# LightRAG Framework Overview

## What is LightRAG?

**LightRAG** is a Simple and Fast Retrieval-Augmented Generation framework. LightRAG was developed by HKUDS (Hong Kong University Data Science Lab). The framework provides developers with tools to build RAG applications efficiently.

## Problem Statement

Large language models face several limitations. LLMs have a knowledge cutoff date that prevents them from accessing recent information. Large language models generate hallucinations when providing responses without factual grounding. LLMs lack domain-specific expertise in specialized fields.

## How LightRAG Solves These Problems

LightRAG solves the hallucination problem by combining large language models with external knowledge retrieval. The framework ensures accurate responses by grounding LLM outputs in actual documents. LightRAG provides contextual responses that reduce hallucinations significantly. The system enables efficient retrieval from external knowledge bases to supplement LLM capabilities.

## Core Benefits

LightRAG offers accuracy through document-grounded responses. The framework provides up-to-date information without model retraining. LightRAG enables domain expertise through specialized document collections. The system delivers cost-effectiveness by avoiding expensive model fine-tuning. LightRAG ensures transparency by showing source documents for each response.