rhinojosa / graph-rag

Knowledge Graph RAG

Create a graph of interconnected documents and boost performance on RAG

1. Install Knowledge Graph RAG:

pip install knowledge_graph_rag

2. Create a Document Graph:

documents = ["Cardiovascular disease ...",
             "Emerging therapeutic interventions ...",
             "The epidemiological burden ...
             "Cardiovascular disease also ...",
             "Advanced imaging techniques, ...",
             "Role of novel biomarkers ..."
]

documents_graph = DocumentsGraph(documents=documents)
documents_graph.plot()

3. Find interconnected documents

documents_containing_connected_terminology = documents_graph.find_connected_documents(vectordb_search_result)
documents_containing_connected_terminology

[{'document': 'emerging therapeutic intervention ...'},
 {'document': 'management cardiovascular ...'},
 {'document': 'role novel biomarkers ...'}]