.NET: Organize the .Net samples (#578)

* Organize the .Net samples * Organize the .Net samples * Merge latest from main * Update sample to also include function calling telemetry (#577) * Move package installation instructions to user-guide (#572) * Move package installation instructions to user-guide * Update user-documentation-dotnet/getting-started/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update docs/docs-templates/getting-started/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * .NET: Add SK-AF Migration Samples for Responses API. (#575) * Responses wip * Adding OpenAI Responses Migration samples * Address all samples and code for Azure and OpenAI Responses Migration code * Update dotnet/samples/SemanticKernelMigration/OpenAIResponses/Step02_ReasoningModel/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Organize the .Net samples * Organize the .Net samples * Merge latest from main * Use Agent rather than AIAgent * Rename agents getting started samples * Use singular Agent --------- Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
2026-06-16 21:04:09 +08:00 · 2025-09-02 10:52:07 +00:00
parent 9b61c72e18
commit 7dee184ae4
78 changed files with 239 additions and 698 deletions
@@ -0,0 +1,33 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.Extensions.Logging" />
+    <PackageReference Include="Microsoft.Extensions.Logging.Console" />
+    <PackageReference Include="OpenAI" />
+    <PackageReference Include="OpenTelemetry" />
+    <PackageReference Include="OpenTelemetry.Exporter.Console" />
+    <PackageReference Include="OpenTelemetry.Exporter.OpenTelemetryProtocol" />
+    <PackageReference Include="OpenTelemetry.Instrumentation.Http" />
+    <PackageReference Include="OpenTelemetry.Instrumentation.Runtime" />
+    <PackageReference Include="OpenTelemetry.Extensions.Hosting" />
+    <PackageReference Include="System.Diagnostics.DiagnosticSource" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,216 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using System.ComponentModel;
+using System.Diagnostics;
+using System.Diagnostics.Metrics;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Logging;
+using OpenTelemetry;
+using OpenTelemetry.Logs;
+using OpenTelemetry.Metrics;
+using OpenTelemetry.Resources;
+using OpenTelemetry.Trace;
+
+#region Setup Telemetry
+
+const string SourceName = "OpenTelemetryAspire.ConsoleApp";
+const string ServiceName = "AgentOpenTelemetry";
+
+// Enable telemetry for agents
+AppContext.SetSwitch("Microsoft.Extensions.AI.Agents.EnableTelemetry", true);
+
+// Configure OpenTelemetry for Aspire dashboard
+var otlpEndpoint = Environment.GetEnvironmentVariable("OTEL_EXPORTER_OTLP_ENDPOINT") ?? "http://localhost:4318";
+
+// Create a resource to identify this service
+var resource = ResourceBuilder.CreateDefault()
+    .AddService(ServiceName, serviceVersion: "1.0.0")
+    .AddAttributes(new Dictionary<string, object>
+    {
+        ["service.instance.id"] = Environment.MachineName,
+        ["deployment.environment"] = "development"
+    })
+    .Build();
+
+// Setup tracing with resource
+using var tracerProvider = Sdk.CreateTracerProviderBuilder()
+    .SetResourceBuilder(ResourceBuilder.CreateDefault().AddService(ServiceName, serviceVersion: "1.0.0"))
+    .AddSource(SourceName) // Our custom activity source
+    .AddSource("Microsoft.Extensions.AI.Agents") // Agent Framework telemetry
+    .AddHttpClientInstrumentation() // Capture HTTP calls to OpenAI
+    .AddOtlpExporter(options => { options.Endpoint = new Uri(otlpEndpoint); })
+    .Build();
+
+// Setup metrics with resource and instrument name filtering
+using var meterProvider = Sdk.CreateMeterProviderBuilder()
+    .SetResourceBuilder(ResourceBuilder.CreateDefault().AddService(ServiceName, serviceVersion: "1.0.0"))
+    .AddMeter(SourceName) // Our custom meter
+    .AddMeter("Microsoft.Extensions.AI.Agents") // Agent Framework metrics
+    .AddHttpClientInstrumentation() // HTTP client metrics
+    .AddRuntimeInstrumentation() // .NET runtime metrics
+    .AddOtlpExporter(options => { options.Endpoint = new Uri(otlpEndpoint); })
+    .Build();
+
+// Setup structured logging with OpenTelemetry
+var serviceCollection = new ServiceCollection();
+serviceCollection.AddLogging(loggingBuilder => loggingBuilder
+    .SetMinimumLevel(LogLevel.Debug)
+    .AddOpenTelemetry(options =>
+    {
+        options.SetResourceBuilder(ResourceBuilder.CreateDefault().AddService(ServiceName, serviceVersion: "1.0.0"));
+        options.AddOtlpExporter(otlpOptions =>
+        {
+            otlpOptions.Endpoint = new Uri(otlpEndpoint);
+        });
+        options.IncludeScopes = true;
+        options.IncludeFormattedMessage = true;
+    }));
+
+using var activitySource = new ActivitySource(SourceName);
+using var meter = new Meter(SourceName);
+
+// Create custom metrics
+var interactionCounter = meter.CreateCounter<int>("agent_interactions_total", description: "Total number of agent interactions");
+var responseTimeHistogram = meter.CreateHistogram<double>("agent_response_time_seconds", description: "Agent response time in seconds");
+
+#endregion
+
+var serviceProvider = serviceCollection.BuildServiceProvider();
+var loggerFactory = serviceProvider.GetRequiredService<ILoggerFactory>();
+var appLogger = loggerFactory.CreateLogger<Program>();
+
+Console.WriteLine("""
+    === OpenTelemetry Aspire Demo ===
+    This demo shows OpenTelemetry integration with the Agent Framework.
+    You can view the telemetry data in the Aspire Dashboard.
+    Type your message and press Enter. Type 'exit' or empty message to quit.
+    """);
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT environment variable is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+// Log application startup
+appLogger.LogInformation("OpenTelemetry Aspire Demo application started");
+
+[Description("Get the weather for a given location.")]
+static async Task<string> GetWeather([Description("The location to get the weather for.")] string location)
+{
+    await Task.Delay(2000);
+    return $"The weather in {location} is cloudy with a high of 15°C.";
+}
+
+// To ensure chat client's function calling is captured in the open telemetry, the chat client needs to have UseOpenTelemetry after UseFunctionInvocation
+using var instrumentedChatClient = new AzureOpenAIClient(new Uri(endpoint), new AzureCliCredential())
+    .GetChatClient(deploymentName)
+        .AsIChatClient() // Converts a native OpenAI SDK ChatClient into a Microsoft.Extensions.AI.IChatClient
+        .AsBuilder()
+        .UseFunctionInvocation()
+        .UseOpenTelemetry(loggerFactory: loggerFactory, sourceName: SourceName, (cfg) => { cfg.EnableSensitiveData = true; })
+        .Build();
+
+appLogger.LogInformation("Creating Agent with OpenTelemetry instrumentation");
+// Create the agent with the instrumented chat client
+using var agent = new ChatClientAgent(instrumentedChatClient,
+            name: "OpenTelemetryDemoAgent",
+            instructions: "You are a helpful assistant that provides concise and informative responses.",
+            tools: [AIFunctionFactory.Create(GetWeather)])
+        .WithOpenTelemetry(loggerFactory, SourceName); // Enable telemetry on the agent
+
+var thread = agent.GetNewThread();
+
+appLogger.LogInformation("Agent created successfully with ID: {AgentId}", agent.Id);
+
+// Create a parent span for the entire agent session
+using var sessionActivity = activitySource.StartActivity("Agent Session");
+var sessionId = thread.ConversationId ?? Guid.NewGuid().ToString();
+sessionActivity?.SetTag("agent.name", "OpenTelemetryDemoAgent");
+sessionActivity?.SetTag("session.id", sessionId);
+sessionActivity?.SetTag("session.start_time", DateTimeOffset.UtcNow.ToString("O"));
+
+appLogger.LogInformation("Starting agent session with ID: {SessionId}", sessionId);
+using (appLogger.BeginScope(new Dictionary<string, object> { ["SessionId"] = sessionId, ["AgentName"] = "OpenTelemetryDemoAgent" }))
+{
+    var interactionCount = 0;
+
+    while (true)
+    {
+        Console.Write("You: ");
+        var userInput = Console.ReadLine();
+
+        if (string.IsNullOrWhiteSpace(userInput) || userInput.Equals("exit", StringComparison.OrdinalIgnoreCase))
+        {
+            appLogger.LogInformation("User requested to exit the session");
+            break;
+        }
+
+        interactionCount++;
+        appLogger.LogInformation("Processing user interaction #{InteractionNumber}: {UserInput}", interactionCount, userInput);
+
+        // Create a child span for each individual interaction
+        using var activity = activitySource.StartActivity("Agent Interaction");
+        activity?.SetTag("user.input", userInput);
+        activity?.SetTag("agent.name", "OpenTelemetryDemoAgent");
+        activity?.SetTag("interaction.number", interactionCount);
+
+        var stopwatch = System.Diagnostics.Stopwatch.StartNew();
+
+        try
+        {
+            appLogger.LogDebug("Starting agent execution for interaction #{InteractionNumber}", interactionCount);
+            Console.Write("Agent: ");
+
+            // Run the agent (this will create its own internal telemetry spans)
+            await foreach (var update in agent.RunStreamingAsync(userInput, thread))
+            {
+                Console.Write(update.Text);
+            }
+
+            Console.WriteLine();
+
+            stopwatch.Stop();
+            var responseTime = stopwatch.Elapsed.TotalSeconds;
+
+            // Record metrics (similar to Python example)
+            interactionCounter.Add(1, new KeyValuePair<string, object?>("status", "success"));
+            responseTimeHistogram.Record(responseTime,
+                new KeyValuePair<string, object?>("status", "success"));
+
+            activity?.SetTag("response.success", true);
+
+            appLogger.LogInformation("Agent interaction #{InteractionNumber} completed successfully in {ResponseTime:F2} seconds",
+                interactionCount, responseTime);
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"Error: {ex.Message}");
+            Console.WriteLine();
+
+            stopwatch.Stop();
+            var responseTime = stopwatch.Elapsed.TotalSeconds;
+
+            // Record error metrics
+            interactionCounter.Add(1, new KeyValuePair<string, object?>("status", "error"));
+            responseTimeHistogram.Record(responseTime,
+                new KeyValuePair<string, object?>("status", "error"));
+
+            activity?.SetTag("response.success", false);
+            activity?.SetTag("error.message", ex.Message);
+            activity?.SetStatus(ActivityStatusCode.Error, ex.Message);
+
+            appLogger.LogError(ex, "Agent interaction #{InteractionNumber} failed after {ResponseTime:F2} seconds: {ErrorMessage}",
+                interactionCount, responseTime, ex.Message);
+        }
+    }
+
+    // Add session summary to the parent span
+    sessionActivity?.SetTag("session.total_interactions", interactionCount);
+    sessionActivity?.SetTag("session.end_time", DateTimeOffset.UtcNow.ToString("O"));
+
+    appLogger.LogInformation("Agent session completed. Total interactions: {TotalInteractions}", interactionCount);
+} // End of logging scope
+
+appLogger.LogInformation("OpenTelemetry Aspire Demo application shutting down");
@@ -0,0 +1,210 @@
+# OpenTelemetry Aspire Demo with Azure OpenAI
+
+This demo showcases the integration of OpenTelemetry with the Microsoft Agent Framework using Azure OpenAI and .NET Aspire Dashboard for telemetry visualization.
+
+## Overview
+
+The demo consists of two main components:
+
+1. **Aspire Dashboard** - Provides a web-based interface to visualize OpenTelemetry data
+2. **Console Application** - An interactive console application that demonstrates agent interactions with proper OpenTelemetry instrumentation
+
+## Architecture
+
+```mermaid
+graph TD
+    A["Console App<br/>(Interactive)"] --> B["Agent Framework<br/>with OpenTel<br/>Instrumentation"]
+    B --> C["Azure OpenAI<br/>Service"]
+    A --> D["Aspire Dashboard<br/>(OpenTelemetry Visualization)"]
+    B --> D
+```
+
+## Prerequisites
+
+- .NET 8.0 SDK or later
+- Azure OpenAI service endpoint and deployment configured
+- Azure CLI installed and authenticated (for Azure credential authentication)
+- Docker installed (for running Aspire Dashboard)
+
+## Configuration
+
+### Azure OpenAI Setup
+Set the following environment variables:
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/"
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
+
+**Note**: This demo uses Azure CLI credentials for authentication. Make sure you're logged in with `az login` and have access to the Azure OpenAI resource.
+
+## Running the Demo
+
+### Quick Start (Using Script)
+
+The easiest way to run the demo is using the provided PowerShell script:
+
+```powershell
+.\start-demo.ps1
+```
+
+This script will automatically:
+- ✅ Check prerequisites (Docker, Azure OpenAI configuration)
+- 🔨 Build the console application
+- 🐳 Start the Aspire Dashboard via Docker (with anonymous access)
+- ⏳ Wait for dashboard to be ready (polls port until listening)
+- 🌐 Open your browser with the dashboard
+- 📊 Configure telemetry endpoints (http://localhost:4317)
+- 🎯 Start the interactive console application
+
+### Manual Setup (Step by Step)
+
+If you prefer to run the components manually:
+
+#### Step 1: Start the Aspire Dashboard via Docker
+
+```powershell
+docker run -d --name aspire-dashboard -p 4318:18888 -p 4317:18889 -e DOTNET_DASHBOARD_UNSECURED_ALLOW_ANONYMOUS=true mcr.microsoft.com/dotnet/aspire-dashboard:9.0
+```
+
+#### Step 2: Access the Dashboard
+
+Open your browser to: http://localhost:4318
+
+#### Step 3: Run the Console Application
+
+```powershell
+cd dotnet/demos/AgentOpenTelemetry
+$env:OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4317"
+dotnet run
+```
+
+#### Interacting with the Console Application
+
+You should see a welcome message like:
+
+```
+=== OpenTelemetry Aspire Demo ===
+This demo shows OpenTelemetry integration with the Agent Framework.
+You can view the telemetry data in the Aspire Dashboard.
+Type your message and press Enter. Type 'exit' or empty message to quit.
+
+You:
+```
+
+1. Type your message and press Enter to interact with the AI agent
+2. The agent will respond, and you can continue the conversation
+3. Type `exit` to stop the application
+
+**Note**: Make sure the Aspire Dashboard is running before starting the console application, as the telemetry data will be sent to the dashboard.
+
+#### Step 4: Test the Integration
+
+1. **Start the Aspire Dashboard** (if not already running)
+2. **Run the Console Application** in a separate terminal
+3. **Send a test message** like "Hello, how are you?"
+4. **Check the Aspire Dashboard** - you should see:
+   - New traces appearing in the **Traces** tab
+   - Each trace showing the complete agent interaction flow
+   - Metrics in the **Metrics** tab showing token usage and duration
+   - Logs in the **Structured Logs** tab with detailed information
+
+## Viewing Telemetry Data
+
+### Traces
+1. In the Aspire Dashboard, navigate to the **Traces** tab
+2. You'll see traces for each agent interaction
+3. Each trace contains:
+   - An outer span for the entire agent interaction
+   - Inner spans from the Agent Framework's OpenTelemetry instrumentation
+   - Spans from HTTP calls to Azure OpenAI
+
+### Metrics
+1. Navigate to the **Metrics** tab
+2. View metrics related to:
+   - Agent execution duration
+   - Token usage (input/output tokens)
+   - Request counts
+
+### Logs
+1. Navigate to the **Structured Logs** tab
+2. Filter by the console application to see detailed logs
+3. Logs include information about user inputs, agent responses, and any errors
+
+## Key Features Demonstrated
+
+### OpenTelemetry Integration
+- **Automatic instrumentation** of Agent Framework operations
+- **Custom spans** for user interactions
+- **Proper span lifecycle management** (create → execute → close)
+- **Telemetry correlation** across the entire request flow
+
+### Agent Framework Features
+- **ChatClientAgent** with Azure OpenAI integration
+- **OpenTelemetry wrapper** using `.WithOpenTelemetry()`
+- **Conversation threading** for multi-turn conversations
+- **Error handling** with telemetry correlation
+
+### Aspire Dashboard Features
+- **Real-time telemetry visualization**
+- **Distributed tracing** across services
+- **Metrics and logging** integration
+- **Resource management** and monitoring
+
+## Available Script
+
+The demo includes a PowerShell script to make running the demo easy:
+
+### `start-demo.ps1`
+Complete demo startup script that handles everything automatically.
+
+**Usage:**
+```powershell
+.\start-demo.ps1           # Start the complete demo
+```
+
+**Features:**
+- **Automatic configuration detection** - Checks for Azure OpenAI configuration
+- **Project building** - Automatically builds projects before running
+- **Error handling** - Provides clear error messages if something goes wrong
+- **Multi-window support** - Opens dashboard in separate window for better experience
+- **Browser auto-launch** - Automatically opens the Aspire Dashboard in your browser
+- **Docker integration** - Uses Docker to run the Aspire Dashboard
+
+**Docker Endpoints:**
+- **Aspire Dashboard**: `http://localhost:4318`
+- **OTLP Telemetry**: `http://localhost:4317`
+
+## Troubleshooting
+
+### Port Conflicts
+If you encounter port binding errors, try:
+1. Stop any existing Docker containers using the same ports (`docker stop aspire-dashboard`)
+2. Or kill any processes using the conflicting ports
+
+### Authentication Issues
+- Ensure your Azure OpenAI endpoint is correctly configured
+- Check that the environment variables are set in the correct terminal session
+- Verify you're logged in with Azure CLI (`az login`) and have access to the Azure OpenAI resource
+- Ensure the Azure OpenAI deployment name matches your actual deployment
+
+### Build Issues
+- Ensure you're using .NET 9.0 SDK
+- Run `dotnet restore` if you encounter package restore issues
+- Check that all project references are correctly resolved
+
+## Project Structure
+
+```
+AgentOpenTelemetry/
+├── AgentOpenTelemetry.csproj             # Project file with dependencies
+├── Program.cs                            # Main application with Azure OpenAI agent integration
+├── start-demo.ps1                        # PowerShell script to start the demo
+└── README.md                             # This file
+```
+
+## Next Steps
+
+- Experiment with different prompts to see various telemetry patterns
+- Explore the Aspire Dashboard's filtering and search capabilities
+- Try modifying the OpenTelemetry configuration to add custom metrics or spans
+- Integrate additional services to see distributed tracing in action
@@ -0,0 +1,139 @@
+# OpenTelemetry Console Demo with Aspire Dashboard (Docker)
+# This script starts the Aspire Dashboard via Docker and the Console Application
+
+Write-Host "Starting OpenTelemetry Console Demo..." -ForegroundColor Green
+Write-Host ""
+
+# Check if we're in the right directory
+if (!(Test-Path "AgentOpenTelemetry.csproj")) {
+    Write-Host "Error: Please run this script from the AgentOpenTelemetry directory" -ForegroundColor Red
+    Write-Host "Expected to find AgentOpenTelemetry.csproj file" -ForegroundColor Red
+    exit 1
+}
+
+# Check if Docker is running
+try {
+    docker version | Out-Null
+    Write-Host "Docker is running" -ForegroundColor Green
+} catch {
+    Write-Host "Docker is not running or not installed" -ForegroundColor Red
+    Write-Host "Please start Docker Desktop and try again" -ForegroundColor Red
+    exit 1
+}
+
+# Check for Azure OpenAI configuration
+if ($env:AZURE_OPENAI_ENDPOINT) {
+    Write-Host "Found Azure OpenAI endpoint: $($env:AZURE_OPENAI_ENDPOINT)" -ForegroundColor Green
+    if ($env:AZURE_OPENAI_DEPLOYMENT_NAME) {
+        Write-Host "Using deployment: $($env:AZURE_OPENAI_DEPLOYMENT_NAME)" -ForegroundColor Green
+    } else {
+        Write-Host "Using default deployment: gpt-4o-mini" -ForegroundColor Cyan
+    }
+} else {
+    Write-Host "Warning: AZURE_OPENAI_ENDPOINT not found!" -ForegroundColor Yellow
+    Write-Host "Please set the AZURE_OPENAI_ENDPOINT environment variable" -ForegroundColor Yellow
+    Write-Host "Example: `$env:AZURE_OPENAI_ENDPOINT='https://your-resource.openai.azure.com/'" -ForegroundColor Yellow
+    Write-Host ""
+}
+
+# Build console application
+Write-Host ""
+Write-Host "Building console application..." -ForegroundColor Cyan
+
+$buildResult = dotnet build --verbosity quiet
+if ($LASTEXITCODE -ne 0) {
+    Write-Host "Failed to build Console App" -ForegroundColor Red
+    exit 1
+}
+
+Write-Host "Build completed successfully" -ForegroundColor Green
+
+Write-Host ""
+Write-Host "Starting Aspire Dashboard via Docker..." -ForegroundColor Cyan
+
+# Stop any existing Aspire Dashboard container
+Write-Host "Stopping any existing Aspire Dashboard container..." -ForegroundColor Gray
+docker stop aspire-dashboard-afdemo 2>$null | Out-Null
+docker rm aspire-dashboard-afdemo 2>$null | Out-Null
+
+# Start Aspire Dashboard in Docker daemon mode with fixed token
+Write-Host "Starting Aspire Dashboard container..." -ForegroundColor Green
+$fixedToken = "demo-token-12345"
+$dockerResult = docker run -d `
+    --name aspire-dashboard-afdemo `
+    -p 4318:18888 `
+    -p 4317:18889 `
+    -e DOTNET_DASHBOARD_UNSECURED_ALLOW_ANONYMOUS=true `
+    --restart unless-stopped `
+    mcr.microsoft.com/dotnet/aspire-dashboard:9.0
+
+if ($LASTEXITCODE -ne 0) {
+    Write-Host "Failed to start Aspire Dashboard container" -ForegroundColor Red
+    Write-Host "Make sure Docker is running and try again" -ForegroundColor Red
+    exit 1
+}
+
+Write-Host "Aspire Dashboard started successfully!" -ForegroundColor Green
+Write-Host "OTLP Endpoint: http://localhost:4318" -ForegroundColor Cyan
+
+# Wait for dashboard to be ready by polling the port
+Write-Host "Waiting for dashboard to be ready..." -ForegroundColor Gray
+$maxWaitSeconds = 10
+$waitCount = 0
+$dashboardReady = $false
+
+while ($waitCount -lt $maxWaitSeconds -and !$dashboardReady) {
+    try {
+        $tcpConnection = Test-NetConnection -ComputerName "localhost" -Port 4317 -InformationLevel Quiet -WarningAction SilentlyContinue -ErrorAction SilentlyContinue
+        if ($tcpConnection) {
+            $dashboardReady = $true
+            Write-Host "Dashboard is ready! (took $waitCount seconds)" -ForegroundColor Green
+        } else {
+            Write-Host "." -NoNewline -ForegroundColor Gray
+            Start-Sleep -Seconds 1
+            $waitCount++
+        }
+    } catch {
+        Write-Host "." -NoNewline -ForegroundColor Gray
+        Start-Sleep -Seconds 1
+        $waitCount++
+    }
+}
+
+if (!$dashboardReady) {
+    Write-Host ""
+    Write-Host "Dashboard port 4317 not responding after $maxWaitSeconds seconds" -ForegroundColor Yellow
+    Write-Host "   Continuing anyway - dashboard might still be starting..." -ForegroundColor Yellow
+} else {
+    Write-Host ""
+}
+
+# Open the dashboard in browser (anonymous access enabled)
+Write-Host "Opening dashboard in browser..." -ForegroundColor Green
+Write-Host "Dashboard URL: http://localhost:4318" -ForegroundColor Cyan
+Start-Process "http://localhost:4318"
+
+Write-Host ""
+Write-Host "Starting Console Application..." -ForegroundColor Cyan
+Write-Host "You can now interact with the AI agent!" -ForegroundColor Green
+Write-Host ""
+
+# Set the OTLP endpoint for the console application (Docker Aspire Dashboard)
+$otlpEndpoint = "http://localhost:4317"
+Write-Host "Using OTLP endpoint: $otlpEndpoint" -ForegroundColor Cyan
+
+$env:OTEL_EXPORTER_OTLP_ENDPOINT = $otlpEndpoint
+
+# Start the console application in the current window
+Write-Host ""
+Write-Host "Starting the console application..." -ForegroundColor Green
+Write-Host "Tip: The dashboard should now be open in your browser!" -ForegroundColor Cyan
+Write-Host ""
+
+dotnet run --no-build
+
+Write-Host ""
+Write-Host "Demo completed!" -ForegroundColor Green
+Write-Host "The Aspire Dashboard is still running in Docker." -ForegroundColor Gray
+Write-Host "You can view telemetry data in the browser tab that opened." -ForegroundColor Gray
+Write-Host "To stop the dashboard: docker stop aspire-dashboard-afdemo" -ForegroundColor Gray
@@ -40,10 +40,10 @@
  </ItemGroup>

  <ItemGroup>
-    <ProjectReference Include="..\..\src\Microsoft.Agents.Orchestration\Microsoft.Agents.Orchestration.csproj" />
-    <ProjectReference Include="..\..\src\Microsoft.Extensions.AI.Agents.AzureAI\Microsoft.Extensions.AI.Agents.AzureAI.csproj" />
-    <ProjectReference Include="..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
-    <ProjectReference Include="..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Agents.Orchestration\Microsoft.Agents.Orchestration.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Extensions.AI.Agents.AzureAI\Microsoft.Extensions.AI.Agents.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
  </ItemGroup>

  <ItemGroup>
@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="A2A" />
+    <PackageReference Include="System.Net.ServerSentEvents" VersionOverride="10.0.0-preview.5.25277.114" />
+    <PackageReference Include="Microsoft.Bcl.AsyncInterfaces" VersionOverride="10.0.0-preview.5.25277.114" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.A2A\Microsoft.Extensions.AI.Agents.A2A.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,20 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with an existing A2A agent.
+
+using System;
+using A2A;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.Extensions.AI.Agents.A2A;
+
+var a2aAgentHost = Environment.GetEnvironmentVariable("A2A_AGENT_HOST") ?? throw new InvalidOperationException("A2A_AGENT_HOST is not set.");
+
+// Initialize an A2ACardResolver to get an A2A agent card.
+A2ACardResolver agentCardResolver = new(new Uri(a2aAgentHost));
+
+// Create an instance of the AIAgent for an existing A2A agent specified by the agent card.
+AIAgent agent = await agentCardResolver.GetAIAgentAsync();
+
+// Invoke the agent and output the text result.
+AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+Console.WriteLine(response);
@@ -0,0 +1,34 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Access to the A2A agent host service
+
+**Note**: These samples need to be run against a valid A2A server. If no A2A server is available, they can be run against the echo-agent that can be spun up locally by following the guidelines at: https://github.com/a2aproject/a2a-dotnet/blob/main/samples/AgentServer/README.md
+
+Set the following environment variables:
+
+```powershell
+$env:A2A_AGENT_HOST="https://your-a2a-agent-host" # Replace with your A2A agent host endpoint
+```
+
+## Advanced scenario
+
+This method can be used to create AI agents for A2A agents whose hosts support the [Direct Configuration / Private Discovery](https://github.com/a2aproject/A2A/blob/main/docs/topics/agent-discovery.md#3-direct-configuration--private-discovery) discovery mechanism.
+
+```csharp
+using A2A;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.Extensions.AI.Agents.A2A;
+
+// Create an A2AClient pointing to your `echo` A2A agent endpoint
+A2AClient a2aClient = new(new Uri("https://your-a2a-agent-host/echo"));
+
+// Create an AIAgent from the A2AClient
+AIAgent agent = a2aClient.GetAIAgent();
+
+// Run the agent
+AgentRunResponse response = await agent.RunAsync("Tell me a joke about a pirate.");
+Console.WriteLine(response);
+```
@@ -0,0 +1,22 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Agents.Persistent" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.AzureAI\Microsoft.Extensions.AI.Agents.AzureAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,41 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure Foundry Agents as the backend.
+
+using System;
+using Azure.AI.Agents.Persistent;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("AZURE_FOUNDRY_PROJECT_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_FOUNDRY_PROJECT_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Get a client to create/retrieve server side agents with.
+var persistentAgentsClient = new PersistentAgentsClient(endpoint, new AzureCliCredential());
+
+// You can create a server side persistent agent with the Azure.AI.Agents.Persistent SDK.
+var agentMetadata = await persistentAgentsClient.Administration.CreateAgentAsync(
+    model: deploymentName,
+    name: JokerName,
+    instructions: JokerInstructions);
+
+// You can retrieve an already created server side persistent agent as an AIAgent.
+AIAgent agent1 = await persistentAgentsClient.GetAIAgentAsync(agentMetadata.Value.Id);
+
+// You can also create a server side persistent agent and return it as an AIAgent directly.
+AIAgent agent2 = await persistentAgentsClient.CreateAIAgentAsync(
+    model: deploymentName,
+    name: JokerName,
+    instructions: JokerInstructions);
+
+// You can then invoke the agent like any other AIAgent.
+AgentThread thread = agent1.GetNewThread();
+Console.WriteLine(await agent1.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Cleanup for sample purposes.
+await persistentAgentsClient.Threads.DeleteThreadAsync(thread.ConversationId);
+await persistentAgentsClient.Administration.DeleteAgentAsync(agent1.Id);
+await persistentAgentsClient.Administration.DeleteAgentAsync(agent2.Id);
@@ -0,0 +1,16 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 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
+```
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,24 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure OpenAI Chat Completion as the backend.
+
+using System;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,16 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI 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 OpenAI 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_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,26 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure OpenAI Responses as the backend.
+
+#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+
+using System;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetOpenAIResponseClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,16 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI 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 OpenAI 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_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
@@ -0,0 +1,20 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Microsoft.ML.OnnxRuntimeGenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,20 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with ONNX as the backend.
+
+using System;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.ML.OnnxRuntimeGenAI;
+
+// E.g. C:\repos\Phi-4-mini-instruct-onnx\cpu_and_mobile\cpu-int4-rtn-block-32-acc-level-4
+var modelPath = Environment.GetEnvironmentVariable("ONNX_MODEL_PATH") ?? throw new InvalidOperationException("ONNX_MODEL_PATH is not set.");
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Get a chat client for ONNX and use it to construct an AIAgent.
+using OnnxRuntimeGenAIChatClient chatClient = new(modelPath);
+AIAgent agent = new ChatClientAgent(chatClient, JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,12 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- An ONNX model downloaded to your machine
+
+Set the following environment variables:
+
+```powershell
+$env:ONNX_MODEL_PATH="C:\repos\Phi-4-mini-instruct-onnx\cpu_and_mobile\cpu-int4-rtn-block-32-acc-level-4" # Replace with your model path
+```
@@ -0,0 +1,17 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,21 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with OpenAI Chat Completion as the backend.
+
+using System;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var apiKey = Environment.GetEnvironmentVariable("OPENAI_APIKEY") ?? throw new InvalidOperationException("OPENAI_APIKEY is not set.");
+var modelName = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new OpenAIClient(
+    apiKey)
+     .GetChatClient(modelName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,13 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- OpenAI api key
+
+Set the following environment variables:
+
+```powershell
+$env:OPENAI_APIKEY="*****" # Replace with your OpenAI api key
+$env:OPENAI_MODEL="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
@@ -0,0 +1,17 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,23 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with OpenAI Responses as the backend.
+
+#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
+
+using System;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var apiKey = Environment.GetEnvironmentVariable("OPENAI_APIKEY") ?? throw new InvalidOperationException("OPENAI_APIKEY is not set.");
+var modelName = Environment.GetEnvironmentVariable("OPENAI_MODEL") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new OpenAIClient(
+    apiKey)
+     .GetOpenAIResponseClient(modelName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
@@ -0,0 +1,13 @@
+# Prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- OpenAI api key
+
+Set the following environment variables:
+
+```powershell
+$env:OPENAI_APIKEY="*****" # Replace with your OpenAI api key
+$env:OPENAI_MODEL="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
@@ -0,0 +1,56 @@
+# Creating an AIAgent instance for various providers
+
+These samples show how to create an AIAgent instance using various providers.
+This is not an exhaustive list, but shows a variety of the more popular options.
+
+For other samples that demonstrate how to use AIAgent instances,
+see the [Getting Started Steps](../GettingStartedSteps/README.md) samples.
+
+## Prerequisites
+
+See the README.md for each sample for the prerequisites for that sample.
+## Samples
+
+|Sample|Description|
+|---|---|
+|[Creating an AIAgent with A2A](./AIAgent_With_A2A/)|This sample demonstrates how to create AIAgent for an existing A2A agent.|
+|[Creating an AIAgent with AzureFoundry](./AIAgent_With_AzureFoundry/)|This sample demonstrates how to create an Azure Foundry agent and expose it as an AIAgent|
+|[Creating an AIAgent with Azure OpenAI ChatCompletion](./AIAgent_With_AzureOpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using Azure OpenAI ChatCompletion as the underlying inference service|
+|[Creating an AIAgent with Azure OpenAI Responses](./AIAgent_With_AzureOpenAIResponses/)|This sample demonstrates how to create an AIAgent using Azure OpenAI Responses as the underlying inference service|
+|[Creating an AIAgent with ONNX](./AIAgent_With_ONNX/)|This sample demonstrates how to create an AIAgent using ONNX as the underlying inference service|
+|[Creating an AIAgent with OpenAI ChatCompletion](./AIAgent_With_OpenAIChatCompletion/)|This sample demonstrates how to create an AIAgent using OpenAI ChatCompletion as the underlying inference service|
+|[Creating an AIAgent with OpenAI Responses](./AIAgent_With_OpenAIResponses/)|This sample demonstrates how to create an AIAgent using OpenAI Responses as the underlying inference service|
+
+## Running the samples from the console
+
+To run the samples, navigate to the desired sample directory, e.g.
+
+```powershell
+cd AIAgent_With_AzureOpenAIChatCompletion
+```
+
+Set the required environment variables as documented in the sample readme.
+If the variables are not set, you will be prompted for the values when running the samples.
+Execute the following command to build the sample:
+
+```powershell
+dotnet build
+```
+
+Execute the following command to run the sample:
+
+```powershell
+dotnet run --no-build
+```
+
+Or just build and run in one step:
+
+```powershell
+dotnet run
+```
+
+## Running the samples from Visual Studio
+
+Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
+
+You will be prompted for any required environment variables if they are not already set.
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,30 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure OpenAI as the backend.
+
+using System;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
+
+// Invoke the agent with streaming support.
+await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate."))
+{
+    Console.WriteLine(update);
+}
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,37 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with a multi-turn conversation.
+
+using System;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Invoke the agent with a multi-turn conversation, where the context is preserved in the thread object.
+AgentThread thread = agent.GetNewThread();
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
+Console.WriteLine(await agent.RunAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread));
+
+// Invoke the agent with a multi-turn conversation and streaming, where the context is preserved in the thread object.
+thread = agent.GetNewThread();
+await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate.", thread))
+{
+    Console.WriteLine(update);
+}
+await foreach (var update in agent.RunStreamingAsync("Now add some emojis to the joke and tell it in the voice of a pirate's parrot.", thread))
+{
+    Console.WriteLine(update);
+}
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,35 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use a ChatClientAgent with function tools.
+// It shows both non-streaming and streaming agent interactions using menu-related tools.
+
+using System;
+using System.ComponentModel;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+[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, and provide the function tool to the agent.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(instructions: "You are a helpful assistant", tools: [AIFunctionFactory.Create(GetWeather)]);
+
+// Non-streaming agent interaction with function tools.
+Console.WriteLine(await agent.RunAsync("What is the weather like in Amsterdam?"));
+
+// Streaming agent interaction with function tools.
+await foreach (var update in agent.RunStreamingAsync("What is the weather like in Amsterdam?"))
+{
+    Console.WriteLine(update);
+}
@@ -0,0 +1,24 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="System.Linq.Async" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,68 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample demonstrates how to use a ChatClientAgent with function tools that require a human in the loop for approvals.
+// It shows both non-streaming and streaming agent interactions using menu-related tools.
+// If the agent is hosted in a service, with a remote user, combine this sample with the Persisted Conversations sample to persist the chat history
+// while the agent is waiting for user input.
+
+using System;
+using System.ComponentModel;
+using System.Linq;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-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)
+    => $"The weather in {location} is cloudy with a high of 15°C.";
+
+// Create the chat client and agent.
+// Note that we are wrapping the function tool with ApprovalRequiredAIFunction to require user approval before invoking it.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);
+
+// Call the agent and check if there are any user input requests to handle.
+AgentThread thread = agent.GetNewThread();
+var response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
+var userInputRequests = response.UserInputRequests.ToList();
+
+// For streaming use:
+// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread).ToListAsync();
+// userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
+
+while (userInputRequests.Count > 0)
+{
+    // Ask the user to approve each function call request.
+    // For simplicity, we are assuming here that only function approval requests are being made.
+    var userInputResponses = userInputRequests
+        .OfType<FunctionApprovalRequestContent>()
+        .Select(functionApprovalRequest =>
+        {
+            Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {functionApprovalRequest.FunctionCall.Name}");
+            return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
+        })
+        .ToList();
+
+    // Pass the user input responses back to the agent for further processing.
+    response = await agent.RunAsync(userInputResponses, thread);
+
+    userInputRequests = response.UserInputRequests.ToList();
+
+    // For streaming use:
+    // updates = await agent.RunStreamingAsync(userInputResponses, thread).ToListAsync();
+    // userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
+}
+
+Console.WriteLine($"\nAgent: {response}");
+
+// For streaming use:
+// Console.WriteLine($"\nAgent: {updates.ToAgentRunResponse()}");
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,76 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure OpenAI as the backend, to produce structured output using JSON schema from a class.
+
+using System;
+using System.Text.Json;
+using System.Text.Json.Serialization;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+using SampleApp;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+// Create the agent options, specifying the response format to use a JSON schema based on the PersonInfo class.
+ChatClientAgentOptions agentOptions = new(name: "HelpfulAssistant", instructions: "You are a helpful assistant.")
+{
+    ChatOptions = new()
+    {
+        ResponseFormat = ChatResponseFormatJson.ForJsonSchema(
+            schema: AIJsonUtilities.CreateJsonSchema(typeof(PersonInfo)),
+            schemaName: "PersonInfo",
+            schemaDescription: "Information about a person including their name, age, and occupation")
+    }
+};
+
+// Create the agent using Azure OpenAI.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+        .GetChatClient(deploymentName)
+        .CreateAIAgent(agentOptions);
+
+// Invoke the agent with some unstructured input, to extract the structured information from.
+var response = await agent.RunAsync("Please provide information about John Smith, who is a 35-year-old software engineer.");
+
+// Deserialize the response into the PersonInfo class.
+var personInfo = response.Deserialize<PersonInfo>(JsonSerializerOptions.Web);
+
+Console.WriteLine("Assistant Output:");
+Console.WriteLine($"Name: {personInfo.Name}");
+Console.WriteLine($"Age: {personInfo.Age}");
+Console.WriteLine($"Occupation: {personInfo.Occupation}");
+
+// Invoke the agent with some unstructured input while streaming, to extract the structured information from.
+var updates = agent.RunStreamingAsync("Please provide information about John Smith, who is a 35-year-old software engineer.");
+
+// Assemble all the parts of the streamed output, since we can only deserialize once we have the full json,
+// then deserialize the response into the PersonInfo class.
+personInfo = (await updates.ToAgentRunResponseAsync()).Deserialize<PersonInfo>(JsonSerializerOptions.Web);
+
+Console.WriteLine("Assistant Output:");
+Console.WriteLine($"Name: {personInfo.Name}");
+Console.WriteLine($"Age: {personInfo.Age}");
+Console.WriteLine($"Occupation: {personInfo.Occupation}");
+
+namespace SampleApp
+{
+    /// <summary>
+    /// Represents information about a person, including their name, age, and occupation, matched to the JSON schema used in the agent.
+    /// </summary>
+    public class PersonInfo
+    {
+        [JsonPropertyName("name")]
+        public string? Name { get; set; }
+
+        [JsonPropertyName("age")]
+        public int? Age { get; set; }
+
+        [JsonPropertyName("occupation")]
+        public string? Occupation { get; set; }
+    }
+}
@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,46 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with a conversation that can be persisted to disk.
+
+using System;
+using System.IO;
+using System.Text.Json;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Create the agent
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName);
+
+// Start a new thread for the agent conversation.
+AgentThread thread = agent.GetNewThread();
+
+// Run the agent with a new thread.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Serialize the thread state to a JsonElement, so it can be stored for later use.
+JsonElement serializedThread = await thread.SerializeAsync();
+
+// Save the serialized thread to a temporary file (for demonstration purposes).
+string tempFilePath = Path.GetTempFileName();
+await File.WriteAllTextAsync(tempFilePath, JsonSerializer.Serialize(serializedThread));
+
+// Load the serialized thread from the temporary file (for demonstration purposes).
+JsonElement reloadedSerializedThread = JsonSerializer.Deserialize<JsonElement>(await File.ReadAllTextAsync(tempFilePath));
+
+// Deserialize the thread state after loading from storage.
+AgentThread resumedThread = await agent.DeserializeThreadAsync(reloadedSerializedThread);
+
+// Run the agent again with the resumed thread.
+Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
@@ -0,0 +1,25 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.SemanticKernel.Connectors.InMemory" />
+    <PackageReference Include="System.Linq.Async" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,155 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+#pragma warning disable CA1869 // Cache and reuse 'JsonSerializerOptions' instances
+
+// This sample shows how to create and use a simple AI agent with a conversation that can be persisted to disk.
+
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text.Json;
+using System.Threading;
+using System.Threading.Tasks;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.Extensions.VectorData;
+using Microsoft.SemanticKernel.Connectors.InMemory;
+using OpenAI;
+using SampleApp;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Create a vector store to store the chat messages in.
+// Replace this with a vector store implementation of your choice if you want to persist the chat history to disk.
+VectorStore vectorStore = new InMemoryVectorStore();
+
+// Create the agent
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(new ChatClientAgentOptions
+     {
+         Name = JokerName,
+         Instructions = JokerInstructions,
+         ChatMessageStoreFactory = () =>
+         {
+             // Create a new chat message store for this agent that stores the messages in a vector store.
+             // Each thread must get its own copy of the VectorChatMessageStore, since the store
+             // also contains the id that the thread is stored under.
+             return new VectorChatMessageStore(vectorStore);
+         }
+     });
+
+// Start a new thread for the agent conversation.
+AgentThread thread = agent.GetNewThread();
+
+// Run the agent with the thread that stores conversation history in the vector store.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate.", thread));
+
+// Serialize the thread state, so it can be stored for later use.
+// Since the chat history is stored in the vector store, the serialized thread
+// only contains the guid that the messages are stored under in the vector store.
+JsonElement serializedThread = await thread.SerializeAsync();
+
+Console.WriteLine("\n--- Serialized thread ---\n");
+Console.WriteLine(JsonSerializer.Serialize(serializedThread, new JsonSerializerOptions { WriteIndented = true }));
+
+// The serialized thread can now be saved to a database, file, or any other storage mechanism
+// and loaded again later.
+
+// Deserialize the thread state after loading from storage.
+AgentThread resumedThread = await agent.DeserializeThreadAsync(serializedThread);
+
+// Run the agent with the thread that stores conversation history in the vector store a second time.
+Console.WriteLine(await agent.RunAsync("Now tell the same joke in the voice of a pirate, and add some emojis to the joke.", resumedThread));
+
+namespace SampleApp
+{
+    /// <summary>
+    /// A sample implementation of <see cref="IChatMessageStore"/> that stores chat messages in a vector store.
+    /// </summary>
+    /// <param name="vectorStore">The vector store to store the messages in.</param>
+    internal sealed class VectorChatMessageStore(VectorStore vectorStore) : IChatMessageStore
+    {
+        private string? _threadId;
+
+        public string? ThreadId => this._threadId;
+
+        public async Task AddMessagesAsync(IReadOnlyCollection<ChatMessage> messages, CancellationToken cancellationToken)
+        {
+            this._threadId ??= Guid.NewGuid().ToString();
+
+            var collection = vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
+            await collection.EnsureCollectionExistsAsync(cancellationToken);
+
+            await collection.UpsertAsync(messages.Select(x => new ChatHistoryItem()
+            {
+                Key = this._threadId + x.MessageId,
+                Timestamp = DateTimeOffset.UtcNow,
+                ThreadId = this._threadId,
+                SerializedMessage = JsonSerializer.Serialize(x),
+                MessageText = x.Text
+            }), cancellationToken);
+        }
+
+        public async Task<IEnumerable<ChatMessage>> GetMessagesAsync(CancellationToken cancellationToken)
+        {
+            var collection = vectorStore.GetCollection<string, ChatHistoryItem>("ChatHistory");
+            await collection.EnsureCollectionExistsAsync(cancellationToken);
+
+            var records = await collection
+                .GetAsync(
+                    x => x.ThreadId == this._threadId, 10,
+                    new() { OrderBy = x => x.Descending(y => y.Timestamp) },
+                    cancellationToken)
+                .ToListAsync(cancellationToken);
+
+            var messages = records
+                .Select(x => JsonSerializer.Deserialize<ChatMessage>(x.SerializedMessage!)!)
+                .ToList();
+            messages.Reverse();
+            return messages;
+        }
+
+        public ValueTask<JsonElement?> SerializeStateAsync(JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
+        {
+            // We have to serialize the thread id, so that on deserialization we can retrieve the messages using the same thread id.
+            return new ValueTask<JsonElement?>(JsonSerializer.SerializeToElement(this._threadId));
+        }
+
+        public ValueTask DeserializeStateAsync(JsonElement? serializedStoreState, JsonSerializerOptions? jsonSerializerOptions = null, CancellationToken cancellationToken = default)
+        {
+            // Here we can deserialize the thread id so that we can access the same messages as before the suspension.
+            this._threadId = JsonSerializer.Deserialize<string>((JsonElement)serializedStoreState!);
+            return new ValueTask();
+        }
+
+        /// <summary>
+        /// The data structure used to store chat history items in the vector store.
+        /// </summary>
+        private sealed class ChatHistoryItem
+        {
+            [VectorStoreKey]
+            public string? Key { get; set; }
+
+            [VectorStoreData]
+            public string? ThreadId { get; set; }
+
+            [VectorStoreData]
+            public DateTimeOffset? Timestamp { get; set; }
+
+            [VectorStoreData]
+            public string? SerializedMessage { get; set; }
+
+            [VectorStoreData]
+            public string? MessageText { get; set; }
+        }
+    }
+}
@@ -0,0 +1,25 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="OpenTelemetry" />
+    <PackageReference Include="OpenTelemetry.Exporter.Console" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,45 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample shows how to create and use a simple AI agent with Azure OpenAI as the backend that logs telemetry using OpenTelemetry.
+
+using System;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI.Agents;
+using OpenAI;
+using OpenTelemetry;
+using OpenTelemetry.Trace;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+
+// Enable telemetry
+AppContext.SetSwitch("Microsoft.Extensions.AI.Agents.EnableTelemetry", true);
+
+// Create TracerProvider with console exporter
+// This will output the telemetry data to the console.
+string sourceName = Guid.NewGuid().ToString();
+using var tracerProvider = Sdk.CreateTracerProviderBuilder()
+    .AddSource(sourceName)
+    .AddConsoleExporter()
+    .Build();
+
+// Create the agent, and enable OpenTelemetry instrumentation.
+AIAgent agent = new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+     .GetChatClient(deploymentName)
+     .CreateAIAgent(JokerInstructions, JokerName)
+     .WithOpenTelemetry(sourceName: sourceName);
+
+// Invoke the agent and output the text result.
+Console.WriteLine(await agent.RunAsync("Tell me a joke about a pirate."));
+
+// Invoke the agent with streaming support.
+await foreach (var update in agent.RunStreamingAsync("Tell me a joke about a pirate."))
+{
+    Console.WriteLine(update);
+}
@@ -0,0 +1,24 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFramework>net9.0</TargetFramework>
+    <LangVersion>12</LangVersion>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>disable</ImplicitUsings>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.OpenAI" />
+    <PackageReference Include="Azure.Identity" />
+    <PackageReference Include="Microsoft.Extensions.AI.OpenAI" />
+    <PackageReference Include="Microsoft.Extensions.Hosting" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents.OpenAI\Microsoft.Extensions.AI.Agents.OpenAI.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Extensions.AI.Agents\Microsoft.Extensions.AI.Agents.csproj" />
+  </ItemGroup>
+
+</Project>
@@ -0,0 +1,99 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+#pragma warning disable CA1812
+
+// This sample shows how to use dependency injection to register an AIAgent and use it from a hosted service with a user input chat loop.
+
+using System;
+using System.Threading;
+using System.Threading.Tasks;
+using Azure.AI.OpenAI;
+using Azure.Identity;
+using Microsoft.Extensions.AI;
+using Microsoft.Extensions.AI.Agents;
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+
+var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
+var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
+
+// Create a host builder that we will register services with and then run.
+HostApplicationBuilder builder = Host.CreateApplicationBuilder(args);
+
+// Add agent options to the service collection.
+const string JokerName = "Joker";
+const string JokerInstructions = "You are good at telling jokes.";
+builder.Services.AddSingleton(new ChatClientAgentOptions(JokerInstructions, JokerName));
+
+// Add a chat client to the service collection.
+builder.Services.AddKeyedChatClient("AzureOpenAI", (sp) => new AzureOpenAIClient(
+    new Uri(endpoint),
+    new AzureCliCredential())
+        .GetChatClient(deploymentName)
+        .AsIChatClient());
+
+// Add the AI agent to the service collection.
+builder.Services.AddSingleton<AIAgent>((sp) => new ChatClientAgent(
+    chatClient: sp.GetRequiredKeyedService<IChatClient>("AzureOpenAI"),
+    options: sp.GetRequiredService<ChatClientAgentOptions>()));
+
+// Add a sample service that will use the agent to respond to user input.
+builder.Services.AddHostedService<SampleApp.SampleService>();
+
+// Create a cancellation token and source to pass to the sample service that can
+// be used to signal shutdown of the application.
+CancellationTokenSource appShutdownCancellationTokenSource = new();
+CancellationToken appShutdownCancellationToken = appShutdownCancellationTokenSource.Token;
+builder.Services.AddKeyedSingleton("AppShutdown", appShutdownCancellationTokenSource);
+
+// Build and run the host.
+using IHost host = builder.Build();
+await host.RunAsync(appShutdownCancellationToken).ConfigureAwait(false);
+
+namespace SampleApp
+{
+    /// <summary>
+    /// A sample service that uses an AI agent to respond to user input.
+    /// </summary>
+    internal sealed class SampleService(AIAgent agent, [FromKeyedServices("AppShutdown")] CancellationTokenSource appShutdownCancellationTokenSource) : IHostedService
+    {
+        private AgentThread? _thread;
+
+        public async Task StartAsync(CancellationToken cancellationToken)
+        {
+            // Create a thread that will be used for the entirety of the service lifetime so that the user can ask follow up questions.
+            this._thread = agent.GetNewThread();
+            _ = this.RunAsync(cancellationToken);
+        }
+
+        public async Task RunAsync(CancellationToken cancellationToken)
+        {
+            // Delay a little to allow the service to finish starting.
+            await Task.Delay(100, cancellationToken);
+
+            while (cancellationToken.IsCancellationRequested is false)
+            {
+                Console.WriteLine("\nAgent: Ask me to tell you a joke about a specific topic. To exit just press Ctrl+C or enter without any input.\n");
+                Console.Write("> ");
+                var input = Console.ReadLine();
+
+                // If the user enters no input, signal the application to shut down.
+                if (string.IsNullOrWhiteSpace(input))
+                {
+                    appShutdownCancellationTokenSource.Cancel();
+                    break;
+                }
+
+                // Stream the output to the console as it is generated.
+                await foreach (var update in agent.RunStreamingAsync(input, this._thread!, cancellationToken: cancellationToken))
+                {
+                    Console.Write(update);
+                }
+
+                Console.WriteLine();
+            }
+        }
+
+        public Task StopAsync(CancellationToken cancellationToken) => Task.CompletedTask;
+    }
+}
@@ -0,0 +1,75 @@
+# Getting started with agents
+
+The getting started with agents samples demonstrate the fundamental concepts and functionalities
+of single agents and can be used with any agent type.
+
+While the functionality can be used with any agent type, these samples use Azure OpenAI as the AI provider
+and use ChatCompletion as the type of service.
+
+For other samples that demonstrate how to create and configure each type of agent that come with the agent framework,
+see the [How to create an agent for each provider](../AgentProviders/README.md) samples.
+
+## Getting started with agents prerequisites
+
+Before you begin, ensure you have the following prerequisites:
+
+- .NET 8.0 SDK or later
+- Azure OpenAI 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 OpenAI resource. For more information, see the [Azure CLI documentation](https://learn.microsoft.com/cli/azure/authenticate-azure-cli-interactively).
+
+## Samples
+
+|Sample|Description|
+|---|---|
+|[Running a simple agent](./Agents_Step01_Running/)|This sample demonstrates how to create and run a basic agent with instructions|
+|[Multi-turn conversation with a simple agent](./Agents_Step02_MultiturnConversation/)|This sample demonstrates how to implement a multi-turn conversation with a simple agent|
+|[Using function tools with a simple agent](./Agents_Step03_UsingFunctionTools/)|This sample demonstrates how to use function tools with a simple agent|
+|[Using function tools with approvals](./Agents_Step04_UsingFunctionToolsWithApprovals/)|This sample demonstrates how to use function tools where approvals require human in the loop approvals before execution|
+|[Structured output with a simple agent](./Agents_Step05_StructuredOutput/)|This sample demonstrates how to use structured output with a simple agent|
+|[Persisted conversations with a simple agent](./Agents_Step06_PersistedConversations/)|This sample demonstrates how to persist conversations and reload them later. This is useful for cases where an agent is hosted in a stateless service|
+|[3rd party thread storage with a simple agent](./Agents_Step07_3rdPartyThreadStorage/)|This sample demonstrates how to store conversation history in a 3rd party storage solution|
+|[Telemetry with a simple agent](./Agents_Step08_Telemetry/)|This sample demonstrates how to add telemetry to a simple agent|
+|[Dependency injection with a simple agent](./Agents_Step09_DependencyInjection/)|This sample demonstrates how to add and resolve an agent with a dependency injection container|
+
+## Running the samples from the console
+
+To run the samples, navigate to the desired sample directory, e.g.
+
+```powershell
+cd Agents_Step01_Running
+```
+
+Set the following environment variables:
+
+```powershell
+$env:AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com/" # Replace with your Azure OpenAI resource endpoint
+$env:AZURE_OPENAI_DEPLOYMENT_NAME="gpt-4o-mini"  # Optional, defaults to gpt-4o-mini
+```
+
+If the variables are not set, you will be prompted for the values when running the samples.
+
+Execute the following command to build the sample:
+
+```powershell
+dotnet build
+```
+
+Execute the following command to run the sample:
+
+```powershell
+dotnet run --no-build
+```
+
+Or just build and run in one step:
+
+```powershell
+dotnet run
+```
+
+## Running the samples from Visual Studio
+
+Open the solution in Visual Studio and set the desired sample project as the startup project. Then, run the project using the built-in debugger or by pressing `F5`.
+
+You will be prompted for any required environment variables if they are not already set.
@@ -1,41 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using Microsoft.Extensions.Logging;
-using Microsoft.Shared.Samples;
-using OpenAI;
-using OpenAI.Chat;
-
-namespace Custom;
-
-/// <summary>
-/// End-to-end sample showing how to use a custom <see cref="OpenAIChatClientAgent"/>.
-/// </summary>
-public sealed class Custom_OpenAIChatClientAgent(ITestOutputHelper output) : AgentSample(output)
-{
-    /// <summary>
-    /// This will create an instance of <see cref="MyOpenAIChatClientAgent"/> and run it.
-    /// </summary>
-    [Fact]
-    public async Task RunCustomChatClientAgent()
-    {
-        var chatClient = new OpenAIClient(TestConfiguration.OpenAI.ApiKey).GetChatClient(TestConfiguration.OpenAI.ChatModelId);
-
-        var agent = new MyOpenAIChatClientAgent(chatClient);
-
-        var chatMessage = new UserChatMessage("Tell me a joke about a pirate.");
-        var chatCompletion = await agent.RunAsync(chatMessage);
-
-        Console.WriteLine(chatCompletion.Content.Last().Text);
-    }
-}
-
-public class MyOpenAIChatClientAgent : OpenAIChatClientAgent
-{
-    private const string JokerName = "Joker";
-    private const string JokerInstructions = "You are good at telling jokes.";
-
-    public MyOpenAIChatClientAgent(ChatClient client, ILoggerFactory? loggerFactory = null) :
-        base(client, instructions: JokerInstructions, name: JokerName, loggerFactory: loggerFactory)
-    {
-    }
-}
@@ -1,58 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using Microsoft.Extensions.AI.Agents;
-using Microsoft.Shared.Samples;
-using OpenAI;
-
-#pragma warning disable OPENAI001 // Type is for evaluation purposes only and is subject to change or removal in future updates. Suppress this diagnostic to proceed.
-
-namespace Providers;
-
-/// <summary>
-/// End-to-end sample showing how to use <see cref="AIAgent"/> with OpenAI Assistants.
-/// </summary>
-public sealed class AIAgent_With_OpenAIAssistant(ITestOutputHelper output) : AgentSample(output)
-{
-    private const string JokerName = "Joker";
-    private const string JokerInstructions = "You are good at telling jokes.";
-
-    [Fact]
-    public async Task RunWithAssistant()
-    {
-        // Get a client to create server side agents with.
-        var openAIClient = new OpenAIClient(TestConfiguration.OpenAI.ApiKey);
-
-        // Get the agent directly from OpenAIClient.
-        AIAgent agent = openAIClient
-            .GetAssistantClient()
-            .CreateAIAgent(
-                model: TestConfiguration.OpenAI.ChatModelId,
-                name: JokerName,
-                instructions: JokerInstructions
-            );
-
-        // Start a new thread for the agent conversation.
-        AgentThread thread = agent.GetNewThread();
-
-        // Respond to user input
-        await RunAgentAsync("Tell me a joke about a pirate.");
-        await RunAgentAsync("Now add some emojis to the joke.");
-
-        // Local function to invoke agent and display the conversation messages for the thread.
-        async Task RunAgentAsync(string input)
-        {
-            Console.WriteLine(
-                $"""
-                User: {input}
-                Assistant:
-                {await agent.RunAsync(input, thread)}
-
-                """);
-        }
-
-        // Cleanup
-        var assistantClient = openAIClient.GetAssistantClient();
-        await assistantClient.DeleteThreadAsync(thread.ConversationId);
-        await assistantClient.DeleteAssistantAsync(agent.Id);
-    }
-}
@@ -0,0 +1,12 @@
+# Getting started
+
+The getting started samples demonstrate the fundamental concepts and functionalities
+of the agent framework.
+
+## Samples
+
+|Sample|Description|
+|---|---|
+|[Agents](./Agents/README.md)|Getting started with agents|
+|[Agent Providers](./AgentProviders/README.md)|Getting started with creating agents using various providers|
+|[Agent Open Telemetry](./AgentOpenTelemetry/README.md)|Getting started with OpenTelemetry for agents|
@@ -1,125 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Text;
-using Azure.AI.Agents.Persistent;
-using Azure.Identity;
-using Microsoft.Extensions.AI;
-using Microsoft.Extensions.AI.Agents;
-using Microsoft.Shared.Samples;
-using OpenAI.Files;
-
-namespace Steps;
-
-/// <summary>
-/// Demonstrates how to use <see cref="ChatClientAgent"/> with code interpreter tools and file references.
-/// Shows uploading files to different providers and using them with code interpreter capabilities to analyze data and generate responses.
-/// </summary>
-public sealed class Step03_ChatClientAgent_UsingCodeInterpreterTools(ITestOutputHelper output) : AgentSample(output)
-{
-    [Theory]
-    [InlineData(ChatClientProviders.AzureAIAgentsPersistent)]
-    [InlineData(ChatClientProviders.OpenAIAssistant)]
-    public async Task RunningWithFileReferenceAsync(ChatClientProviders provider)
-    {
-        var codeInterpreterTool = new HostedCodeInterpreterTool()
-        {
-            Inputs = [new HostedFileContent(await UploadFileAsync("Resources/groceries.txt", provider))]
-        };
-
-        var agentOptions = new ChatClientAgentOptions(
-            name: "HelpfulAssistant",
-            instructions: "You are a helpful assistant.",
-            tools: [codeInterpreterTool]);
-
-        // Create the server-side agent Id when applicable (depending on the provider).
-        agentOptions.Id = await base.AgentCreateAsync(provider, agentOptions);
-
-        using var chatClient = base.GetChatClient(provider, agentOptions);
-
-        ChatClientAgent agent = new(chatClient, agentOptions);
-
-        var thread = agent.GetNewThread();
-
-        // Prompt which allows to verify that the data was processed from file correctly and current datetime is returned.
-        const string Prompt = "Calculate the total number of items, identify the most frequently purchased item and return the result with today's datetime.";
-
-        var assistantOutput = new StringBuilder();
-        var codeInterpreterOutput = new StringBuilder();
-
-        await foreach (var update in agent.RunStreamingAsync(Prompt, thread))
-        {
-            if (!string.IsNullOrWhiteSpace(update.Text))
-            {
-                assistantOutput.Append(update.Text);
-            }
-
-            if (update.RawRepresentation is ChatResponseUpdate chatUpdate && chatUpdate.RawRepresentation is not null)
-            {
-                codeInterpreterOutput.Append(GetCodeInterpreterOutput(chatUpdate.RawRepresentation, provider));
-            }
-        }
-
-        Console.WriteLine("Assistant Output:");
-        Console.WriteLine(assistantOutput.ToString());
-
-        Console.WriteLine("Code interpreter Output:");
-        Console.WriteLine(codeInterpreterOutput.ToString());
-
-        // Clean up the server-side agent after use when applicable (depending on the provider).
-        await base.AgentCleanUpAsync(provider, agent, thread);
-    }
-
-    #region private
-
-    /// <summary>
-    /// Uploads a file to the specified chat client provider and returns the file ID.
-    /// </summary>
-    /// <param name="filePath">Path to the file to be uploaded.</param>
-    /// <param name="provider">The chat client provider to use for uploading the file.</param>
-    /// <returns>The ID of the uploaded file.</returns>
-    /// <exception cref="NotSupportedException"></exception>
-    private async Task<string> UploadFileAsync(string filePath, ChatClientProviders provider)
-    {
-        switch (provider)
-        {
-            case ChatClientProviders.OpenAIAssistant:
-                var fileClient = new OpenAIFileClient(TestConfiguration.OpenAI.ApiKey);
-                OpenAIFile openAIFileInfo = await fileClient.UploadFileAsync(filePath, FileUploadPurpose.Assistants);
-
-                return openAIFileInfo.Id;
-            case ChatClientProviders.AzureAIAgentsPersistent:
-                var persistentAgentsClient = new PersistentAgentsClient(TestConfiguration.AzureAI.Endpoint, new AzureCliCredential());
-                PersistentAgentFileInfo persistentAgentFileInfo = await persistentAgentsClient.Files.UploadFileAsync(filePath, PersistentAgentFilePurpose.Agents);
-
-                return persistentAgentFileInfo.Id;
-
-            default:
-                throw new NotSupportedException($"Client provider {provider} is not supported.");
-        }
-    }
-
-    /// <summary>
-    /// Depending on the provider, different strategies are used to extract the code interpreter output from the response raw representation.
-    /// </summary>
-    /// <param name="rawRepresentation">Raw representation of the response containing code interpreter output.</param>
-    /// <param name="provider">Provider of the chat client that is used to determine how to extract the output.</param>
-    /// <returns>The code interpreter output as a string.</returns>
-    private static string? GetCodeInterpreterOutput(object rawRepresentation, ChatClientProviders provider)
-        => provider switch
-        {
-            ChatClientProviders.OpenAIAssistant
-                            when rawRepresentation is OpenAI.Assistants.RunStepDetailsUpdate stepDetails => $"{stepDetails.CodeInterpreterInput}{string.Join(
-                                    string.Empty,
-                                    stepDetails.CodeInterpreterOutputs.SelectMany(l => l.Logs)
-                                    )}",
-
-            ChatClientProviders.AzureAIAgentsPersistent
-                            when rawRepresentation is Azure.AI.Agents.Persistent.RunStepDetailsUpdate stepDetails => $"{stepDetails.CodeInterpreterInput}{string.Join(
-                                string.Empty,
-                                stepDetails.CodeInterpreterOutputs.OfType<RunStepDeltaCodeInterpreterLogOutput>().SelectMany(l => l.Logs)
-                                )}",
-            _ => null,
-        };
-
-    #endregion
-}
@@ -1,131 +0,0 @@
-// Copyright (c) Microsoft. All rights reserved.
-
-using System.Text;
-using Azure.AI.Agents.Persistent;
-using Azure.Identity;
-using Microsoft.Extensions.AI;
-using Microsoft.Extensions.AI.Agents;
-using Microsoft.Shared.Samples;
-using OpenAI.Files;
-using OpenAI.VectorStores;
-
-namespace Steps;
-
-/// <summary>
-/// Demonstrates how to use <see cref="ChatClientAgent"/> with file search tools and file references.
-/// Shows uploading files to different providers and using them with file search capabilities to retrieve and analyze information from documents.
-/// </summary>
-public sealed class Step07_ChatClientAgent_UsingFileSearchTools(ITestOutputHelper output) : AgentSample(output)
-{
-    [Theory]
-    [InlineData(ChatClientProviders.AzureAIAgentsPersistent)]
-    [InlineData(ChatClientProviders.OpenAIAssistant)]
-    public async Task RunningWithFileReferenceAsync(ChatClientProviders provider)
-    {
-        // Upload a file to the specified provider.
-        var fileId = await UploadFileAsync("Resources/employees.pdf", provider);
-
-        // Create a vector store for the uploaded file to enable file search capabilities.
-        var vectorStoreId = await CreateVectorStoreAsync([fileId], provider);
-
-        // Create a file search tool that can access the vector store.
-        var fileSearchTool = new HostedFileSearchTool()
-        {
-            Inputs = [new HostedVectorStoreContent(vectorStoreId)],
-        };
-
-        var agentOptions = new ChatClientAgentOptions
-        {
-            Name = "FileSearchAssistant",
-            Instructions = "You are a helpful assistant that can search through uploaded documents to answer questions. Use the file search tool to find relevant information from the uploaded files.",
-            ChatOptions = new() { Tools = [fileSearchTool] }
-        };
-
-        // Create the server-side agent Id when applicable (depending on the provider).
-        agentOptions.Id = await base.AgentCreateAsync(provider, agentOptions);
-
-        using var chatClient = base.GetChatClient(provider, agentOptions);
-
-        ChatClientAgent agent = new(chatClient, agentOptions);
-
-        var thread = agent.GetNewThread();
-
-        // Prompt which allows to verify that the file search functionality works correctly with the uploaded document.
-        const string Prompt = "Who is the youngest employee?";
-
-        var assistantOutput = new StringBuilder();
-
-        await foreach (var update in agent.RunStreamingAsync(Prompt, thread))
-        {
-            if (!string.IsNullOrWhiteSpace(update.Text))
-            {
-                assistantOutput.Append(update.Text);
-            }
-        }
-
-        Console.WriteLine("Assistant Output:");
-        Console.WriteLine(assistantOutput.ToString());
-
-        // Clean up the server-side agent after use when applicable (depending on the provider).
-        await base.AgentCleanUpAsync(provider, agent, thread);
-    }
-
-    #region private
-
-    /// <summary>
-    /// Uploads a file to the specified chat client provider and returns the file ID.
-    /// </summary>
-    /// <param name="filePath">Path to the file to be uploaded.</param>
-    /// <param name="provider">The chat client provider to use for uploading the file.</param>
-    /// <returns>The ID of the uploaded file.</returns>
-    /// <exception cref="NotSupportedException"></exception>
-    private async Task<string> UploadFileAsync(string filePath, ChatClientProviders provider)
-    {
-        switch (provider)
-        {
-            case ChatClientProviders.OpenAIAssistant:
-                var fileClient = new OpenAIFileClient(TestConfiguration.OpenAI.ApiKey);
-                OpenAIFile openAIFileInfo = await fileClient.UploadFileAsync(filePath, FileUploadPurpose.Assistants);
-
-                return openAIFileInfo.Id;
-            case ChatClientProviders.AzureAIAgentsPersistent:
-                var persistentAgentsClient = new PersistentAgentsClient(TestConfiguration.AzureAI.Endpoint, new AzureCliCredential());
-                PersistentAgentFileInfo persistentAgentFileInfo = await persistentAgentsClient.Files.UploadFileAsync(filePath, PersistentAgentFilePurpose.Agents);
-
-                return persistentAgentFileInfo.Id;
-
-            default:
-                throw new NotSupportedException($"Client provider {provider} is not supported.");
-        }
-    }
-
-    private Task<string> CreateVectorStoreAsync(IEnumerable<string> fileIds, ChatClientProviders provider)
-        => provider switch
-        {
-            ChatClientProviders.OpenAIAssistant => CreateVectorStoreOpenAIAssistantAsync(fileIds),
-            ChatClientProviders.AzureAIAgentsPersistent => CreateVectorStoreAzureAIAgentsPersistentAsync(fileIds),
-            _ => throw new NotSupportedException($"Client provider {provider} is not supported."),
-        };
-
-    private async Task<string> CreateVectorStoreOpenAIAssistantAsync(IEnumerable<string> fileIds)
-    {
-        var vectorStoreClient = new VectorStoreClient(TestConfiguration.OpenAI.ApiKey);
-        VectorStoreCreationOptions options = new();
-        foreach (var fileId in fileIds)
-        {
-            options.FileIds.Add(fileId);
-        }
-
-        var vectorStore = await vectorStoreClient.CreateVectorStoreAsync(waitUntilCompleted: true, options);
-        return vectorStore.VectorStoreId;
-    }
-
-    private async Task<string> CreateVectorStoreAzureAIAgentsPersistentAsync(IEnumerable<string> fileIds)
-    {
-        var client = new PersistentAgentsClient(TestConfiguration.AzureAI.Endpoint, new AzureCliCredential());
-        var vectorStore = await client.VectorStores.CreateVectorStoreAsync(fileIds);
-        return vectorStore.Value.Id;
-    }
-
-    #endregion
-}