The GenAI Stack is a pre-built development environment created by Neo4j in collaboration with Docker, LangChain, and Ollama. It focuses on improving the accuracy, relevance, and provenance of generated responses in Large Language Models (LLMs) through Retrieval Augmented Generation (RAG).
Table of contents
Typical Process for RAG ApplicationsNeo4j Components in LangChainConfigurationChange Parameters of LLMInitialize Neo4jVector StoreBuilt-in Search TypesMethods of Neo4jVector InitializationNeo4j RetrieverLoad Embedding ModelLoad Generation ModelQuery Related to Retrieval/Search TypesDefine Prompt TemplateInitialize a Base QA Chain InstanceInitialize A RAG QA ChainCustomize R etrieval StrategyAdding Structure-Aware Retrieval to GenAI StackGenerate AnswersAdvanced RAG StrategiesNeo4j x LangChain: Deep dive into the new Vector index implementationQuery Neo4j Graph DatabaseGenerate Cypher Query from Question2 Impressions