What is GraphRAG?

Example

A plot search finds a film. The graph around that film holds its cast and its genres.

cypher

MATCH (movie:Movie)
  SEARCH movie IN (
    VECTOR INDEX moviePlots
    FOR $queryVector
    LIMIT 4
  ) SCORE AS similarityScore
RETURN
  movie.title AS title, movie.plot AS plot, similarityScore,
  collect { MATCH (movie)-[:IN_GENRE]->(g) RETURN g.name } AS genres,
  collect { MATCH (movie)<-[:ACTED_IN]-(a) RETURN a.name } AS actors

The search finds four films by plot alone. Following [:IN_GENRE] and [:ACTED_IN] out from each one adds its genres and its cast. The model receives all of it.

Lessons that use this term

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44 lessons use this term. The 40 with the highest term density are listed here.

Using Neo4j with LangChain6 mentions

Graph RetrievalVectorscan enhance a vector retriever using GraphRAG to include additional4 mentions
Additional DataVectorsthis optional challenge, you can explore how adding additional data to the GraphRAG retriever can improve the agent's responses to more complex1 mention
Simple LangChain AgentNeo4j and LangChainthe agent to query a Neo4j graph database, retrieve information using RAG and GraphRAG, and dynamically generate Cypher queries based on user1 mention

Neo4j and Generative AI Workshop17 mentions

GraphRAG for PythonGenerative AIThe GraphRAG for Python package (neo4j-graphrag) allows you to access3 mentions
GraphRAG?Generative AI(Graph Retrieval Augmented Generation) is an approach that uses the strengths of graph databases to provide relevant7 mentions
Add structured data to the knowledge graphKnowledge Graph ConstructionThe unstructured part of your graph is known as the Lexical Graph, while the structured part is known as the [Domain2 mentions
Extracting a schema from textKnowledge Graph ConstructionThe GraphRAG for Python package (neo4j-graphrag) allows you to access1 mention
Search lesson contentAgents"What are the benefits of using GraphRAG?" "How are Knowledge Graphs associated with other1 mention
Query databaseAgentsWhat are the benefits of using GraphRAG1 mention
What is a Knowledge GraphGenerative AIcan use knowledge graphs for context, forming the foundation for applications that leverage proprietary or1 mention
Vector + Cypher retrieverRetrievalHow can I use GraphRAG in my Generative AI1 mention

Neo4j & GenerativeAI Fundamentals14 mentions

GraphRAGRetrieval Augmented Generation (RAG)GraphRAG (Graph Retrieval Augmented Generation) is an approach that uses the strengths of graph databases to provide relevant7 mentions
GraphRAG for PythonIntegrating Neo4j with Generative AIGraphRAG for Python package (neo4j-graphrag) allows you to access3 mentions
RAG PipelineIntegrating Neo4j with Generative AIthe GraphRAG pipeline to use the vector2 mentions
What is a Knowledge GraphKnowledge Graphscan use knowledge graphs for context, forming the foundation for applications that leverage proprietary or1 mention
Graph-Enhanced Vector RetrieverIntegrating Neo4j with Generative AI"Find the highest rated action movie about travelling to other planets", the GraphRAG pipeline will follow these1 mention

GraphRAG Hackathon16 mentions

Hack TimeTime to BuildMCP server — it knows Neo4j, Cypher, graph modeling, and how to structure a GraphRAG4 mentions
Introducing the GraphRAG hackathonIntroduction to GraphRAGthis hackathon, you will build a GraphRAG application — an AI system that uses a knowledge graph to give LLMs accurate, connected, contextual2 mentions
Querying with CypherIntroduction to GraphRAGto keep your graph performant Traverse multi-hop paths — the foundation of GraphRAG2 mentions
Understanding GraphRAGIntroduction to GraphRAGcombines graph traversal with vector search to give LLMs richer4 mentions
Understanding Neo4jIntroduction to GraphRAGyou will use to store and query the knowledge graph at the heart of your GraphRAG1 mention
Getting StartedGet Started with Aurarelationship types, and property patterns | | neo4j-graphrag-skill | Build GraphRAG retrieval pipelines backed by a Neo4j knowledge graph | | neo4j-vector-index-skill | Create and query vector indexes2 mentions

Constructing Knowledge Graphs with Neo4j GraphRAG for Python6 mentions

Add structured data to the knowledge graphKnowledge Graph PipelineThe unstructured part of your graph is known as the Lexical Graph, while the structured part is known as the [Domain2 mentions
Extracting a schema from textKnowledge Graph PipelineGraphRAG for Python package (neo4j-graphrag) allows you to access Neo4j Generative AI1 mention
Text to Cypher retrieverRetrieval1 mention
Set up your development environmentIntroductionGraphRAG for Python (neo4j_graphrag) package to create a knowledge graph from unstructured and structured data Create1 mention
Vector + Cypher retrieverRetrieval1 mention

Building Agents in Neo4j Aura3 mentions

Next StepsPublishing Agentsto connect AI applications to Neo4j tools and data sources Building GraphRAG Python MCP tools — Build your own GraphRAG MCP server with graph-backed3 mentions

Neo4j Agent Memory Workshop2 mentions

The Starting AgentIntroduction to Agent Memory| A GraphRAG search: it matches lesson passages by meaning, then traverses to the entities connected to each1 mention

Building GraphRAG Python MCP tools5 mentions

Add Neo4j ConnectionBuilding Database-Connected Featuresthis challenge, you will build a Movies GraphRAG Server that uses lifespan management to establish and maintain a connection to a Neo4j2 mentions
Create a Movie ResourceBuilding Database-Connected Featuresthis challenge, you will add a resource to your Movies GraphRAG Server that exposes detailed movie information by its1 mention
Build a GraphRAG ToolBuilding Database-Connected Featuresfrom the graph to provide relevant context to the LLM - the essence of GraphRAG1 mention

Developing with Neo4j MCP Tools2 mentions

Congratulations!Using Neo4j MCP ToolsNeo4j GraphRAG Developer Guide Official MCP1 mention
Summary & Next StepsUsing Neo4j MCP ToolsIntelligence: Knowledge graphs and GraphRAG provide practical ways to enhance AI applications with structured1 mention

Building GraphRAG TypeScript MCP tools4 mentions

Create a Movie ResourceBuilding Database-Connected Featuresthis challenge, you will add a resource to your Movies GraphRAG Server that exposes detailed movie information by its1 mention
Build a GraphRAG ToolBuilding Database-Connected Featuresfrom the graph to provide relevant context to the LLM - the essence of GraphRAG1 mention
Add Neo4j ConnectionBuilding Database-Connected Featuresthis challenge, you will build a Movies GraphRAG Server that creates a Neo4j driver at module scope and uses it in a tool1 mention

Building Knowledge Graphs with LLMs4 mentions

Querying using CypherExploring your knowledge graph| mentions | | --- | --- | | Neo4J | 10 | | vector search | 10 | | LLM | 9 | | GraphRAG | 9 | | retriever | 73 mentions
Neo4j LLM Graph BuilderLLM Graph BuilderAugmented Generation (RAG) approaches to answer questions, including GraphRAG, Vector Search, and1 mention

AI on Your Lakehouse: Context Comes in Shapes, Not Queries1 mention

Port the PatternPort the PatternNeo4j & GenAI Fundamentals for retrievers and GraphRAG, Community Detection to go deeper on Leiden and1 mention

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