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HKUDS/LightRAG

LightRAG is a simple and fast framework for Retrieval-Augmented Generation, designed to enhance LLM performance with external knowledge.

Core Features

Simple and fast RAG implementation.

Supports various storage backends including OpenSearch.

Offers local deployment of components (embedding, reranking, storage) via Docker.

Integrates RAGAS for evaluation and Langfuse for tracing.

Scalable for large-scale datasets and supports multimodal data via RAG-Anything.

Quick Start

pip install lightrag-hku

Detailed Introduction

LightRAG is an advanced open-source framework for Retrieval-Augmented Generation (RAG), focusing on simplicity and speed. It empowers Large Language Models (LLMs) by efficiently integrating external knowledge, thereby improving accuracy and reducing hallucinations. Key features include support for diverse storage solutions like OpenSearch, seamless local deployment with Docker, and robust integrations for evaluation (RAGAS) and tracing (Langfuse). Designed for scalability, LightRAG efficiently handles large datasets and extends its capabilities to multimodal data through RAG-Anything, making it a versatile tool for building high-performance AI applications.