Added console chat app. uses semantic kernel, kernel memory and plugins.

Dotnet-SK-MemoryPlugin-ChatConsole/Chat.SK.csproj

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+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net8.0</TargetFramework>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <Nullable>enable</Nullable>
+    <NoWarn>SKEXP0042</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.KernelMemory.Core" Version="0.28.240212.1" />
+    <PackageReference Include="Microsoft.KernelMemory.MemoryDb.AzureAISearch" Version="0.28.240212.1" />
+    <PackageReference Include="Microsoft.KernelMemory.SemanticKernelPlugin" Version="0.28.240212.1" />
+    <PackageReference Include="Microsoft.SemanticKernel" Version="1.3.0" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.AzureAISearch" Version="1.3.1-alpha" />
+    <PackageReference Include="Microsoft.SemanticKernel.Functions.OpenAPI" Version="1.0.0-beta8" />
+    <PackageReference Include="Microsoft.SemanticKernel.Planners.Handlebars" Version="1.3.0-preview" />
+    <PackageReference Include="Microsoft.SemanticKernel.Planners.OpenAI" Version="1.3.0-preview" />
+    <PackageReference Include="Microsoft.SemanticKernel.Plugins.Memory" Version="1.3.1-alpha" />
+    <PackageReference Include="Microsoft.SemanticKernel.Plugins.OpenApi" Version="1.3.0-alpha" />
+  </ItemGroup>
+
+</Project>

Dotnet-SK-MemoryPlugin-ChatConsole/Chat.SK.sln

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+
+Microsoft Visual Studio Solution File, Format Version 12.00
+# Visual Studio Version 17
+VisualStudioVersion = 17.8.34511.84
+MinimumVisualStudioVersion = 10.0.40219.1
+Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "Chat.SK", "Chat.SK.csproj", "{F9E08994-3C60-4BA5-8A12-2636BB57E200}"
+EndProject
+Global
+	GlobalSection(SolutionConfigurationPlatforms) = preSolution
+		Debug|Any CPU = Debug|Any CPU
+		Release|Any CPU = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(ProjectConfigurationPlatforms) = postSolution
+		{F9E08994-3C60-4BA5-8A12-2636BB57E200}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
+		{F9E08994-3C60-4BA5-8A12-2636BB57E200}.Debug|Any CPU.Build.0 = Debug|Any CPU
+		{F9E08994-3C60-4BA5-8A12-2636BB57E200}.Release|Any CPU.ActiveCfg = Release|Any CPU
+		{F9E08994-3C60-4BA5-8A12-2636BB57E200}.Release|Any CPU.Build.0 = Release|Any CPU
+	EndGlobalSection
+	GlobalSection(SolutionProperties) = preSolution
+		HideSolutionNode = FALSE
+	EndGlobalSection
+	GlobalSection(ExtensibilityGlobals) = postSolution
+		SolutionGuid = {3B750AC7-CD92-407F-AB2D-FA821171F64A}
+	EndGlobalSection
+EndGlobal

Dotnet-SK-MemoryPlugin-ChatConsole/Program.cs

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+using Microsoft.KernelMemory;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+using System.ComponentModel;
+
+// Disable warnings related to Semantic Kernel
+#pragma warning disable SKEXP0003
+#pragma warning disable SKEXP0010
+#pragma warning disable SKEXP0011
+#pragma warning disable SKEXP0021
+#pragma warning disable SKEXP0052
+#pragma warning disable SKEXP0060
+#pragma warning disable SKEXP0061
+
+// Azure OpenAI Variables
+var apiKey = "";
+var deploymentChatName = "";
+var deploymentEmbeddingName = "";
+var endpoint = "";
+
+// Azure AI Search Variables
+string searchApiKey = "";
+string searchEndpoint = "";
+
+
+var builder = Kernel.CreateBuilder();
+
+builder
+    .AddAzureOpenAIChatCompletion(
+    deploymentChatName, 
+    endpoint, 
+    apiKey);
+
+var kernel = builder.Build();
+
+var embeddingConfig = new AzureOpenAIConfig
+{
+    APIKey = apiKey,
+    Deployment = deploymentEmbeddingName,
+    Endpoint = endpoint,
+    APIType = AzureOpenAIConfig.APITypes.EmbeddingGeneration,
+    Auth = AzureOpenAIConfig.AuthTypes.APIKey
+};
+
+var chatConfig = new AzureOpenAIConfig
+{
+    APIKey = apiKey,
+    Deployment = deploymentChatName,
+    Endpoint = endpoint,
+    APIType = AzureOpenAIConfig.APITypes.ChatCompletion,
+    Auth = AzureOpenAIConfig.AuthTypes.APIKey
+};
+
+var kernelMemory = new KernelMemoryBuilder()
+    .WithAzureOpenAITextGeneration(chatConfig)
+    .WithAzureOpenAITextEmbeddingGeneration(embeddingConfig)
+    .WithAzureAISearchMemoryDb(searchEndpoint, searchApiKey)
+    .Build<MemoryServerless>();
+
+// Import a document to the memory, e.g. Expense Policy PDF document
+await kernelMemory.ImportDocumentAsync("CHANGE_ME: FILE_LOCATION.pdf", documentId: "doc001");
+
+// Import the memory plugin
+var plugin = new MemoryPlugin(kernelMemory, waitForIngestionToComplete: true);
+kernel.ImportPluginFromObject(plugin, "memory");
+
+// Import the VCard plugin
+kernel.ImportPluginFromType<VCardPlugin>();
+
+ChatHistory history = [];
+
+var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
+
+Console.WriteLine("Hello! This is a chat console.");
+Console.WriteLine(string.Empty);
+
+var system = $@"
+CHANGE_ME: WRITE YOUR ASSISTANT SYSTEM PROMPT HERE
+";
+
+history.AddMessage(AuthorRole.System, system);
+
+// Enable auto function calling
+OpenAIPromptExecutionSettings openAIPromptExecutionSettings = new()
+{
+    ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions
+};
+
+while (true)
+{
+    Console.WriteLine(string.Empty);
+    Console.ForegroundColor = ConsoleColor.Yellow;
+    Console.Write("Input > ");
+    var message = Console.ReadLine();
+    Console.ResetColor();
+
+    // Prompt the message to the kernel memory
+    var prompt = $@"
+           Question to Kernel Memory: {message}
+           Kernel Memory Answer: {{memory.ask}}
+           ";
+
+    history.AddMessage(AuthorRole.User, prompt);
+
+    var result = await chatCompletionService.GetChatMessageContentAsync(history, openAIPromptExecutionSettings, kernel);
+
+    Console.WriteLine(string.Empty);
+    Console.WriteLine(string.Empty);
+    Console.Write("Assistant > ");
+    Console.WriteLine(result.Content);
+
+    history.AddMessage(AuthorRole.Assistant, result.Content);
+}
+
+public class VCardPlugin
+{
+    const string FunctionModelDescription = @"
+- This function creates a request for a Virtual Card.
+- You must always ask for the user approval before creating a virtual card.
+- You must always ask for the user policy details before creating a virtual card.
+- You must always ask for the number of days of travel before creating a virtual card.
+- You must always request the ammount to be created. 
+- If the ammount is bigger than the allowed from the policy deny the request.
+";
+
+    [KernelFunction, Description(FunctionModelDescription)]
+    public string CreateCard(int ammount, int days)
+    {
+        Random random = new Random();
+        string cardNumber = "5" + random.Next(1, 6).ToString() + string.Concat(Enumerable.Range(0, 14).Select(n => random.Next(0, 10).ToString()));
+
+        // Calculate the Luhn check digit
+        int sum = 0;
+        for (int i = 0; i < 15; i++)
+        {
+            int digit = int.Parse(cardNumber[i].ToString());
+            if (i % 2 == 0)
+            {
+                digit *= 2;
+                if (digit > 9)
+                {
+                    digit -= 9;
+                }
+            }
+            sum += digit;
+        }
+
+        int checkDigit = (10 - (sum % 10)) % 10;
+        cardNumber += checkDigit.ToString();
+
+        // Generate a random expiry date in the future
+        int expiryMonth = random.Next(1, 13); // Month is between 1 and 12
+        int expiryYear = DateTime.Now.Year + random.Next(1, 6); // Year is between now and 5 years from now
+
+        // Generate a random 3-digit CVC
+        int cvc = random.Next(100, 1000); // CVC is a 3-digit number
+
+        Console.ForegroundColor = ConsoleColor.DarkBlue;
+        Console.WriteLine($"[Card created with ammount {ammount} for {days} days]");
+        Console.WriteLine($"Card Number: {cardNumber}");
+        Console.WriteLine($"Expiry Date: {expiryMonth:D2}/{expiryYear}");
+        Console.WriteLine($"CVC: {cvc}");
+        Console.ResetColor();
+
+        return "Virtual Card created successfully.";
+    }
+}

Dotnet-SK-MemoryPlugin-ChatConsole/README.md

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+# Intro
+
+This application is a .NET console chat application.
+
+The application replicates a chat application where the AI assistant uses techniques like RAG and automatic function calling to assist the user. 
+An example scenario would be an internal chat app where the user can ask questions about the companies expense/travel policies and request a creation of virtual card to use in a trip.
+
+The main goal is to:
+
+- Integrate a semantic kernel memory into the application, which will allow the LLM to remember and recall information from Azure AI Search.
+- Demonstrate how to implement plugins in a semantic kernel enabled app.
+
+Requirements:
+
+- a Azure OpenAI Service.
+- a Azure AI Search Service.
+- some public document to be indexed in the Azure AI Search Service.
+
+## Main Project Structure
+
+### Chat.SK
+
+Main project that contains the chat application. It uses the Semantic Kernel and Kernel Memory nuget packages.
+
+## Running the Application
+
+Steps:
+
+1. Update the variables for Azure Open Ai and AI Search in `Program.cs`.
+1. Update location of the location of the public document in `Program.cs` to be imported to the Kernel Memory.											
+1. Add an example system prompt.
+1. Run with `dotnet run` or `F5`.