outsystems-recursive-character-text-splitter
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OutSystems Recursive Character Text Splitter

Stable version 1.0.0 (Compatible with OutSystems 11)
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 on 23 April 2024
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5.0
 (3 ratings)
outsystems-recursive-character-text-splitter

OutSystems Recursive Character Text Splitter

Documentation
1.0.0
Overview:
The Outsystems Recursive Character Text Splitter asset provides a robust method for splitting text into manageable chunks based on defined criteria. Recursive text splitting is a valuable technique in various aspects of artificial intelligence (AI) and particularly in methods like Retrieval-Augmented Generation (RAG). This document outlines the functionality, parameters, and usage of the Recursive Character Text Splitter.

Functionality:
The Recursive Character Text Splitter operates on the principle of recursively breaking down input text into smaller segments until a specified condition is met. This allows for the creation of chunks that maintain semantic relevance, such as keeping paragraphs, sentences, or words together.

Usage:
To use the Recursive Character Text Splitter, follow these steps:
  1. Input Text: Provide the algorithm with the text you wish to split. This can be any piece of text, such as a paragraph or a document.
  2. Chunk Size Limit: Define the maximum size limit for each chunk of text. This parameter determines the threshold at which the text will be split into smaller segments.
  3. Recursive Process: The algorithm applies the splitting criteria recursively to the input text. It iteratively breaks down the text into smaller segments until the size limit for each chunk is reached.
  4. Output: Once the splitting process is complete, the Recursive Character Text Splitter returns a list of chunks. Each chunk includes the chunk text and the size of the chunk.

Conclusion

In conclusion, the Outsystems Recursive Character Text Splitter asset offers a powerful solution for splitting text into manageable chunks based on specified criteria. Its recursive approach ensures that chunks maintain semantic relevance, making it particularly useful in AI applications like Retrieval-Augmented Generation (RAG). By following the outlined steps, users can easily utilize this tool to split text efficiently. Overall, this asset provides a valuable tool for enhancing text processing capabilities in various AI applications.