From 1fc6d3c945f437bbc7ffbf8da5641815194c2d44 Mon Sep 17 00:00:00 2001 From: Marco Minerva Date: Thu, 31 Oct 2024 15:25:06 +0100 Subject: [PATCH] Update README: Add note on vector storage with Dapper The README.md file has been updated to include a new note about how vectors are saved and retrieved using direct SQL queries with Dapper. Additionally, it provides a link to the master branch for those who prefer to use Entity Framework Core instead. This addition helps clarify the technologies used and offers options for different preferences. --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index b6c49b9..e0d2f62 100644 --- a/README.md +++ b/README.md @@ -6,6 +6,9 @@ A repository that showcases the native VECTOR type in Azure SQL Database to perf The application is a Minimal API that exposes endpoints to load documents, generate embeddings and save them into the database as Vectors, and perform searches using Vector Search and RAG. Currently, only PDF files are supported. Embedding and Chat Completion are integrated with [Semantic Kernel](https://github.com/microsoft/semantic-kernel). +> [!NOTE] +> Vectors are saved and retrieved using direct SQL queries using [Dapper](https://github.com/DapperLib/Dapper). If you prefer to use Entity Framework Core, check out the [master branch](https://github.com/marcominerva/SqlDatabaseVectorSearch/tree/sql). + ![SQL Database Vector Search](https://github.com/marcominerva/SqlDatabaseVectorSearch/blob/master/SqlDatabaseVectorSearch.png) ### Setup