> ## Documentation Index
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> Use this file to discover all available pages before exploring further.

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# twelvelabs

> <a href="https://github.com/pixeltable/pixeltable/blob/main/pixeltable/functions/twelvelabs.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.twelvelabs

Pixeltable UDFs
that wrap various endpoints from the TwelveLabs API. In order to use them, you must
first `pip install twelvelabs` and configure your TwelveLabs credentials, as described in
the [Working with TwelveLabs](https://docs.pixeltable.com/howto/providers/working-with-twelvelabs) tutorial.

## <span style={{ 'color': 'gray' }}>udf</span>  embed()

```python Signatures theme={null}
# Signature 1:
@pxt.udf
embed(
    text: pxt.String,
    image: pxt.Image | None,
    model_name: pxt.String
) -> pxt.Array[float32] | None

# Signature 2:
@pxt.udf
embed(
    image: pxt.Image,
    model_name: pxt.String
) -> pxt.Array[float32] | None

# Signature 3:
@pxt.udf
embed(
    audio: pxt.Audio,
    model_name: pxt.String,
    start_sec: pxt.Float | None,
    end_sec: pxt.Float | None,
    embedding_option: pxt.Json[(String, ...)] | None
) -> pxt.Array[float32] | None

# Signature 4:
@pxt.udf
embed(
    video: pxt.Video,
    model_name: pxt.String,
    start_sec: pxt.Float | None,
    end_sec: pxt.Float | None,
    embedding_option: pxt.Json[(String, ...)] | None
) -> pxt.Array[float32] | None
```

Creates an embedding vector for the given text, audio, image, or video input.

Each UDF signature corresponds to one of the four supported input types. If text is specified, it is possible to
specify an image as well, corresponding to the `text_image` embedding type in the TwelveLabs API. This is
(currently) the only way to include more than one input type at a time.

Equivalent to the TwelveLabs Embed API:
[https://docs.twelvelabs.io/v1.3/docs/guides/create-embeddings](https://docs.twelvelabs.io/v1.3/docs/guides/create-embeddings)

Request throttling:
Applies the rate limit set in the config (section `twelvelabs`, key `rate_limit`). If no rate
limit is configured, uses a default of 600 RPM.

**Requirements:**

* `pip install twelvelabs`

**Parameters:**

* **`model_name`** (`String`): The name of the model to use. Check
  [the TwelveLabs documentation](https://docs.twelvelabs.io/v1.3/sdk-reference/python/create-embeddings-v-1/create-text-image-and-audio-embeddings)
  for available models.
* **`text`** (`String`): The text to embed.
* **`image`** (`Image | None`, default: `Literal(None)`): If specified, the embedding will be created from both the text and the image.

**Returns:**

* `pxt.Array[float32] | None`: The embedding.

**Examples:**

Add a computed column `embed` for an embedding of a string column `input`:

```python  theme={null}
tbl.add_computed_column(
    embed=embed(model_name='marengo3.0', text=tbl.input)
)
```


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