LightRAG is a lightweight, efficient Retrieval-Augmented Generation (RAG) system designed for fast and scalable knowledge retrieval and generation. It supports multiple retrieval modes, including local, global, hybrid, and mix, integrating both structured knowledge graphs and unstructured vector search for comprehensive answers. Key features include multi-file type support (PDF, DOC, PPT, CSV), custom knowledge graph integration, and advanced query capabilities with citation functionality. LightRAG is compatible with various storage solutions like Neo4J, PostgreSQL, and Faiss, and supports LLM models from OpenAI, Hugging Face, and Ollama. It also offers a user-friendly GUI for document indexing, querying, and graph visualization. Designed for simplicity and speed, LightRAG is ideal for applications requiring efficient knowledge extraction and generation.