# Wan

> Wan-2.2 video-to-video is a video model that generates high-quality videos with high visual quality and motion diversity from text prompts and source videos.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/wan/v2.2-a14b/video-to-video`
- **Model ID**: `fal-ai/wan/v2.2-a14b/video-to-video`
- **Category**: video-to-video
- **Kind**: inference


## Pricing

Your request will cost **$0.08** per **video second** for **720p**, **$0.06** per **video second** for **580p**, **$0.04** per **video second** for **480p**. Video seconds are calculated at 16 frames per second.

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`video_url`** (`string`, _required_):
  URL of the input video.
  - Examples: "https://storage.googleapis.com/falserverless/example_inputs/wan-2.2-v2v-input.mp4"

- **`prompt`** (`string`, _required_):
  The text prompt to guide video generation.
  - Examples: "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`** (`float`, _optional_):
  Strength 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`
  - Default: `0.9`
  - Range: `0` to `1`
  - Examples: 0.9

- **`num_frames`** (`integer`, _optional_):
  Number of frames to generate. Must be between 17 to 161 (inclusive). Default value: `81`
  - Default: `81`
  - Range: `17` to `161`
  - Examples: 81

- **`frames_per_second`** (`integer`, _optional_):
  Frames 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`
  - Default: `16`
  - Range: `4` to `60`
  - Examples: 16

- **`negative_prompt`** (`string`, _optional_):
  Negative prompt for video generation. Default value: `""`
  - Default: `""`

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility. If None, a random seed is chosen.

- **`resolution`** (`ResolutionEnum`, _optional_):
  Resolution of the generated video (480p, 580p, or 720p). Default value: `"720p"`
  - Default: `"720p"`
  - Options: `"480p"`, `"580p"`, `"720p"`
  - Examples: "720p"

- **`aspect_ratio`** (`AspectRatioEnum`, _optional_):
  Aspect ratio of the generated video. If 'auto', the aspect ratio will be determined automatically based on the input video. Default value: `"auto"`
  - Default: `"auto"`
  - Options: `"auto"`, `"16:9"`, `"9:16"`, `"1:1"`

- **`num_inference_steps`** (`integer`, _optional_):
  Number of inference steps for sampling. Higher values give better quality but take longer. Default value: `27`
  - Default: `27`
  - Range: `2` to `40`
  - Examples: 27

- **`enable_safety_checker`** (`boolean`, _optional_):
  If set to true, input data will be checked for safety before processing.
  - Default: `false`
  - Examples: true

- **`enable_output_safety_checker`** (`boolean`, _optional_):
  If set to true, output video will be checked for safety after generation.
  - Default: `false`
  - Examples: false

- **`enable_prompt_expansion`** (`boolean`, _optional_):
  Whether to enable prompt expansion. This will use a large language model to expand the prompt with additional details while maintaining the original meaning.
  - Default: `false`
  - Examples: false

- **`acceleration`** (`AccelerationEnum`, _optional_):
  Acceleration level to use. The more acceleration, the faster the generation, but with lower quality. The recommended value is 'regular'. Default value: `"regular"`
  - Default: `"regular"`
  - Options: `"none"`, `"regular"`
  - Examples: "regular"

- **`guidance_scale`** (`float`, _optional_):
  Classifier-free guidance scale. Higher values give better adherence to the prompt but may decrease quality. Default value: `3.5`
  - Default: `3.5`
  - Range: `1` to `10`
  - Examples: 3.5

- **`guidance_scale_2`** (`float`, _optional_):
  Guidance 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`
  - Default: `4`
  - Range: `1` to `10`
  - Examples: 4

- **`shift`** (`float`, _optional_):
  Shift value for the video. Must be between 1.0 and 10.0. Default value: `5`
  - Default: `5`
  - Range: `1` to `10`
  - Examples: 5

- **`interpolator_model`** (`InterpolatorModelEnum`, _optional_):
  The model to use for frame interpolation. If None, no interpolation is applied. Default value: `"film"`
  - Default: `"film"`
  - Options: `"none"`, `"film"`, `"rife"`
  - Examples: "film"

- **`num_interpolated_frames`** (`integer`, _optional_):
  Number of frames to interpolate between each pair of generated frames. Must be between 0 and 4. Default value: `1`
  - Default: `1`
  - Range: `0` to `4`
  - Examples: 1

- **`adjust_fps_for_interpolation`** (`boolean`, _optional_):
  If 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`
  - Default: `true`
  - Examples: true

- **`video_quality`** (`VideoQualityEnum`, _optional_):
  The quality of the output video. Higher quality means better visual quality but larger file size. Default value: `"high"`
  - Default: `"high"`
  - Options: `"low"`, `"medium"`, `"high"`, `"maximum"`
  - Examples: "high"

- **`video_write_mode`** (`VideoWriteModeEnum`, _optional_):
  The 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"`
  - Default: `"balanced"`
  - Options: `"fast"`, `"balanced"`, `"small"`
  - Examples: "balanced"

- **`resample_fps`** (`boolean`, _optional_):
  If true, the video will be resampled to the passed frames per second. If false, the video will not be resampled.
  - Default: `false`
  - Examples: false



**Required Parameters Example**:

```json
{
  "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."
}
```

**Full Example**:

```json
{
  "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
}
```


### Output Schema

The API returns the following output format:

- **`video`** (`File`, _required_):
  The generated video file.
  - Examples: {"url":"https://storage.googleapis.com/falserverless/example_outputs/wan-2.2-v2v-output.mp4"}

- **`prompt`** (`string`, _optional_):
  The text prompt used for video generation. Default value: `""`
  - Default: `""`
  - Examples: "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."

- **`seed`** (`integer`, _required_):
  The seed used for generation.



**Example Response**:

```json
{
  "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."
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/wan/v2.2-a14b/video-to-video \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "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."
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "fal-ai/wan/v2.2-a14b/video-to-video",
    arguments={
        "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."
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
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);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/fal-ai/wan/v2.2-a14b/video-to-video)
- [API Documentation](https://fal.ai/models/fal-ai/wan/v2.2-a14b/video-to-video/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/wan/v2.2-a14b/video-to-video)

### fal.ai Platform

- [Platform Documentation](https://docs.fal.ai)
- [Python Client](https://docs.fal.ai/clients/python)
- [JavaScript Client](https://docs.fal.ai/clients/javascript)