| ▲ | 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. | ||||||||
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| ▲ | GeorgeTj a day ago | parent | prev | next [-] | |||||||
Useful content for my current project thanx for posting | ||||||||
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| ▲ | Pasannn a day ago | parent | prev [-] | |||||||
nice content very informative keep it up | ||||||||
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