An embedding subsystem is one of four subsystems needed to implement Retrieval Augmented Generation. It turns your custom corpus into a database of vectors that can be searched for semantic meaning. The other subsystems are the data pipeline for creating your custom corpus, the retriever for querying the vector database to add more context to a user query, and finally,

This tutorial guides you through constructing robust data pipelines on the edge, ensuring flexibility and scalability. Learn to create, populate, and transform datasets seamlessly while prioritizing data privacy. Master the art of automation with MinIO's Python SDK.