Securing Your LangChain-Based RAG Agent Using Okta FGA

Generative Artificial Intelligence (GenAI) has significantly impacted software development, particularly with Retrieval-Augmented Generation (RAG) applications that enhance Large Language Models (LLMs) by providing context through data retrieval from databases or search engines. Ensuring security in these systems is crucial, as traditional Role-Based Access Control (RBAC) methods are insufficient. Fine-Grained Authorization (FGA) offers a solution. This tutorial guides you through building a LangChain-based RAG agent and securing it with Okta FGA, covering setup, configuration, and testing.