.Net: added readme

dotnet/src/Connectors/Connectors.Memory.SqlServer/README.md

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+# Microsoft.SemanticKernel.Connectors.SqlServer
+
+This connector uses the SQL Server database engine to implement Semantic Memory.
+
+> [!IMPORTANT]  
+> The features needed to use this connector are available in preview in Azure SQL only at the moment. Please take a look at the [Announcing EAP for Vector Support in Azure SQL Database](https://devblogs.microsoft.com/azure-sql/announcing-eap-native-vector-support-in-azure-sql-database/) for more information on how to enable the feature.
+
+## Quick start
+
+Create a new .NET console application:
+
+```bash
+dotnet new console --framework net8.0 -n MySemanticMemoryApp
+```
+
+Add the Semantic Kernel packages needed to create a Chatbot:
+
+```bash
+dotnet add package Microsoft.SemanticKernel
+dotnet add package Microsoft.SemanticKernel.Connectors.OpenAI
+```
+
+Add `Microsoft.SemanticKernel.Connectors.SqlServer` to give your Chatbot memories:
+
+```bash
+dotnet add package Microsoft.SemanticKernel.Connectors.SqlServer --prerelease
+```
+
+Then you can use the following code to create a Chatbot with a memory that uses SQL Server:
+
+```csharp
+using System.Text;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using Microsoft.SemanticKernel.Connectors.SqlServer;
+using Microsoft.SemanticKernel.Memory;
+
+#pragma warning disable SKEXP0001, SKEXP0010, SKEXP0020
+
+// Replace with your Azure OpenAI endpoint
+const string AzureOpenAIEndpoint = "https://.openai.azure.com/";
+
+// Replace with your Azure OpenAI API key
+const string AzureOpenAIApiKey = "";
+
+// Replace with your Azure OpenAI embedding deployment name
+const string EmbeddingModelDeploymentName = "embeddings";
+
+// Replace with your Azure OpenAI chat completion deployment name
+const string ChatModelDeploymentName = "gpt-35";
+
+// Complete with your Azure SQL connection string
+const string ConnectionString = "Data Source=.database.windows.net;Initial Catalog=;Authentication=Active Directory Default;Connection Timeout=30";
+
+// Table where memories will be stored
+const string TableName = "ChatMemories";
+
+
+var kernel = Kernel.CreateBuilder()
+    .AddAzureOpenAIChatCompletion(ChatModelDeploymentName, AzureOpenAIEndpoint, AzureOpenAIApiKey)
+    .Build();
+
+var memory = new MemoryBuilder()
+    .WithSqlServerMemoryStore(ConnectionString)
+    .WithAzureOpenAITextEmbeddingGeneration(EmbeddingModelDeploymentName, AzureOpenAIEndpoint, AzureOpenAIApiKey)
+    .Build();
+
+await memory.SaveInformationAsync(TableName, "With the new connector Microsoft.SemanticKernel.Connectors.SqlServer it is possible to efficiently store and retrieve memories thanks to the newly added vector support", "semantic-kernel-mssql");
+await memory.SaveInformationAsync(TableName, "At the moment Microsoft.SemanticKernel.Connectors.SqlServer can be used only with Azure SQL", "semantic-kernel-azuresql");
+await memory.SaveInformationAsync(TableName, "Azure SQL support for vectors is in Early Adopter Preview.", "azuresql-vector-eap");
+await memory.SaveInformationAsync(TableName, "Pizza is one of the favourite food in the world.", "pizza-favourite-food");
+
+var ai = kernel.GetRequiredService<IChatCompletionService>();
+var chat = new ChatHistory("You are an AI assistant that helps people find information.");
+var builder = new StringBuilder();
+while (true)
+{
+    Console.Write("Question: ");
+    var question = Console.ReadLine()!;
+
+    Console.WriteLine("\nSearching information from the memory...");
+    builder.Clear();
+    await foreach (var result in memory.SearchAsync(TableName, question, limit: 3))
+    {
+        builder.AppendLine(result.Metadata.Text);
+    }
+    if (builder.Length != 0) {
+        Console.WriteLine("\nFound information from the memory:");
+        Console.WriteLine(builder.ToString());
+    }
+
+    Console.WriteLine("Answer: ");
+    var contextToRemove = -1;
+    if (builder.Length != 0)
+    {
+        builder.Insert(0, "Here's some additional information: ");
+        contextToRemove = chat.Count;
+        chat.AddUserMessage(builder.ToString());
+    }
+
+    chat.AddUserMessage(question);
+
+    builder.Clear();
+    await foreach (var message in ai.GetStreamingChatMessageContentsAsync(chat))
+    {
+        Console.Write(message);
+        builder.Append(message.Content);
+    }
+    Console.WriteLine();
+    chat.AddAssistantMessage(builder.ToString());
+
+    if (contextToRemove >= 0)
+        chat.RemoveAt(contextToRemove);
+
+    Console.WriteLine();
+}
+```