This article explores how to implement a retriever over a knowledge graph containing structured information to power RAG (Retrieval-Augmented Generation) applications.
Learn about the LLM Knowledge Graph Builder, an online tool that uses machine learning models to transform unstructured data into a knowledge graph. This tool is integrated with a Retrieval-Augmented Generation (RAG) chatbot and is part of Neo4j's GraphRAG Ecosystem Tools.
This article explains how to import GEDCOM files containing genealogy/ancestry data into Neo4j using AuraDB Free. It includes step-by-step instructions for pre-processing the data with Python, importing the data into Neo4j, and exploring the data using the Neo4j Browser and Neo4j Bloom. The article also provides code examples for adding new relationships to the data and styling the graph visualization.
