Wan VACE 14B | Video to Video

fal-ai/wan-vace-14b/depth

VACE is a video generation model that uses a source image, mask, and video to create prompted videos with controllable sources.

Inference

Commercial use

Schema

LLMs

Playground API

About

Endpoint for generating video from depth maps.

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

Migrate to @fal-ai/client

The @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Please check the migration guide for more information.

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-vace-14b/depth", {
  input: {
    prompt: "A confident woman strides toward the camera down a sun-drenched, empty street. Her vibrant summer dress, a flowing emerald green with delicate white floral embroidery, billows slightly in the gentle breeze.  She carries a stylish, woven straw bag, its natural tan contrasting beautifully with the dress. The dress's fabric shimmers subtly, catching the light. The white embroidery is intricate, each tiny flower meticulously detailed.  Her expression is focused, yet relaxed, radiating self-assuredness. Her auburn hair, partially pulled back in a loose braid, catches the sunlight, creating warm highlights. The street itself is paved with warm, grey cobblestones, reflecting the bright sun. The mood is optimistic and serene, emphasizing the woman's independence and carefree spirit. High resolution 4k",
    video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-vace-depth-video.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"
});

Protect your API 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.

3. Queue#

Long-running requests

For long-running requests, such as training jobs or models with slower inference times, it is recommended to check the Queue status and rely on Webhooks instead of blocking while waiting for the result.

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-vace-14b/depth", {
  input: {
    prompt: "A confident woman strides toward the camera down a sun-drenched, empty street. Her vibrant summer dress, a flowing emerald green with delicate white floral embroidery, billows slightly in the gentle breeze.  She carries a stylish, woven straw bag, its natural tan contrasting beautifully with the dress. The dress's fabric shimmers subtly, catching the light. The white embroidery is intricate, each tiny flower meticulously detailed.  Her expression is focused, yet relaxed, radiating self-assuredness. Her auburn hair, partially pulled back in a loose braid, catches the sunlight, creating warm highlights. The street itself is paved with warm, grey cobblestones, reflecting the bright sun. The mood is optimistic and serene, emphasizing the woman's independence and carefree spirit. High resolution 4k",
    video_url: "https://storage.googleapis.com/falserverless/example_inputs/wan-vace-depth-video.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-vace-14b/depth", {
  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-vace-14b/depth", {
  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);

Auto uploads

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.

5. Schema#

Input#

prompt string* required

The text prompt to guide video generation.

negative_prompt string

Negative prompt for video generation. Default value: "letterboxing, borders, black bars, 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"

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter.

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter.

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string* required

URL to the source video file. Required for depth task.

ref_image_urls list<string>

URLs to source reference image. If provided, the model will use this image as reference.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

preprocess boolean

Whether to preprocess the input video.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

Temporal downsample factor for the video. This is an integer value that determines how many frames to skip in the video. A value of 0 means no downsampling. For each downsample factor, one upsample factor will automatically be applied.

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

The minimum frames per second to downsample the video to. This is used to help determine the auto downsample factor to try and find the lowest detail-preserving downsample factor. The default value is appropriate for most videos, if you are using a video with very fast motion, you may need to increase this value. If your video has a very low amount of motion, you could decrease this value to allow for higher downsampling and thus longer sequences. Default value: 15

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

{
  "prompt": "A confident woman strides toward the camera down a sun-drenched, empty street. Her vibrant summer dress, a flowing emerald green with delicate white floral embroidery, billows slightly in the gentle breeze.  She carries a stylish, woven straw bag, its natural tan contrasting beautifully with the dress. The dress's fabric shimmers subtly, catching the light. The white embroidery is intricate, each tiny flower meticulously detailed.  Her expression is focused, yet relaxed, radiating self-assuredness. Her auburn hair, partially pulled back in a loose braid, catches the sunlight, creating warm highlights. The street itself is paved with warm, grey cobblestones, reflecting the bright sun. The mood is optimistic and serene, emphasizing the woman's independence and carefree spirit. High resolution 4k",
  "negative_prompt": "letterboxing, borders, black bars, 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",
  "match_input_num_frames": false,
  "num_frames": 81,
  "match_input_frames_per_second": false,
  "frames_per_second": 16,
  "resolution": "auto",
  "aspect_ratio": "auto",
  "num_inference_steps": 30,
  "guidance_scale": 5,
  "sampler": "unipc",
  "shift": 5,
  "video_url": "https://storage.googleapis.com/falserverless/example_inputs/wan-vace-depth-video.mp4",
  "enable_safety_checker": true,
  "enable_prompt_expansion": false,
  "preprocess": false,
  "acceleration": "regular",
  "video_quality": "high",
  "video_write_mode": "balanced",
  "num_interpolated_frames": 0,
  "temporal_downsample_factor": 0,
  "enable_auto_downsample": false,
  "auto_downsample_min_fps": 15,
  "interpolator_model": "film",
  "sync_mode": false,
  "transparency_mode": "content_aware"
}

Output#

video VideoFile* required

The generated depth video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

{
  "video": {
    "url": "https://storage.googleapis.com/falserverless/example_outputs/wan-vace-depth-output.mp4"
  },
  "prompt": ""
}

Other types#

WanVACERequest#

prompt string* required

The text prompt to guide video generation.

negative_prompt string

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter.

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter.

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

task TaskEnum

Task type for the model. Default value: "depth"

Possible enum values: depth, pose, inpainting, outpainting, reframe

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string

URL to the source video file. If provided, the model will use this video as a reference.

mask_video_url string

URL to the source mask file. If provided, the model will use this mask as a reference.

mask_image_url string

URL 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.

ref_image_urls list<string>

URLs to source reference image. If provided, the model will use this image as reference.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

preprocess boolean

Whether to preprocess the input video.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

WanVACEReframeRequest#

prompt string

The text prompt to guide video generation. Optional for reframing. Default value: ""

negative_prompt string

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter. Default value: true

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter. Default value: true

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string* required

URL to the source video file. This video will be used as a reference for the reframe task.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

zoom_factor float

Zoom factor for the video. When this value is greater than 0, the video will be zoomed in by this factor (in relation to the canvas size,) cutting off the edges of the video. A value of 0 means no zoom.

trim_borders boolean

Whether to trim borders from the video. Default value: true

WanVACEImageToVideoRequest#

prompt string* required

The prompt to guide the video generation.

first_frame_url string* required

URL to the first frame of the video.

last_frame_url string

URL to the last frame of the video.

ref_image_urls list<string>

URLs to reference images.

negative_prompt string

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

WanVACEPoseRequest#

prompt string* required

The text prompt to guide video generation. For pose task, the prompt should describe the desired pose and action of the subject in the video.

negative_prompt string

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter.

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter.

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string* required

URL to the source video file. Required for pose task.

ref_image_urls list<string>

URLs to source reference image. If provided, the model will use this image as reference.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

preprocess boolean

Whether to preprocess the input video.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

WanVACEReframeResponse#

video VideoFile* required

The generated reframe video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACETextToVideoRequest#

prompt string* required

The prompt to guide the video generation.

negative_prompt string

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "720p"

Possible enum values: 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "16:9"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

ref_image_urls list<string>

URLs to reference images.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

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.

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

WanVACEOutpaintingResponse#

video VideoFile* required

The generated outpainting video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEImageToVideoResponse#

video VideoFile* required

The generated image to video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEResponse#

video VideoFile* required

The generated video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEInpaintingResponse#

video VideoFile* required

The generated inpainting video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEInpaintingRequest#

prompt string* required

The text prompt to guide video generation.

negative_prompt string

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter.

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter.

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string* required

URL to the source video file. Required for inpainting.

mask_video_url string* required

URL to the source mask file. Required for inpainting.

mask_image_url string

URL to the guiding mask file. If provided, the model will use this mask as a reference to create masked video using salient mask tracking. Will be ignored if mask_video_url is provided.

ref_image_urls list<string>

Urls to source reference image. If provided, the model will use this image as reference.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

preprocess boolean

Whether to preprocess the input video.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

WanVACETextToVideoResponse#

video VideoFile* required

The generated text to video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEPoseResponse#

video VideoFile* required

The generated pose video file.

prompt string* required

The prompt used for generation.

seed integer* required

The seed used for generation.

WanVACEOutpaintingRequest#

prompt string* required

The text prompt to guide video generation.

negative_prompt string

match_input_num_frames boolean

If true, the number of frames in the generated video will match the number of frames in the input video. If false, the number of frames will be determined by the num_frames parameter.

num_frames integer

Number of frames to generate. Must be between 81 to 241 (inclusive). Default value: 81

match_input_frames_per_second boolean

If true, the frames per second of the generated video will match the input video. If false, the frames per second will be determined by the frames_per_second parameter.

frames_per_second integer

Frames per second of the generated video. Must be between 5 to 30. Ignored if match_input_frames_per_second is true. Default value: 16

seed integer

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

resolution ResolutionEnum

Resolution of the generated video. Default value: "auto"

Possible enum values: auto, 240p, 360p, 480p, 580p, 720p

aspect_ratio AspectRatioEnum

Aspect ratio of the generated video. Default value: "auto"

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

num_inference_steps integer

Number of inference steps for sampling. Higher values give better quality but take longer. Default value: 30

guidance_scale float

Guidance scale for classifier-free guidance. Higher values encourage the model to generate images closely related to the text prompt. Default value: 5

sampler SamplerEnum

Sampler to use for video generation. Default value: "unipc"

Possible enum values: unipc, dpm++, euler

shift float

Shift parameter for video generation. Default value: 5

video_url string* required

URL to the source video file. Required for outpainting.

ref_image_urls list<string>

URLs to source reference image. If provided, the model will use this image as reference.

first_frame_url string

URL to the first frame of the video. If provided, the model will use this frame as a reference.

last_frame_url string

URL to the last frame of the video. If provided, the model will use this frame as a reference.

enable_safety_checker boolean

If set to true, the safety checker will be enabled.

enable_prompt_expansion boolean

Whether to enable prompt expansion.

acceleration Enum

Acceleration to use for inference. Options are 'none' or 'regular'. Accelerated inference will very slightly affect output, but will be significantly faster. Default value: regular

Possible enum values: none, low, regular

video_quality VideoQualityEnum

The quality of the generated video. Default value: "high"

Possible enum values: low, medium, high, maximum

video_write_mode VideoWriteModeEnum

The write mode of the generated video. Default value: "balanced"

Possible enum values: fast, balanced, small

num_interpolated_frames integer

Number of frames to interpolate between the original frames. A value of 0 means no interpolation.

temporal_downsample_factor integer

enable_auto_downsample boolean

If true, the model will automatically temporally downsample the video to an appropriate frame length for the model, then will interpolate it back to the original frame length.

auto_downsample_min_fps float

interpolator_model InterpolatorModelEnum

The model to use for frame interpolation. Options are 'rife' or 'film'. Default value: "film"

Possible enum values: rife, film

sync_mode boolean

If True, the media will be returned as a data URI and the output data won't be available in the request history.

transparency_mode TransparencyModeEnum

The transparency mode to apply to the first and last frames. This controls how the transparent areas of the first and last frames are filled. Default value: "content_aware"

Possible enum values: content_aware, white, black

expand_left boolean

Whether to expand the video to the left.

expand_right boolean

Whether to expand the video to the right.

expand_top boolean

Whether to expand the video to the top.

expand_bottom boolean

Whether to expand the video to the bottom.

expand_ratio float

Amount of expansion. This is a float value between 0 and 1, where 0.25 adds 25% to the original video size on the specified sides. Default value: 0.25

Wan VACE 14B Video to Video

Table of contents

1. Calling the API

2. Authentication

3. Queue

4. Files

5. Schema

About

1. Calling the API#

Install the client#

Migrate to @fal-ai/client

Setup your API Key#

Submit a request#

2. Authentication#

API Key#

Protect your API Key

3. Queue#

Long-running requests

Submit a request#

Fetch request status#

Get the result#

4. Files#

Data URI (base64)#

Hosted files (URL)#

Uploading files#

Auto uploads

5. Schema#

Input#

Output#

Other types#

WanVACERequest#

WanVACEReframeRequest#

WanVACEImageToVideoRequest#

WanVACEPoseRequest#

WanVACEReframeResponse#

WanVACETextToVideoRequest#

VideoFile#

WanVACEOutpaintingResponse#

WanVACEImageToVideoResponse#

WanVACEResponse#

WanVACEInpaintingResponse#

WanVACEInpaintingRequest#

WanVACETextToVideoResponse#

WanVACEPoseResponse#

WanVACEOutpaintingRequest#

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