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Practical Agentic RAG patterns implemented with LangGraph(github.com)
8 points by Delta000 a day ago | 7 comments
Delta000 a day ago | parent | next [-]

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...

Razer99 a day ago | parent | prev | next [-]

Hey thankyou for the info, I was wondering if you can add a notebook about supervisor agent as well.

Delta000 a day ago | parent [-]

Hi, yes i am currently working on that pattern as well it will be added as well

GeorgeTj a day ago | parent | prev | next [-]

Useful content for my current project thanx for posting

Delta000 a day ago | parent [-]

Glad this helped you

Pasannn a day ago | parent | prev [-]

nice content very informative keep it up

Delta000 a day ago | parent [-]

Thankyou