From 46ee6abd5261be9e7e231cdf3752b6106b72d655 Mon Sep 17 00:00:00 2001
From: davidmyriel <davidmyriel@gmail.com>
Date: Mon, 25 Nov 2024 16:32:52 -0800
Subject: [PATCH] Update agentic-rag-crewai-zoom.md

---
 .../content/documentation/agentic-rag-crewai-zoom.md          | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/qdrant-landing/content/documentation/agentic-rag-crewai-zoom.md b/qdrant-landing/content/documentation/agentic-rag-crewai-zoom.md
index 3f1f98284..59fc4bd63 100644
--- a/qdrant-landing/content/documentation/agentic-rag-crewai-zoom.md
+++ b/qdrant-landing/content/documentation/agentic-rag-crewai-zoom.md
@@ -17,6 +17,8 @@ Traditional RAG systems focus on fetching data and generating responses, but the
 
 In this tutorial, we'll walk you through building an Agentic RAG system step by step. By the end, you'll have a working framework for storing data in a Qdrant Vector Database and extracting insights using CrewAI agents in conjunction with Vector Search over your data.
 
+We already built this app for you. [Clone this repository](https://github.com/qdrant/examples/tree/master/agentic_rag_zoom_crewai) and follow along with the tutorial. 
+
 ## What You'll Build
 In this hands-on tutorial, we'll create a system that:
 
@@ -148,7 +150,7 @@ When you run this script, you will be able to interact with the system through a
 
 ### The Data Pipeline
 
-At the heart of our system is the data processing pipeline. We use a singleton pattern to ensure efficient resource usage:
+At the heart of our system is the data processing pipeline:
 
 ```python
 class MeetingData: