chore: import upstream snapshot with attribution

dotnet/samples/02-agents/Agents/Agent_Step01_UsingFunctionToolsWithApprovals/Agent_Step01_UsingFunctionToolsWithApprovals.csproj

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+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.Identity" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/02-agents/Agents/Agent_Step01_UsingFunctionToolsWithApprovals/Program.cs

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+// Copyright (c) Microsoft. All rights reserved.
+
+// Function Tools with Approvals — Human-in-the-loop tool execution
+//
+// This sample demonstrates how to use function tools that require human
+// approval before execution. It shows both non-streaming and streaming
+// agent interactions using menu-related tools.
+// If the agent is hosted in a service, combine this with the Persisted
+// Conversations sample to persist chat history while waiting for user input.
+
+using System.ComponentModel;
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+using ChatMessage = Microsoft.Extensions.AI.ChatMessage;
+
+var endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
+
+// Create a sample function tool that the agent can use.
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+// Create the chat client and agent.
+// Note that we are wrapping the function tool with ApprovalRequiredAIFunction to require user approval before invoking it.
+// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+AIAgent agent = new AIProjectClient(
+    new Uri(endpoint),
+    new DefaultAzureCredential())
+    .AsAIAgent(model: deploymentName, instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);
+
+// Call the agent and check if there are any function approval requests to handle.
+// For simplicity, we are assuming here that only function approvals are pending.
+AgentSession session = await agent.CreateSessionAsync();
+AgentResponse response = await agent.RunAsync("What is the weather like in Amsterdam?", session);
+List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
+
+// For streaming use:
+// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", session).ToListAsync();
+// approvalRequests = updates.SelectMany(x => x.Contents).OfType<ToolApprovalRequestContent>().ToList();
+
+while (approvalRequests.Count > 0)
+{
+    // Ask the user to approve each function call request.
+    List<ChatMessage> userInputResponses = approvalRequests
+        .ConvertAll(functionApprovalRequest =>
+        {
+            Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
+            return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
+        });
+
+    // Pass the user input responses back to the agent for further processing.
+    response = await agent.RunAsync(userInputResponses, session);
+
+    approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
+
+    // For streaming use:
+    // updates = await agent.RunStreamingAsync(userInputResponses, session).ToListAsync();
+    // approvalRequests = updates.SelectMany(x => x.Contents).OfType<ToolApprovalRequestContent>().ToList();
+}
+
+Console.WriteLine($"\nAgent: {response}");
+
+// For streaming use:
+// Console.WriteLine($"\nAgent: {updates.ToAgentResponse()}");