Module Overview
In this module, you will setup and use the Neo4j GraphRAG for Python package to:
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Create and configure a vector retriever.
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Perform semantic search using a vector index.
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Build a GraphRAG pipeline that uses retrievers to give context to an LLM.
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Use graph traversal in combination with vector search for enhanced retrieval.
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Implement text-to-Cypher retrieval for natural language querying.
In addition, you will explore popular GenAI frameworks for integrating with Neo4j, such as LangChain and LlamaIndex.
If you are ready, let’s get going!