> ## 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.

# Get Youtube Transcript Node

> Retrieve the transcript of a Youtube video

<img src="https://mintcdn.com/vectorshift/YP4-JQlrCs6FGFt3/images/platform/pipelines/data-loaders/youtube.png?fit=max&auto=format&n=YP4-JQlrCs6FGFt3&q=85&s=6247edb259beaaa42bc0da54a264a394" alt="Youtube Transcript Loader" width="1310" height="658" data-path="images/platform/pipelines/data-loaders/youtube.png" />

This node retrieves the transcript of a Youtube video, given the URL of the youtube video.

## Node Inputs

1. Youtube URL: The URL of the Youtube video you want to transcribe
   * Type: `Text`

## Node Parameters

In the gear:

1. Chunk Text: Chunk the articles returned
2. Chunk Size (if Chunk Text is set to True): The size of each chunks in tokens (1 token = 4 characters; default is 512 tokens)
3. Chunk Overlap  (if Chunk Text is set to True): The number of tokens of overlap between chunks (default is 0 tokens)

## Node Outputs

1. Content: Transcript of the youtube video
   * Type: `Text`
   * Example usage: `{{you_tube_0.content}}`

## Considerations

* Click on the “+” button on the right of the node to create and connect the node to a [semantic search node](/platform/pipelines/knowledge/semantic-search) to enable semantic search on the transcript.

## Example

The below example shows a pipeline that returns the transcripts of a youtube video based on a youtube link.

1. Text Node: Contains the Youtube URL
2. Youtube Node: Returns the transcript of the Youtube video based on a youtube link
   * Youtube URL: `{{text_0.text}}`
3. Output Node: Displays the transcript
   * Output: `{{you_tube_0.output}}`

<img src="https://mintcdn.com/vectorshift/YP4-JQlrCs6FGFt3/images/platform/pipelines/data-loaders/youtube-example.png?fit=max&auto=format&n=YP4-JQlrCs6FGFt3&q=85&s=e75ac62e95c7c41ce8afa70d68eafcda" alt="Youtube Example" width="1907" height="834" data-path="images/platform/pipelines/data-loaders/youtube-example.png" />
