test

dotnet/samples/GettingStarted/FoundryAgents/FoundryAgents_Step12_Middleware/FoundryAgents_Step12_Middleware.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="Microsoft.Extensions.Logging.Console" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Azure.AI.Projects" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.AzureAI\Microsoft.Agents.AI.AzureAI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/GettingStarted/FoundryAgents/FoundryAgents_Step12_Middleware/Program.cs

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+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows multiple middleware layers working together with Azure Foundry Agents:
+// agent run (PII filtering and guardrails),
+// function invocation (logging and result overrides), and human-in-the-loop
+// approval workflows for sensitive function calls.
+
+using System.ComponentModel;
+using System.Text.RegularExpressions;
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Extensions.AI;
+
+// Get Azure AI Foundry configuration from environment variables
+string endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+string deploymentName = System.Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o";
+
+const string AssistantInstructions = "You are an AI assistant that helps people find information.";
+const string AssistantName = "InformationAssistant";
+
+// Get a client to create/retrieve/delete server side agents with Azure Foundry Agents.
+AIProjectClient aiProjectClient = new(new Uri(endpoint), new AzureCliCredential());
+
+[Description("Get the weather for a given location.")]
+static string GetWeather([Description("The location to get the weather for.")] string location)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+[Description("The current datetime offset.")]
+static string GetDateTime()
+    => DateTimeOffset.Now.ToString();
+
+AITool dateTimeTool = AIFunctionFactory.Create(GetDateTime, name: nameof(GetDateTime));
+AITool getWeatherTool = AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather));
+
+// Define the agent you want to create. (Prompt Agent in this case)
+AIAgent originalAgent = await aiProjectClient.CreateAIAgentAsync(
+    name: AssistantName,
+    model: deploymentName,
+    instructions: AssistantInstructions,
+    tools: [getWeatherTool, dateTimeTool]);
+
+// Adding middleware to the agent level
+AIAgent middlewareEnabledAgent = originalAgent
+    .AsBuilder()
+    .Use(FunctionCallMiddleware)
+    .Use(FunctionCallOverrideWeather)
+    .Use(PIIMiddleware, null)
+    .Use(GuardrailMiddleware, null)
+    .Build();
+
+AgentThread thread = await middlewareEnabledAgent.GetNewThreadAsync();
+
+Console.WriteLine("\n\n=== Example 1: Wording Guardrail ===");
+AgentResponse guardRailedResponse = await middlewareEnabledAgent.RunAsync("Tell me something harmful.");
+Console.WriteLine($"Guard railed response: {guardRailedResponse}");
+
+Console.WriteLine("\n\n=== Example 2: PII detection ===");
+AgentResponse piiResponse = await middlewareEnabledAgent.RunAsync("My name is John Doe, call me at 123-456-7890 or email me at john@something.com");
+Console.WriteLine($"Pii filtered response: {piiResponse}");
+
+Console.WriteLine("\n\n=== Example 3: Agent function middleware ===");
+
+// Agent function middleware support is limited to agents that wraps a upstream ChatClientAgent or derived from it.
+
+AgentResponse functionCallResponse = await middlewareEnabledAgent.RunAsync("What's the current time and the weather in Seattle?", thread);
+Console.WriteLine($"Function calling response: {functionCallResponse}");
+
+// Special per-request middleware agent.
+Console.WriteLine("\n\n=== Example 4: Middleware with human in the loop function approval ===");
+
+AIAgent humanInTheLoopAgent = await aiProjectClient.CreateAIAgentAsync(
+    name: "HumanInTheLoopAgent",
+    model: deploymentName,
+    instructions: "You are an Human in the loop testing AI assistant that helps people find information.",
+
+    // Adding a function with approval required
+    tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)))]);
+
+// Using the ConsolePromptingApprovalMiddleware for a specific request to handle user approval during function calls.
+AgentResponse response = await humanInTheLoopAgent
+    .AsBuilder()
+    .Use(ConsolePromptingApprovalMiddleware, null)
+    .Build()
+    .RunAsync("What's the current time and the weather in Seattle?");
+
+Console.WriteLine($"HumanInTheLoopAgent agent middleware response: {response}");
+
+// Function invocation middleware that logs before and after function calls.
+async ValueTask<object?> FunctionCallMiddleware(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
+{
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 1 Pre-Invoke");
+    var result = await next(context, cancellationToken);
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 1 Post-Invoke");
+
+    return result;
+}
+
+// Function invocation middleware that overrides the result of the GetWeather function.
+async ValueTask<object?> FunctionCallOverrideWeather(AIAgent agent, FunctionInvocationContext context, Func<FunctionInvocationContext, CancellationToken, ValueTask<object?>> next, CancellationToken cancellationToken)
+{
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 2 Pre-Invoke");
+
+    var result = await next(context, cancellationToken);
+
+    if (context.Function.Name == nameof(GetWeather))
+    {
+        // Override the result of the GetWeather function
+        result = "The weather is sunny with a high of 25°C.";
+    }
+    Console.WriteLine($"Function Name: {context!.Function.Name} - Middleware 2 Post-Invoke");
+    return result;
+}
+
+// This middleware redacts PII information from input and output messages.
+async Task<AgentResponse> PIIMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    // Redact PII information from input messages
+    var filteredMessages = FilterMessages(messages);
+    Console.WriteLine("Pii Middleware - Filtered Messages Pre-Run");
+
+    var response = await innerAgent.RunAsync(filteredMessages, thread, options, cancellationToken).ConfigureAwait(false);
+
+    // Redact PII information from output messages
+    response.Messages = FilterMessages(response.Messages);
+
+    Console.WriteLine("Pii Middleware - Filtered Messages Post-Run");
+
+    return response;
+
+    static IList<ChatMessage> FilterMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Select(m => new ChatMessage(m.Role, FilterPii(m.Text))).ToList();
+    }
+
+    static string FilterPii(string content)
+    {
+        // Regex patterns for PII detection (simplified for demonstration)
+        Regex[] piiPatterns = [
+            new(@"\b\d{3}-\d{3}-\d{4}\b", RegexOptions.Compiled), // Phone number (e.g., 123-456-7890)
+                    new(@"\b[\w\.-]+@[\w\.-]+\.\w+\b", RegexOptions.Compiled), // Email address
+                    new(@"\b[A-Z][a-z]+\s[A-Z][a-z]+\b", RegexOptions.Compiled) // Full name (e.g., John Doe)
+        ];
+
+        foreach (var pattern in piiPatterns)
+        {
+            content = pattern.Replace(content, "[REDACTED: PII]");
+        }
+
+        return content;
+    }
+}
+
+// This middleware enforces guardrails by redacting certain keywords from input and output messages.
+async Task<AgentResponse> GuardrailMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    // Redact keywords from input messages
+    var filteredMessages = FilterMessages(messages);
+
+    Console.WriteLine("Guardrail Middleware - Filtered messages Pre-Run");
+
+    // Proceed with the agent run
+    var response = await innerAgent.RunAsync(filteredMessages, thread, options, cancellationToken);
+
+    // Redact keywords from output messages
+    response.Messages = FilterMessages(response.Messages);
+
+    Console.WriteLine("Guardrail Middleware - Filtered messages Post-Run");
+
+    return response;
+
+    List<ChatMessage> FilterMessages(IEnumerable<ChatMessage> messages)
+    {
+        return messages.Select(m => new ChatMessage(m.Role, FilterContent(m.Text))).ToList();
+    }
+
+    static string FilterContent(string content)
+    {
+        foreach (var keyword in new[] { "harmful", "illegal", "violence" })
+        {
+            if (content.Contains(keyword, StringComparison.OrdinalIgnoreCase))
+            {
+                return "[REDACTED: Forbidden content]";
+            }
+        }
+
+        return content;
+    }
+}
+
+// This middleware handles Human in the loop console interaction for any user approval required during function calling.
+async Task<AgentResponse> ConsolePromptingApprovalMiddleware(IEnumerable<ChatMessage> messages, AgentThread? thread, AgentRunOptions? options, AIAgent innerAgent, CancellationToken cancellationToken)
+{
+    AgentResponse response = await innerAgent.RunAsync(messages, thread, options, cancellationToken);
+
+    List<UserInputRequestContent> userInputRequests = response.UserInputRequests.ToList();
+
+    while (userInputRequests.Count > 0)
+    {
+        // Ask the user to approve each function call request.
+        // For simplicity, we are assuming here that only function approval requests are being made.
+
+        // Pass the user input responses back to the agent for further processing.
+        response.Messages = userInputRequests
+            .OfType<FunctionApprovalRequestContent>()
+            .Select(functionApprovalRequest =>
+            {
+                Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
+                bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
+                return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
+            })
+            .ToList();
+
+        response = await innerAgent.RunAsync(response.Messages, thread, options, cancellationToken);
+
+        userInputRequests = response.UserInputRequests.ToList();
+    }
+
+    return response;
+}
+
+// Cleanup by agent name removes the agent version created.
+await aiProjectClient.Agents.DeleteAgentAsync(middlewareEnabledAgent.Name);

dotnet/samples/GettingStarted/FoundryAgents/FoundryAgents_Step12_Middleware/README.md

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+# Agent Middleware
+
+This sample demonstrates how to add middleware to intercept agent runs and function calls to implement cross-cutting concerns like logging, validation, and guardrails.
+
+## What This Sample Shows
+
+1. Azure Foundry Agents integration via `AIProjectClient` and `AzureCliCredential`
+2. Agent run middleware (logging and monitoring)
+3. Function invocation middleware (logging and overriding tool results)
+4. Per-request agent run middleware
+5. Per-request function pipeline with approval
+6. Combining agent-level and per-request middleware
+
+## Function Invocation Middleware
+
+Not all agents support function invocation middleware.
+
+Attempting to use function middleware on agents that do not wrap a ChatClientAgent or derives from it will throw an InvalidOperationException.
+
+## Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 10 SDK or later
+- Azure Foundry service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure Foundry resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_FOUNDRY_PROJECT_ENDPOINT="https://your-foundry-service.services.ai.azure.com/api/projects/your-foundry-project" # Replace with your Azure Foundry resource endpoint
+$env:AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
+
+## Running the Sample
+
+Navigate to the FoundryAgents sample directory and run:
+
+```powershell
+cd dotnet/samples/GettingStarted/FoundryAgents
+dotnet run --project .\FoundryAgents_Step12_Middleware
+```
+
+## Expected Behavior
+
+When you run this sample, you will see the following demonstrations:
+
+1. **Example 1: Wording Guardrail** - The agent receives a request for harmful content. The guardrail middleware intercepts the request and prevents the agent from responding to harmful prompts, returning a safe response instead.
+
+2. **Example 2: PII Detection** - The agent receives a message containing personally identifiable information (name, phone number, email). The PII middleware detects and filters this sensitive information before processing.
+
+3. **Example 3: Agent Function Middleware** - The agent uses function tools (GetDateTime and GetWeather) to answer a question about the current time and weather in Seattle. The function middleware logs the function calls and can override results if needed.
+
+4. **Example 4: Human-in-the-Loop Function Approval** - The agent attempts to call a weather function, but the approval middleware intercepts the call and prompts the user to approve or deny the function invocation before it executes. The user can respond with "Y" to approve or any other input to deny.
+
+Each example demonstrates how middleware can be used to implement cross-cutting concerns and control agent behavior at different levels (agent-level and per-request).