Curious about how Retrieval Augmented Generation (RAG) enhances LLMs and cuts down on hallucinations? Join our livestream to demystify RAG and see it in action!
We'll kick off with a brief overview of RAG, followed by a live demo using the LangChain framework and Neo4j database. Then, dive deep with us as we build a retrieval query from scratch, uncovering the presenter’s techniques and testing methods.
Don't miss out on this chance to elevate your understanding of RAG and become proficient in building powerful retrieval queries!
Guest: Jennifer Reif, Neo4j
Blog: https://jmhreif.com/blog/2024/rag-demo-retrieval/
GraphRAG Demo Repository: https://github.com/neo4j-examples/rag-demo
Jennifers Podcast: https://jmhreif.podbean.com/
Get started with GraphRAG: https://bit.ly/3zDc2ty
0:00 - Introduction
3:23 - Introduction of Jennifer Reif
5:00 - Retrieval Queries and Vector Search
8:00 - Technical Demonstration
25:04 - Enhancing the Query
36:00 - Application Testing and Debugging
40:00 - Q&A and Discussion
57:57 - WrapUp
#neo4j #graphdatabase #rag #graphrag #vector #database #query