Neon Serverless Postgres Connector for Microsoft Semantic Kernel

Introduction

Introducing the Neon Serverless Postgres Connector for Microsoft Semantic Kernel, allowing developers to seamlessly integrate Neon’s serverless Postgres capabilities with AI-driven vector search and retrieval workflows.

Why Use Neon for Semantic Kernel?

Neon is a fully managed Serverless Postgres solution with a native integration for Microsoft Azure, providing high-performance and scalable vector search capabilities.

Getting Started

Prerequisites

Ensure you have a free Neon account to start using Neon with Semantic Kernel.

Setting Up Your Neon Database

Create a new Neon project in the Neon Console and enable the pgvector extension to enable vector store functionality.

Implementing Vector Store Retrieval-Augmented Generation (RAG)

Utilize examples from the provided GitHub repository to incorporate Neon Serverless Postgres with a .NET console app for RAG workflows and efficient searching.

Loading Data into Neon

Use commands to fetch, create a database schema in Neon, and embed papers related to RAG into the Neon Postgres vector store for searching.

Querying Data from Neon

After loading data, search for relevant papers based on specific queries using OpenAI embeddings and semantic search capabilities.

Next Steps

Try the example project to explore Neon-powered AI search and scale your AI workflows with serverless database solutions using Neon Serverless Postgres and Microsoft Semantic Kernel.

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Summary with Markdown Formatting

Introduction

Introducing the Neon Serverless Postgres Connector for Microsoft Semantic Kernel, enabling seamless integration of Neon's serverless Postgres capabilities with AI-driven vector search workflows.

Why Use Neon for Semantic Kernel?

• Neon offers a fully managed Serverless Postgres solution with native integration for Microsoft Azure.
• Branching feature allows creating isolated data copies for development and testing.

Getting Started

Prerequisites

Ensure you have a free Neon account before starting with Semantic Kernel.

Setting Up Your Neon Database

1. Create a new Neon project in the Neon Console.
2. Enable the pgvector extension in the Neon SQL editor.

Implementing Vector Store Retrieval-Augmented Generation (RAG)

Utilize the provided GitHub repository for examples on combining Neon Serverless Postgres with a .NET console app for RAG workflows.

Loading Data into Neon

• Fetch, create a database schema, and embed papers related to RAG in the Neon Postgres vector store using specific commands.

Querying Data from Neon

Search for relevant papers based on queries, employing OpenAI embeddings and semantic search capabilities.

Next Steps

• Experiment with the example project for Neon-powered AI search.
• Scale AI workflows using Neon Serverless Postgres and Microsoft Semantic Kernel integration.