Building RAG Applications With the Neo4j GenAI Stack: A Comprehensive Guide

The GenAI Stack is a pre-built development environment created by Neo4j in collaboration with Docker, LangChain, and Ollama for creating Generative AI (GenAI) applications. It focuses on improving the accuracy, relevance, and provenance of generated responses in Large Language Models (LLMs) through Retrieval Augmented Generation (RAG). The stack includes application containers with Python and LangChain, a database container with Neo4j for vector index and graph search, and an LLM container with Ollama. Key features include information retrieval enhancement using RAG, components such as the database container, functionality to import and embed data, perform queries using vector and graph search, generate new content in the style of existing high-quality data, trust and verification through RAG applications, and customization options like changing parameters of LLMs and creating customized retrievers. The GenAI Stack offers a robust and efficient platform for creating sophisticated GenAI applications, aiding developers in rapid development, testing, and deployment of GenAI applications.