Implementing Agentic RAG using LangGraph, Groq & FastAPI

Author(s): A.Venkatesh

Originally published on Towards AI.

Retrieval-Augmented Generation (RAG) is evolving, and combining it with agentic decision-making unlocks even more powerful and context-aware systems.

In this post, we’ll walk through building an Agentic RAG system from scratch using:

This article explores the development of an Agentic RAG system, using various tools such as LangGraph, Groq, and FastAPI to create a dynamic agent that intelligently decides whether to answer questions directly or retrieve information from a database. The implementation covers various steps from project setup, document loading, and creating a stateful agentic workflow to enhance user interactions while ensuring efficient information retrieval and response generation.

Read the full blog for free on Medium.

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Published via Towards AI