AI Development Framework
3.2k 2026-04-26
GiovanniPasq/agentic-rag-for-dummies
A modular framework built with LangGraph for developing advanced Agentic RAG systems, offering both learning materials and an extensible architecture.
Core Features
Hierarchical Indexing for precise search and rich context.
Conversation Memory for natural, continuous dialogue.
Query Clarification with human-in-the-loop support.
Agent Orchestration and Multi-Agent Map-Reduce for complex queries.
Self-Correction and Context Compression for efficient processing.
Detailed Introduction
This project provides a comprehensive, modular framework for building Agentic RAG (Retrieval-Augmented Generation) systems using LangGraph. It addresses the gap in basic RAG tutorials by offering an extensible architecture and learning materials, enabling developers to quickly understand and implement advanced agent-driven RAG. Key features include hierarchical indexing, conversation memory, query clarification, and multi-agent orchestration, making it ideal for creating intelligent, self-correcting AI applications.