The GraphRAG library is integrated into Neo4j to generate natural language summaries of communities of entities and relationships found in a knowledge graph. After constructing the knowledge graph, the GraphRAG library uses Leiden community detection algorithm and LLM prompting to extract relevant information. The extracted data can be stored in Neo4j for downstream analysis, visualization, and retrieval. A high-level indexing pipeline is implemented, allowing users to skip the graph extraction process. The dataset used is "A Christmas Carol" by Charles Dickens, which is freely accessible via the Gutenberg Project. The authors tested different configuration options, such as entity types and max gleanings value, to optimize the extraction process. They also evaluated the performance of the GraphRAG library using metrics like entity count distribution, node degree distribution, and community size per hierarchical level. To retrieve relevant information from the extracted data, a local retriever is implemented using LangChain and LlamaIndex orchestration frameworks. The global retriever architecture is also demonstrated, which iterates over all communities on a specified hierarchical level to generate intermediate summaries and a final response.