Building Your Own Agentic RAG Systems with Llama-Index | Router Query Engines #1

Are you tired of the same old RAG (Retrieval Augmented Generation) systems? Ready to take your AI development skills to the next level? In this video, we'll dive into the exciting world of Agentic RAG systems, introducing agents into the well-defined RAG system workflow.

Github Repo: https://github.com/Princekrampah/agentic_rag_llamaIndex_tutorial
Medium Article: https://medium.com/aimonks/agentic-rag-with-llama-index-router-query-engine-01-381e83a418af

Last year was all about RAG systems, but this year, it's all about agents! Don't worry if you missed the RAG buzz era; you can still catch up and even enhance your systems with agents. We'll start by implementing a basic Agentic RAG application using Llama-index.

📚 What You'll Learn:

A quick refresher on traditional RAG architectures
The limitations of simple RAG implementations
How agents can enhance RAG systems for complex tasks like document summarization and advanced QA
Introduction to Router Query Engines and their role in Agentic RAG systems
This video is the first in a series where we'll explore various Agentic RAG architectures. Whether you're a beginner or looking to upgrade your current RAG systems, this tutorial is perfect for you.

🔗 Resources:

Check out my blog for detailed articles on RAG and Agentic RAG systems: https://medium.com/aimonks/agentic-rag-with-llama-index-router-query-engine-01-381e83a418af

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Thank you for watching and see you in the next video!!

Видео Building Your Own Agentic RAG Systems with Llama-Index | Router Query Engines #1 канала Code With Prince
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