I created NewsGraphRAG as a personal deep-dive to explore the boundaries of hybrid local retrieval systems. Built entirely for free and running fully locally on your machine, this project demonstrates how graph databases unlock multi-hop reasoning that traditional flat vector databases simply can't handle. By combining spaCy and Ollama (llama3.2) for a two-stage NER pipeline and using Neo4j's built-in vector index, the system extracts interconnected entities from news articles and successfully traverses relationship paths to answer complex queries with high traceability.

Check out my latest project exploring local GraphRAG systems:

Building a Local Knowledge Graph RAG System for News Analysis with Neo4j and Ollama

How graph databases unlock multi-hop reasoning that vector databases simply can't do — built entirely for free, running entirely on your machine

The Problem with Traditional RAG