Endpoint for generating a video from another video.
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/v2.2-a14b/video-to-video", {
input: {
video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-2.2-v2v-input.mp4",
prompt: "A low-angle medium shot captures a domestic white cat with brown and black patches and a blue bandana sitting on a light-colored tiled floor indoors, meticulously grooming itself by licking its paw and then rubbing its face with it, against a soft-focused background of wooden kitchen cabinets and a reflective metallic appliance."
},
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/v2.2-a14b/video-to-video", {
input: {
video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-2.2-v2v-input.mp4",
prompt: "A low-angle medium shot captures a domestic white cat with brown and black patches and a blue bandana sitting on a light-colored tiled floor indoors, meticulously grooming itself by licking its paw and then rubbing its face with it, against a soft-focused background of wooden kitchen cabinets and a reflective metallic appliance."
},
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/v2.2-a14b/video-to-video", {
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/v2.2-a14b/video-to-video", {
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.
video_url string* requiredURL of the input video.
prompt string* requiredThe text prompt to guide video generation.
strength floatStrength of the video transformation. A value of 1.0 means the output will be completely based on the prompt, while a value of 0.0 means the output will be identical to the input video. Default value: 0.9
num_frames integerNumber of frames to generate. Must be between 17 to 161 (inclusive). Default value: 81
frames_per_second integerFrames per second of the generated video. Must be between 4 to 60. When using interpolation and adjust_fps_for_interpolation is set to true (default true,) the final FPS will be multiplied by the number of interpolated frames plus one. For example, if the generated frames per second is 16 and the number of interpolated frames is 1, the final frames per second will be 32. If adjust_fps_for_interpolation is set to false, this value will be used as-is. Default value: 16
negative_prompt stringNegative prompt for video generation. Default value: ""
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. If 'auto', the aspect ratio will be determined automatically based on the input video. Default value: "auto"
Possible enum values: auto, 16:9, 9:16, 1:1
num_inference_steps integerNumber of inference steps for sampling. Higher values give better quality but take longer. Default value: 27
enable_safety_checker booleanIf set to true, input data will be checked for safety before processing. Disabling it requires account authorization; unauthorized requests are always checked.
enable_output_safety_checker booleanIf set to true, output video will be checked for safety after generation.
enable_prompt_expansion booleanWhether to enable prompt expansion. This will use a large language model to expand the prompt with additional details while maintaining the original meaning.
acceleration AccelerationEnumAcceleration level to use. The more acceleration, the faster the generation, but with lower quality. The recommended value is 'regular'. Default value: "regular"
Possible enum values: none, regular
guidance_scale floatClassifier-free guidance scale. Higher values give better adherence to the prompt but may decrease quality. Default value: 3.5
guidance_scale_2 floatGuidance scale for the second stage of the model. This is used to control the adherence to the prompt in the second stage of the model. Default value: 4
shift floatShift value for the video. Must be between 1.0 and 10.0. Default value: 5
interpolator_model InterpolatorModelEnumThe model to use for frame interpolation. If None, no interpolation is applied. Default value: "film"
Possible enum values: none, film, rife
num_interpolated_frames integerNumber of frames to interpolate between each pair of generated frames. Must be between 0 and 4. Default value: 1
adjust_fps_for_interpolation booleanIf true, the number of frames per second will be multiplied by the number of interpolated frames plus one. For example, if the generated frames per second is 16 and the number of interpolated frames is 1, the final frames per second will be 32. If false, the passed frames per second will be used as-is. Default value: true
video_quality VideoQualityEnumThe quality of the output video. Higher quality means better visual quality but larger file size. Default value: "high"
Possible enum values: low, medium, high, maximum
video_write_mode VideoWriteModeEnumThe write mode of the output video. Faster write mode means faster results but larger file size, balanced write mode is a good compromise between speed and quality, and small write mode is the slowest but produces the smallest file size. Default value: "balanced"
Possible enum values: fast, balanced, small
resample_fps booleanIf true, the video will be resampled to the passed frames per second. If false, the video will not be resampled.
{
"video_url": "https://storage.googleapis.com/falserverless/example_inputs/wan-2.2-v2v-input.mp4",
"prompt": "A low-angle medium shot captures a domestic white cat with brown and black patches and a blue bandana sitting on a light-colored tiled floor indoors, meticulously grooming itself by licking its paw and then rubbing its face with it, against a soft-focused background of wooden kitchen cabinets and a reflective metallic appliance.",
"strength": 0.9,
"num_frames": 81,
"frames_per_second": 16,
"resolution": "720p",
"aspect_ratio": "auto",
"num_inference_steps": 27,
"enable_safety_checker": true,
"enable_output_safety_checker": false,
"enable_prompt_expansion": false,
"acceleration": "regular",
"guidance_scale": 3.5,
"guidance_scale_2": 4,
"shift": 5,
"interpolator_model": "film",
"num_interpolated_frames": 1,
"adjust_fps_for_interpolation": true,
"video_quality": "high",
"video_write_mode": "balanced",
"resample_fps": false
}The generated video file.
prompt stringThe text prompt used for video generation. Default value: ""
seed integer* requiredThe seed used for generation.
{
"video": {
"url": "https://storage.googleapis.com/falserverless/example_outputs/wan-2.2-v2v-output.mp4"
},
"prompt": "A low-angle medium shot captures a domestic white cat with brown and black patches and a blue bandana sitting on a light-colored tiled floor indoors, meticulously grooming itself by licking its paw and then rubbing its face with it, against a soft-focused background of wooden kitchen cabinets and a reflective metallic appliance."
}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.