Neo4j Live: Building Model Native Apps With Hypermode & Neo4j

It's clear that the future of application development will involve AI models and that frameworks must adapt to expose the right abstractions for working with AI. In this episode of Neo4 Live we explore the open source Modus API framework and the building blocks of model-native app development: chaining data and LLMs together, LLM tool use, and knowledge graph RAG. We'll see how to get started with Modus and Neo4j and add a GraphRAG feature to a Modus + Neo4j model-native app. Guest: Will Lyon Modus on GitHub: https://github.com/hypermodeinc/modus Hypermode: https://hypermode.com/home Neo4j + Modus blog: https://hypermode.com/blog/neo4j-support-modus Neo4j + Modus docs: https://docs.hypermode.com/modus/sdk/assemblyscript/neo4j Slides: https://hyp.foo/neo4j-live-slides Code: https://hyp.foo/recipes Full Stack GraphQL Applications: https://www.manning.com/books/fullstack-graphql-applications Building Knowledge Graphs with LLMs: https://graphacademy.neo4j.com/courses/llm-knowledge-graph-construction/ GraphRAG: https://graphrag.com/ 0:00 - Introduction & Welcome to Neo4j Live 6:41 - Understanding AI, Knowledge Graphs & Agentic Workflows 13:08 - Introduction to Modus: A Model-Native API Framework 24:06 - Hands-On: Getting Started with Modus & GraphQL API 33:35 - Building AI-Powered Apps with Function Calling & LLMs 46:02 - Knowledge GraphRAG: Enhancing AI with Neo4j 52:28 - Live Demo: Movie Recommendations with Neo4j & Vector Search 58:48 - Q&A: Use Cases, Next Steps & Community Engagement 1:00:42 - WrapUp #neo4j #graphdatabase #graphrag #genai #llm #hypermode #modus #appdevelopment