.NET: Add always approve helpers, improve sample and fix bug (#5451)

* Add always approve helpers, improve sample and fix bug

* Address PR comments

dotnet/samples/02-agents/Harness/Harness_Shared_Console/HarnessConsole.cs

@@ -61,6 +61,21 @@ public static class HarnessConsole
 
     private static async Task StreamAgentResponseAsync(AIAgent agent, AgentSession session, AgentModeProvider? modeProvider, string userInput, int? maxContextWindowTokens, int? maxOutputTokens)
     {
+        // Initial user input
+        var approvalRequests = await StreamAndCollectApprovalsAsync(agent.RunStreamingAsync(userInput, session), modeProvider, session, maxContextWindowTokens, maxOutputTokens);
+        var messagesToSend = PromptForApprovals(approvalRequests);
+
+        // Loop while there are approval responses to send back
+        while (messagesToSend is not null)
+        {
+            approvalRequests = await StreamAndCollectApprovalsAsync(agent.RunStreamingAsync(messagesToSend, session), modeProvider, session, maxContextWindowTokens, maxOutputTokens);
+            messagesToSend = PromptForApprovals(approvalRequests);
+        }
+    }
+
+    private static async Task<List<ToolApprovalRequestContent>> StreamAndCollectApprovalsAsync(IAsyncEnumerable<AgentResponseUpdate> updates, AgentModeProvider? modeProvider, AgentSession session, int? maxContextWindowTokens, int? maxOutputTokens)
+    {
+        var approvalRequests = new List<ToolApprovalRequestContent>();
         string mode = modeProvider?.GetMode(session) ?? "unknown";
         System.Console.ForegroundColor = GetModeColor(mode);
         System.Console.Write($"\n[{mode}] Agent: ");
@@ -72,7 +87,7 @@ public static class HarnessConsole
 
         try
         {
-            await foreach (var update in agent.RunStreamingAsync(userInput, session))
+            await foreach (var update in updates)
             {
                 foreach (var content in update.Contents)
                 {
@@ -96,6 +111,17 @@ public static class HarnessConsole
                         hasTextOutput = false;
                         spinner.Start();
                     }
+                    else if (content is ToolApprovalRequestContent approvalRequest)
+                    {
+                        await spinner.StopAsync();
+                        approvalRequests.Add(approvalRequest);
+                        string toolName = approvalRequest.ToolCall is FunctionCallContent fc ? ToolCallFormatter.Format(fc) : approvalRequest.ToolCall?.ToString() ?? "unknown";
+                        System.Console.ForegroundColor = ConsoleColor.Yellow;
+                        System.Console.Write(hasTextOutput ? "\n\n  ⚠️ Approval needed: " : "\n  ⚠️ Approval needed: ");
+                        System.Console.Write(toolName);
+                        System.Console.ForegroundColor = GetModeColor(mode);
+                        hasTextOutput = false;
+                    }
                     else if (content is ErrorContent errorContent)
                     {
                         await spinner.StopAsync();
@@ -174,7 +200,7 @@ public static class HarnessConsole
 
         await spinner.StopAsync();
 
-        if (!hasReceivedAnyText)
+        if (!hasReceivedAnyText && approvalRequests.Count == 0)
         {
             System.Console.ForegroundColor = ConsoleColor.DarkYellow;
             System.Console.Write("\n  (no text response from agent)");
@@ -183,6 +209,59 @@ public static class HarnessConsole
         System.Console.ResetColor();
         System.Console.WriteLine();
         System.Console.WriteLine();
+
+        return approvalRequests;
+    }
+
+    /// <summary>
+    /// Prompts the user for approval of each tool approval request.
+    /// Returns a list of messages to send back to the agent, or <see langword="null"/> if there are no requests.
+    /// </summary>
+    private static List<ChatMessage>? PromptForApprovals(List<ToolApprovalRequestContent> approvalRequests)
+    {
+        if (approvalRequests.Count == 0)
+        {
+            return null;
+        }
+
+        var responses = new List<AIContent>();
+        foreach (var request in approvalRequests)
+        {
+            string toolName = request.ToolCall is FunctionCallContent fc ? ToolCallFormatter.Format(fc) : request.ToolCall?.ToString() ?? "unknown";
+
+            System.Console.ForegroundColor = ConsoleColor.Yellow;
+            System.Console.WriteLine($"\n  🔐 Tool approval required: {toolName}");
+            System.Console.ResetColor();
+            System.Console.WriteLine("     1) Approve this call");
+            System.Console.WriteLine("     2) Always approve this tool (any arguments)");
+            System.Console.WriteLine("     3) Always approve this tool with these arguments");
+            System.Console.WriteLine("     4) Deny");
+            System.Console.Write("     Choice [1-4]: ");
+
+            string? choice = System.Console.ReadLine()?.Trim();
+            AIContent response = choice switch
+            {
+                "2" => request.CreateAlwaysApproveToolResponse("User chose to always approve this tool"),
+                "3" => request.CreateAlwaysApproveToolWithArgumentsResponse("User chose to always approve this tool with these arguments"),
+                "4" => request.CreateResponse(approved: false, reason: "User denied"),
+                _ => request.CreateResponse(approved: true, reason: "User approved"),
+            };
+
+            string action = choice switch
+            {
+                "2" => "✅ Always approved (any args)",
+                "3" => "✅ Always approved (these args)",
+                "4" => "❌ Denied",
+                _ => "✅ Approved",
+            };
+            System.Console.ForegroundColor = ConsoleColor.DarkGray;
+            System.Console.WriteLine($"     {action}");
+            System.Console.ResetColor();
+
+            responses.Add(response);
+        }
+
+        return [new ChatMessage(ChatRole.User, responses)];
     }
 
     private static void HandleModeCommand(AgentModeProvider? modeProvider, AgentSession session, string input)

dotnet/samples/02-agents/Harness/Harness_Step01_Research/Program.cs

@@ -29,31 +29,6 @@ var deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYME
 const int MaxContextWindowTokens = 1_050_000;
 const int MaxOutputTokens = 128_000;
 
-// Create a compaction strategy based on the model's context window.
-// gpt-5.4: 1,050,000 token context window, 128,000 max output tokens.
-// Defaults: tool result eviction at 50% of input budget, truncation at 80%.
-var compactionStrategy = new ContextWindowCompactionStrategy(
-    maxContextWindowTokens: MaxContextWindowTokens,
-    maxOutputTokens: MaxOutputTokens);
-
-// Create an OpenAIClient that communicates with the Foundry responses service and get an IChatClient with stored output disabled
-// so that chat history is managed locally by the agent framework.
-// 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.
-OpenAIClientOptions clientOptions = new() { Endpoint = new Uri(endpoint), RetryPolicy = new ClientRetryPolicy(3) };
-IChatClient chatClient = new OpenAIClient(new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"), clientOptions)
-    .GetResponsesClient()
-    .AsIChatClientWithStoredOutputDisabled(deploymentName)
-    .AsBuilder()
-    .UseFunctionInvocation()
-    .UsePerServiceCallChatHistoryPersistence()
-    .UseAIContextProviders(new CompactionProvider(compactionStrategy))
-    .Build();
-
-// Create web browsing tools for downloading and converting HTML pages to markdown.
-var webBrowsingTools = new WebBrowsingTools();
-
 // Create a ChatClientAgent with the Harness providers (TodoProvider and AgentModeProvider)
 // and research-focused instructions including the mandatory planning workflow.
 var instructions =
@@ -123,36 +98,70 @@ var instructions =
     When a temporary file is no longer needed, delete it to keep file memory tidy.
     """;
 
-AIAgent agent = new ChatClientAgent(
-    chatClient,
-    new ChatClientAgentOptions
-    {
-        Name = "ResearchAgent",
-        Description = "A research assistant that plans and executes research tasks.",
-        AIContextProviders =
-        [
-            new TodoProvider(),
-            new AgentModeProvider(),
-            new FileMemoryProvider(
-                new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
-                (_) => new FileMemoryState() { WorkingFolder = DateTime.UtcNow.ToString("yyyyMMdd_HHmmss") + "_" + Guid.NewGuid().ToString() })
-        ],
-        RequirePerServiceCallChatHistoryPersistence = true,
-        UseProvidedChatClientAsIs = true,
-        ChatHistoryProvider = new InMemoryChatHistoryProvider(new InMemoryChatHistoryProviderOptions
+// Create a compaction strategy based on the model's context window.
+// gpt-5.4: 1,050,000 token context window, 128,000 max output tokens.
+// Defaults: tool result eviction at 50% of input budget, truncation at 80%.
+var compactionStrategy = new ContextWindowCompactionStrategy(
+    maxContextWindowTokens: MaxContextWindowTokens,
+    maxOutputTokens: MaxOutputTokens);
+
+AIAgent agent =
+    // Create an OpenAIClient that communicates with the Foundry responses service.
+    new OpenAIClient(
+        // 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.
+        new BearerTokenPolicy(new DefaultAzureCredential(), "https://ai.azure.com/.default"),
+        new OpenAIClientOptions()
         {
-            ChatReducer = compactionStrategy.AsChatReducer(),
-        }),
-        ChatOptions = new ChatOptions
+            Endpoint = new Uri(endpoint),
+            RetryPolicy = new ClientRetryPolicy(3)          // Enable retries to improve resiliency.
+        })
+    .GetResponsesClient()
+    .AsIChatClientWithStoredOutputDisabled(deploymentName)  // We want to manage chat history locally (not stored in the responses service), so that we can manage compaction ourselves.
+
+    // Build a ChatClient Pipeline
+    .AsBuilder()
+    .UseFunctionInvocation()                                // We are building our own stack from scratch so we need to include Function Invocation ourselves.
+    .UsePerServiceCallChatHistoryPersistence()              // Save chat history updates to the session after each service call, rather than only at the end of the run.
+    .UseAIContextProviders(new CompactionProvider(compactionStrategy))  // Add Compaction before each service call to responses so that long function invocation loops don't overflow the context.
+
+    // Build our agent on top of the ChatClient Pipeline
+    .BuildAIAgent(
+        new ChatClientAgentOptions
         {
-            // Set a high token limit for long research tasks with many tool calls and long outputs.
-            // This matches gpt-5.4's max output tokens, and should be adjusted depending on the model used and expected response length.
-            MaxOutputTokens = 128_000,
-            Instructions = instructions,
-            Reasoning = new() { Effort = ReasoningEffort.Medium },
-            Tools = [ResponseTool.CreateWebSearchTool().AsAITool(), .. webBrowsingTools.Tools],
-        },
-    });
+            Name = "ResearchAgent",
+            Description = "A research assistant that plans and executes research tasks.",
+            UseProvidedChatClientAsIs = true,                           // Since we built our own stack from scratch we need to tell the agent not to also add defaults like Function Invocation.
+            RequirePerServiceCallChatHistoryPersistence = true,         // Since we are added the per service call persistence ChatClient, we need to tell the agent to not also store chat history at the end of the run.
+            ChatHistoryProvider = new InMemoryChatHistoryProvider(      // Store chat history in memory in the session object. Will persist if the session is persisted.
+                new InMemoryChatHistoryProviderOptions
+                {
+                    ChatReducer = compactionStrategy.AsChatReducer(),   // Run compaction on the InMemory chat history when it gets too large.
+                }),
+            AIContextProviders =
+            [
+                new TodoProvider(),         // Add an AIContextProvider to allow the agent to create a TODO list, which is stored in the session.
+                new AgentModeProvider(),    // Add an AIContextProvider that tracks the agent mode and allows switching mode. Current mode is stored in the session.
+                new FileMemoryProvider(     // Add an AIContextProvider that can store memories in files under a session specific working folder.
+                    new FileSystemAgentFileStore(Path.Combine(AppContext.BaseDirectory, "agent-files")),
+                    (_) => new FileMemoryState() { WorkingFolder = DateTime.UtcNow.ToString("yyyyMMdd_HHmmss") + "_" + Guid.NewGuid().ToString() })
+            ],
+            ChatOptions = new ChatOptions
+            {
+                Instructions = instructions,
+                Tools =
+                [
+                    ResponseTool.CreateWebSearchTool().AsAITool(),          // Add the foundry hosted web search tool that runs in the service.
+                    new WebBrowsingTool(),                                  // Add a local web browsing tool that converts html to markdown.
+                ],
+                MaxOutputTokens = MaxOutputTokens,                          // Set a high token limit for long research tasks with many tool calls and long outputs.
+                Reasoning = new() { Effort = ReasoningEffort.Medium },
+            },
+        })
+    .AsBuilder()
+    .UseToolApproval()                                                      // Add the ability to auto approve tools once a user has said they don't want to be asked again. Approval rules are tied to the session.
+    .Build();
 
 // Run the interactive console session using the shared HarnessConsole helper.
 await HarnessConsole.RunAgentAsync(agent, title: "Research Assistant", userPrompt: "Enter a research topic to get started.", maxContextWindowTokens: MaxContextWindowTokens, maxOutputTokens: MaxOutputTokens);

dotnet/samples/02-agents/Harness/Harness_Step01_Research/WebBrowsingTool.cs

@@ -2,25 +2,34 @@
 
 using System.ComponentModel;
 using System.Net;
+using System.Text.Json;
 using System.Text.RegularExpressions;
 using Microsoft.Extensions.AI;
 
 namespace SampleApp;
 
 /// <summary>
-/// Provides a web browsing tool that downloads HTML pages and converts them to markdown.
+/// An AI function that downloads HTML pages and converts them to markdown.
 /// </summary>
-internal sealed partial class WebBrowsingTools
+internal sealed partial class WebBrowsingTool : AIFunction
 {
     private static readonly HttpClient s_httpClient = new();
+    private readonly AIFunction _inner = AIFunctionFactory.Create(DownloadUriAsync);
 
-    /// <summary>
-    /// Gets the web browsing tools.
-    /// </summary>
-    public IList<AITool> Tools { get; } =
-    [
-        AIFunctionFactory.Create(DownloadUriAsync),
-    ];
+    /// <inheritdoc/>
+    public override string Name => this._inner.Name;
+
+    /// <inheritdoc/>
+    public override string Description => this._inner.Description;
+
+    /// <inheritdoc/>
+    public override JsonElement JsonSchema => this._inner.JsonSchema;
+
+    /// <inheritdoc/>
+    protected override ValueTask<object?> InvokeCoreAsync(
+        AIFunctionArguments arguments,
+        CancellationToken cancellationToken) =>
+        this._inner.InvokeAsync(arguments, cancellationToken);
 
     [Description("Download the html from the given url as markdown")]
     private static async Task<string> DownloadUriAsync(