4 comments

[ 4.2 ms ] story [ 19.6 ms ] thread
What happens when your RAG system retrieves the wrong documents? Or when the retrieved context is not enough to answer the question?

A traditional RAG pipeline usually doesn't think twice and its path is so its a single attempt generated answer.

"Retrieve → Generate → Answer"

What I built

Retrieve → Reason → Verify → Correct → Answer

I created a collection of self contained notebooks demonstrating different Agentic RAG patterns with LangGraph. Each notebook focuses on a practical pattern that you can understand, experiment with and adapt to your own AI projects.

Free version: https://github.com/ChandulaSenevirathna/Agentic_RAG

Advanced version: https://chandula7.gumroad.com/l/Advanced_RAG_LangGraph_Patte...

Nice content i was on the look for some langgraph content. thnx
Important topic recently i was working on RAG project and traditional methods failed when the task was getting complex.
Exactly I faced the same thing thats why i made this content hope you will find some good use of it