate. Must be between 81 to 100 (inclusive). Works only with only reference images as input if source video or mask video is provided output len would be same as source up to 241 frames Default value: 81
frames_per_second integerFrames per second of the generated video. Must be between 5 to 24. Default value: 16
task TaskEnumTask type for the model. Default value: "depth"
Possible enum values: depth, inpainting
shift floatShift parameter for video generation. Default value: 5
seed integerRandom seed for reproducibility. If None, a random seed is chosen.
resolution ResolutionEnumResolution of the generated video (480p,580p, or 720p). Default value: "720p"
Possible enum values: 480p, 580p, 720p
aspect_ratio AspectRatioEnumAspect ratio of the generated video (16:9 or 9:16). Default value: "16:9"
Possible enum values: auto, 9:16, 16:9
num_inference_steps integerNumber of inference steps for sampling. Higher values give better quality but take longer. Default value: 30
video_url stringURL to the source video file. If provided, the model will use this video as a reference.
mask_video_url stringURL to the source mask file. If provided, the model will use this mask as a reference.
mask_image_url stringURL to the guiding mask file. If provided, the model will use this mask as a reference to create masked video. If provided mask video url will be ignored.
Urls to source reference image. If provided, the model will use this image as reference.
enable_safety_checker booleanIf set to true, the safety checker will be enabled.
enable_prompt_expansion booleanWhether to enable prompt expansion.
preprocess booleanWhether to preprocess the input video.
{
"prompt": "The video shows a man riding a horse on a vast grassland. He has long lavender hair and wears a traditional dress of a white top and black pants. The animation style makes him look like he is doing some kind of outdoor activity or performing. The background is a spectacular mountain range and cloud sky, giving a sense of tranquility and vastness. The entire video is shot from a fixed angle, focusing on the rider and his horse.",
"negative_prompt": "bright colors, overexposed, static, blurred details, subtitles, style, artwork, painting, picture, still, overall gray, worst quality, low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured, malformed limbs, fused fingers, still picture, cluttered background, three legs, many people in the background, walking backwards",
"num_frames": 81,
"frames_per_second": 16,
"task": "depth",
"shift": 5,
"resolution": "720p",
"aspect_ratio": "16:9",
"num_inference_steps": 30,
"video_url": "https://storage.googleapis.com/falserverless/vace/src_video.mp4",
"mask_video_url": "https://storage.googleapis.com/falserverless/vace/src_mask.mp4",
"ref_image_urls": [
"https://storage.googleapis.com/falserverless/vace/src_ref_image_1.png"
],
"enable_safety_checker": true,
"enable_prompt_expansion": true
}The generated video file.
seed integer* requiredThe seed used for generation.
{
"video": {
"url": "https://storage.googleapis.com/falserverless/vace/out_video_vace.mp4"
}
}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.