<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Search on The Smoking Duck Blog</title><link>https://blog.aabouzied.com/blog/search/</link><description>Recent content in Search on The Smoking Duck Blog</description><generator>Hugo</generator><language>en-US</language><copyright>Copyright © 2021, Ahmed Abouzied.</copyright><lastBuildDate>Wed, 07 Oct 2026 04:34:55 +0200</lastBuildDate><atom:link href="https://blog.aabouzied.com/blog/search/index.xml" rel="self" type="application/rss+xml"/><item><title>An Experiment with RAG Search Accuracy</title><link>https://blog.aabouzied.com/experiment-rag-search-accuracy/</link><pubDate>Fri, 20 Dec 2024 06:30:13 +0000</pubDate><guid>https://blog.aabouzied.com/experiment-rag-search-accuracy/</guid><description>&lt;h2 id="overview"&gt;Overview&lt;/h2&gt;&#10;&lt;p&gt;In a previous article, we explored the foundations of a basic Retrieval-Augmented Generation (RAG) system by building a straightforward implementation and loading it with articles from the Go blog. This simple setup allowed us to test the concept of enhancing search accuracy by combining a document corpus with advanced retrieval techniques.&lt;/p&gt;&#10;&lt;p&gt;Now, we’re taking that experiment further. In this article, we’ll delve into optimizing RAG search accuracy through more advanced techniques and comparisons. Specifically, we’ll discuss:&lt;/p&gt;</description></item></channel></rss>