> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pixeltable.com/llms.txt
> Use this file to discover all available pages before exploring further.

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  ## Submitting Feedback
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# runwayml

> <a href="https://github.com/pixeltable/pixeltable/blob/main/pixeltable/functions/runwayml.py#L0" id="viewSource" target="_blank" rel="noopener noreferrer"><img src="https://img.shields.io/badge/View%20Source%20on%20Github-blue?logo=github&labelColor=gray" alt="View Source on GitHub" style={{ display: 'inline', margin: '0px' }} noZoom /></a>

# <span style={{ 'color': 'gray' }}>module</span>  pixeltable.functions.runwayml

Pixeltable UDFs
that wrap various endpoints from the RunwayML API. In order to use them, you must
first `pip install runwayml` and configure your RunwayML credentials by setting the `RUNWAYML_API_SECRET` environment
variable.

## <span style={{ 'color': 'gray' }}>udf</span>  image\_to\_video()

```python Signature theme={null}
@pxt.udf
image_to_video(
    prompt_image: pxt.Image,
    model: pxt.String,
    ratio: pxt.String,
    *,
    prompt_text: pxt.String | None = None,
    duration: pxt.Int | None = None,
    seed: pxt.Int | None = None,
    audio: pxt.Bool | None = None,
    model_kwargs: pxt.Json | None = None
) -> pxt.Json
```

Generate videos from images.

For additional details, see: [Image to video](https://docs.dev.runwayml.com/api/#tag/Start-generating/paths/~1v1~1image_to_video/post)

**Requirements:**

* `pip install runwayml`

**Parameters:**

* **`prompt_image`** (`pxt.Image`): Input image to use as the first frame.
* **`model`** (`pxt.String`): The model to use.
* **`ratio`** (`pxt.String`): Aspect ratio of the generated video.
* **`prompt_text`** (`pxt.String | None`): Text description to guide generation.
* **`duration`** (`pxt.Int | None`): Duration in seconds.
* **`seed`** (`pxt.Int | None`): Seed for reproducibility.
* **`audio`** (`pxt.Bool | None`): Whether to generate audio.
* **`model_kwargs`** (`pxt.Json | None`): Additional API parameters.

**Returns:**

* `pxt.Json`: A dictionary containing the response and metadata.

**Examples:**

Add a computed column that generates videos from images:

```python  theme={null}
tbl.add_computed_column(
    response=image_to_video(
        tbl.image,
        model='gen4',
        ratio='16:9',
        prompt_text='Slow motion',
        duration=5,
    )
)
tbl.add_computed_column(video=tbl.response['output'].astype(pxt.Video))
```

## <span style={{ 'color': 'gray' }}>udf</span>  text\_to\_image()

```python Signature theme={null}
@pxt.udf
text_to_image(
    prompt_text: pxt.String,
    reference_images: pxt.Json[(Image, model: pxt.String, ratio: pxt.String, *, seed: pxt.Int | None = None, model_kwargs: pxt.Json | None = None
) -> pxt.Json
```

Generate images from text prompts and reference images.

For additional details, see: [Text/Image to Image](https://docs.dev.runwayml.com/api/#tag/Start-generating/paths/~1v1~1text_to_image/post)

**Requirements:**

* `pip install runwayml`

**Parameters:**

* **`prompt_text`** (`pxt.String`): Text description of the image to generate.
* **`reference_images`** (`pxt.Json[(Image`): List of 1-3 reference images.
* **`model`** (`Any`): The model to use.
* **`ratio`** (`Any`): Aspect ratio of the generated image.
* **`seed`** (`Any`): Seed for reproducibility.
* **`model_kwargs`** (`Any`): Additional API parameters.

**Returns:**

* `pxt.Json`: A dictionary containing the response and metadata.

**Examples:**

Add a computed column that generates images from prompts:

```python  theme={null}
tbl.add_computed_column(
    response=text_to_image(
        tbl.prompt, [tbl.ref_image], model='gen4_image', ratio='16:9'
    )
)
tbl.add_computed_column(image=tbl.response['output'][0].astype(pxt.Image))
```

## <span style={{ 'color': 'gray' }}>udf</span>  text\_to\_video()

```python Signature theme={null}
@pxt.udf
text_to_video(
    prompt_text: pxt.String,
    model: pxt.String,
    ratio: pxt.String,
    *,
    duration: pxt.Int | None = None,
    audio: pxt.Bool | None = None,
    model_kwargs: pxt.Json | None = None
) -> pxt.Json
```

Generate videos from text prompts.

For additional details, see: [Text to video](https://docs.dev.runwayml.com/api/#tag/Start-generating/paths/~1v1~1text_to_video/post)

**Requirements:**

* `pip install runwayml`

**Parameters:**

* **`prompt_text`** (`pxt.String`): Text description of the video to generate.
* **`model`** (`pxt.String`): The model to use.
* **`ratio`** (`pxt.String`): Aspect ratio of the generated video.
* **`duration`** (`pxt.Int | None`): Duration in seconds.
* **`audio`** (`pxt.Bool | None`): Whether to generate audio.
* **`model_kwargs`** (`pxt.Json | None`): Additional API parameters.

**Returns:**

* `pxt.Json`: A dictionary containing the response and metadata.

**Examples:**

Add a computed column that generates videos from prompts:

```python  theme={null}
tbl.add_computed_column(
    response=text_to_video(
        tbl.prompt, model='veo3.1', ratio='16:9', duration=4
    )
)
tbl.add_computed_column(video=tbl.response['output'].astype(pxt.Video))
```

## <span style={{ 'color': 'gray' }}>udf</span>  video\_to\_video()

```python Signature theme={null}
@pxt.udf
video_to_video(
    video_uri: pxt.String,
    prompt_text: pxt.String,
    model: pxt.String,
    ratio: pxt.String,
    *,
    seed: pxt.Int | None = None,
    model_kwargs: pxt.Json | None = None
) -> pxt.Json
```

Transform videos with text guidance.

For additional details, see: [Video to video](https://docs.dev.runwayml.com/api/#tag/Start-generating/paths/~1v1~1video_to_video/post)

**Requirements:**

* `pip install runwayml`

**Parameters:**

* **`video_uri`** (`pxt.String`): HTTPS URL to the input video.
* **`prompt_text`** (`pxt.String`): Text description of the transformation.
* **`model`** (`pxt.String`): The model to use.
* **`ratio`** (`pxt.String`): Aspect ratio of the output video.
* **`seed`** (`pxt.Int | None`): Seed for reproducibility.
* **`model_kwargs`** (`pxt.Json | None`): Additional API parameters.

**Returns:**

* `pxt.Json`: A dictionary containing the response and metadata.

**Examples:**

Add a computed column that transforms videos:

```python  theme={null}
tbl.add_computed_column(
    response=video_to_video(
        tbl.video_url, 'Anime style', model='gen4_aleph', ratio='16:9'
    )
)
tbl.add_computed_column(video=tbl.response['output'].astype(pxt.Video))
```


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