diff --git a/dotnet/samples/Concepts/FunctionCalling/ContextDependentAdvertising.cs b/dotnet/samples/Concepts/FunctionCalling/ContextDependentAdvertising.cs
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+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.ChatCompletion;
+using Microsoft.SemanticKernel.Connectors.OpenAI;
+
+namespace FunctionCalling;
+
+///
+/// These samples demonstrate how to advertise functions to AI model based on a context.
+///
+public class ContextDependentAdvertising(ITestOutputHelper output) : BaseTest(output)
+{
+ ///
+ /// This sample demonstrates how to advertise functions to AI model based on the context of the chat history.
+ /// It advertises functions to the AI model based on the game state.
+ /// For example, if the maze has not been created, advertise the create maze function only to prevent the AI model
+ /// from adding traps or treasures to the maze before it is created.
+ ///
+ [Fact]
+ public async Task AdvertiseFunctionsDependingOnContextPerUserInteractionAsync()
+ {
+ Kernel kernel = CreateKernel();
+
+ IChatCompletionService chatCompletionService = kernel.GetRequiredService();
+
+ // Tracking number of iterations to avoid infinite loop.
+ int maxIteration = 10;
+ int iteration = 0;
+
+ // Define the functions for AI model to call.
+ var gameUtils = kernel.ImportPluginFromType();
+ KernelFunction createMaze = gameUtils["CreateMaze"];
+ KernelFunction addTraps = gameUtils["AddTrapsToMaze"];
+ KernelFunction addTreasures = gameUtils["AddTreasuresToMaze"];
+ KernelFunction playGame = gameUtils["PlayGame"];
+
+ ChatHistory chatHistory = [];
+ chatHistory.AddUserMessage("I would like to play a maze game with a lot of tricky traps and shiny treasures.");
+
+ // Loop until the game has started or the max iteration is reached.
+ while (!chatHistory.Any(item => item.Content?.Contains("Game started.") ?? false) && iteration < maxIteration)
+ {
+ List functionsToAdvertise = new();
+
+ // Decide game state based on chat history.
+ bool mazeCreated = chatHistory.Any(item => item.Content?.Contains("Maze created.") ?? false);
+ bool trapsAdded = chatHistory.Any(item => item.Content?.Contains("Traps added to the maze.") ?? false);
+ bool treasuresAdded = chatHistory.Any(item => item.Content?.Contains("Treasures added to the maze.") ?? false);
+
+ // The maze has not been created yet so advertise the create maze function.
+ if (!mazeCreated)
+ {
+ functionsToAdvertise.Add(createMaze);
+ }
+ // The maze has been created so advertise the adding traps and treasures functions.
+ else if (mazeCreated && (!trapsAdded || !treasuresAdded))
+ {
+ functionsToAdvertise.Add(addTraps);
+ functionsToAdvertise.Add(addTreasures);
+ }
+ // Both traps and treasures have been added so advertise the play game function.
+ else if (treasuresAdded && trapsAdded)
+ {
+ functionsToAdvertise.Add(playGame);
+ }
+
+ // Provide the functions to the AI model.
+ OpenAIPromptExecutionSettings settings = new() { FunctionChoiceBehavior = FunctionChoiceBehavior.Required(functionsToAdvertise) };
+
+ // Prompt the AI model.
+ ChatMessageContent result = await chatCompletionService.GetChatMessageContentAsync(chatHistory, settings, kernel);
+
+ Console.WriteLine(result);
+
+ iteration++;
+ }
+ }
+
+ private static Kernel CreateKernel()
+ {
+ // Create kernel
+ IKernelBuilder builder = Kernel.CreateBuilder();
+
+ builder.AddOpenAIChatCompletion(TestConfiguration.OpenAI.ChatModelId, TestConfiguration.OpenAI.ApiKey);
+
+ return builder.Build();
+ }
+
+ private sealed class GameUtils
+ {
+ [KernelFunction]
+ public static string CreateMaze() => "Maze created.";
+
+ [KernelFunction]
+ public static string AddTrapsToMaze() => "Traps added to the maze.";
+
+ [KernelFunction]
+ public static string AddTreasuresToMaze() => "Treasures added to the maze.";
+
+ [KernelFunction]
+ public static string PlayGame() => "Game started.";
+ }
+}