Unlocking Vector Databases : Search and RAG with Vespa

In this workshop, we will dive in Vector Databases using Vespa, an open-source search engine and vector/tensor DB. The objective is to give participants tools to work on various use-cases form E-commerce search to recommendations and RAG.

The workshop is made of 6 main chapters :
- Introduction: 10km view of the use-cases and anti-use-cases for Vespa and why. Lab will be centered around CRUD
- Lexical Search: query syntax, boolean clauses, ranking for product search
- Grouping: facets for data exploration on sales data and result diversification
- Tensors: use tensor math for recommendations and vector search on an E-commerce dataset
- Hybrid Search: generate embeddings on the fly; use RRF; implement RAG
- Performance and scaling: intro to how Vespa scales; typical performance bottlenecks

Each chapter is composed of :
- a short introduction to the topic
- a lab that will be solved in small groups, working on a pre-defined dataset
- a debriefing with the large group
- short wrap-up

Host or Publisher datacraft