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

# Split Text Node

> Split text based on a delimiter

<img alt="Split Text Node" classname="w-full" src="https://mintcdn.com/vectorshift/B2X2zpDX7crEnhCG/images/platform/pipelines/data-transformation/split-text.png?fit=max&auto=format&n=B2X2zpDX7crEnhCG&q=85&s=c47e79710e5de1959c0b40ffdbecf88f" width="663" height="409" data-path="images/platform/pipelines/data-transformation/split-text.png" />

This node takes input text and separates it into a list of texts based on the delimiter.

It is often used when splitting a large text into smaller pieces, and then performing operations on each item in the list.

## Node Inputs

1. Text for splitting: The text for splitting
   * Type: `Text`

If Delimiter is Character(s):

1. Character: The character for splitting
   * Type: `Text`

## Node Parameters

On the face of the node:

1. Delimiter: The type of delimiter for splitting. The available options are Space, New Line and Character(s). The default option is Space.
   * Type: `Dropdown`

## Node Outputs

1. Processed Text: The text is split by the delimiter and outputted in List format
   * Type: `List<Text>`
   * Example usage: `{{split_text_0.processed_text}}`

## Example

The below example shows a pipeline that takes in a text and splits it into a list of texts based on the delimiter.

1. Text Node: Contains the text "apples,oranges,peaches"
2. Split Text Node: Splits the text into a list of texts based on the delimiter
   * Text for splitting: `{{text_0.text}}`
   * Delimiter: `Character(s)`
   * Character: `,`
3. Output: display the new text
   * Output: `{{split_text_0.processed_text}}`

<img src="https://mintcdn.com/vectorshift/B2X2zpDX7crEnhCG/images/platform/pipelines/data-transformation/split-text-example.png?fit=max&auto=format&n=B2X2zpDX7crEnhCG&q=85&s=d25a214dd76e8aa9d14a79cdaefba71e" alt="Split Text Example" width="1904" height="834" data-path="images/platform/pipelines/data-transformation/split-text-example.png" />
