I put together four self contained notebooks exploring different ways to make a RAG pipeline more agentic.
Instead of retrieving once and immediately generating an answer this methods show patterns where the system can perform the following
* decide whether retrieval is needed
* where to retrieve from
* evaluate retrieved context
* correct or retry when the context isn't sufficient
* defer to a human
Each notebook focuses on a different pattern and is intended to be runnable and easy to experiment with.
Delta000•36m ago
Instead of retrieving once and immediately generating an answer this methods show patterns where the system can perform the following
* decide whether retrieval is needed * where to retrieve from * evaluate retrieved context * correct or retry when the context isn't sufficient * defer to a human
Each notebook focuses on a different pattern and is intended to be runnable and easy to experiment with.
The notebooks are free to explore on GitHub https://github.com/ChandulaSenevirathna/Agentic_RAG
I also put together a more complete version with all four implementations and explanations here https://chandula7.gumroad.com/l/Advanced_RAG_LangGraph_Patte...
Would be interested in feedback on which Agentic RAG pattern people are finding most useful in real projects.