Implementing Agentic RAG using LangGraph, Groq & FastAPI
Last Updated on August 28, 2025 by Editorial Team
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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