<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Splitters on Dapr Docs</title><link>https://docs.dapr.io/developing-ai/dapr-agents/integrations/splitters/</link><description>Recent content in Splitters on Dapr Docs</description><generator>Hugo</generator><language>en</language><atom:link href="https://docs.dapr.io/developing-ai/dapr-agents/integrations/splitters/index.xml" rel="self" type="application/rss+xml"/><item><title>Text</title><link>https://docs.dapr.io/developing-ai/dapr-agents/integrations/splitters/text/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://docs.dapr.io/developing-ai/dapr-agents/integrations/splitters/text/</guid><description>&lt;p>The Text Splitter module is a foundational integration in Dapr Agents designed to preprocess documents for use in &lt;a href="https://en.wikipedia.org/wiki/Retrieval-augmented_generation">Retrieval-Augmented Generation (RAG)&lt;/a> workflows and other in-context learning applications. Its primary purpose is to break large documents into smaller, meaningful chunks that can be embedded, indexed, and efficiently retrieved based on user queries.&lt;/p>
&lt;p>By focusing on manageable chunk sizes and preserving contextual integrity through overlaps, the Text Splitter ensures documents are processed in a way that supports downstream tasks like question answering, summarization, and document retrieval.&lt;/p></description></item></channel></rss>