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Displaying posts with tag: rag (reset)
Building Applications with MySQL AI

We recently announced the availability of MySQL AI which enables predictive and generative AI workflows for on-premise MySQL customers. MySQL AI includes built-in LLMs and embedding models that run on CPUs, a vector store, semantic search functions, automated machine learning and a graphical console called MySQL studio. Since its release there has been considerable interest […]

Build a RAG System with LangChain and MySQL HeatWave GenAI

Retrieval-Augmented Generation (RAG) is a powerful technique that enhances the capabilities of Large Language Models (LLMs) for enterprise data. By grounding the model in information from your vector store/knowledge base, RAG helps produce more accurate, relevant, and trustworthy answers. MySQL HeatWave is a fully managed MySQL database service that combines transactions, analytics, machine learning, and […]

Scoped Vector Search with the MyVector Plugin for MySQL – Part I


Semantic Search with SQL Simplicity and Operational Control

Introduction

Vector search is redefining how we work with unstructured and semantic data. Until recently, integrating it into traditional relational databases like MySQL required external services, extra infrastructure, or awkward workarounds. That changes with the MyVector plugin — a native vector indexing and search extension purpose-built for MySQL.

Whether you’re enhancing search for user-generated content, improving recommendation systems, or building AI-driven assistants, MyVector makes it possible to store, index, and search vector embeddings directly inside MySQL — with full support for SQL syntax, indexing, and filtering.

What Is MyVector?

The MyVector plugin adds native support …

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