From bb3e794a29b6449ca7b30390f1e8a0e5b1824c20 Mon Sep 17 00:00:00 2001 From: Marco Minerva Date: Tue, 5 Nov 2024 11:25:45 +0100 Subject: [PATCH] Update README: clarify EFCore usage and SQL note The README.md file has been updated to specify that Vectors are saved and retrieved using the `EFCore.SqlServer.VectorSearch` library with Entity Framework Core. Additionally, the note about using straight SQL has been moved to a separate section and rephrased for better clarity. --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index e127a80..94ca5cc 100644 --- a/README.md +++ b/README.md @@ -4,10 +4,10 @@ A repository that showcases the native VECTOR type in Azure SQL Database to perf > [!IMPORTANT] > Usage of this application requires the Vector support feature in Azure SQL Database or Managed Instance, currently in EAP. [See this blog post](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/) for more details. -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). +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. Vectors are saved and retrieved with Entity Framework Core using the [EFCore.SqlServer.VectorSearch](https://github.com/efcore/EfCore.SqlServer.VectorSearch) library. Embedding and Chat Completion are integrated with [Semantic Kernel](https://github.com/microsoft/semantic-kernel). > [!NOTE] -Vectors are saved and retrieved with Entity Framework Core using the [EFCore.SqlServer.VectorSearch](https://github.com/efcore/EfCore.SqlServer.VectorSearch) library. If you prefer to use straight SQL, check out the [sql branch](https://github.com/marcominerva/SqlDatabaseVectorSearch/tree/sql). +> If you prefer to use straight SQL, check out the [sql branch](https://github.com/marcominerva/SqlDatabaseVectorSearch/tree/sql). ![SQL Database Vector Search](https://github.com/marcominerva/SqlDatabaseVectorSearch/blob/master/SqlDatabaseVectorSearch.png)