Art Tourguide with LightRAG
For knowledge retrieval, this tutorial uses LightRAG which is knowledge graph based RAG implementation. Compared to GraphRAG, LightRAG is more accurate for single topic datasets, and uses 1,000x less tokens for retrieval. Furthermore, documents can be added to LightRAG incrementally without rebuilding the knowledge graph. See the full results in the paper. For the agent itself, we use LangGraph.
About this tutorial
This hands-on Jupyter notebook is part of GenAI Agents, a free open-source repository by Nir Diamant covering ai agents techniques with runnable code examples and detailed explanations.
RAG Made Simple
Nir Diamant's complete visual guide to Retrieval-Augmented Generation — essential for any GenAI engineer building systems that retrieve and ground responses on real data.
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