.NET: Add Magentic Orchestration Sample

dotnet/agent-framework-dotnet.slnx

@@ -1,4 +1,4 @@
-<Solution>
+<Solution>
   <Configurations>
     <BuildType Name="Debug" />
     <BuildType Name="Publish" />
@@ -278,6 +278,7 @@
   </Folder>
   <Folder Name="/Samples/03-workflows/Orchestration/">
     <Project Path="samples/03-workflows/Orchestration/Handoff/Handoff.csproj" />
+    <Project Path="samples/03-workflows/Orchestration/Magentic/Magentic.csproj" />
   </Folder>
   <Folder Name="/Samples/03-workflows/Observability/">
     <Project Path="samples/03-workflows/Observability/ApplicationInsights/ApplicationInsights.csproj" />

dotnet/samples/03-workflows/Orchestration/Magentic/Magentic.csproj

@@ -0,0 +1,23 @@
+<Project Sdk="Microsoft.NET.Sdk">
+
+  <PropertyGroup>
+    <OutputType>Exe</OutputType>
+    <TargetFrameworks>net10.0</TargetFrameworks>
+
+    <Nullable>enable</Nullable>
+    <ImplicitUsings>enable</ImplicitUsings>
+    <NoWarn>$(NoWarn);MAAIW001;OPENAI001</NoWarn>
+  </PropertyGroup>
+
+  <ItemGroup>
+    <PackageReference Include="Azure.AI.Projects" />
+    <PackageReference Include="Azure.Identity" />
+  </ItemGroup>
+
+  <ItemGroup>
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Workflows\Microsoft.Agents.AI.Workflows.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI.Foundry\Microsoft.Agents.AI.Foundry.csproj" />
+    <ProjectReference Include="..\..\..\..\src\Microsoft.Agents.AI\Microsoft.Agents.AI.csproj" />
+  </ItemGroup>
+
+</Project>

dotnet/samples/03-workflows/Orchestration/Magentic/Program.cs

@@ -0,0 +1,195 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+// This sample ports the Python Magentic orchestration sample to .NET.
+// A Magentic workflow coordinates a researcher and a coder, streams orchestration
+// events as the plan evolves, and prints the final conversation transcript.
+
+#pragma warning disable OPENAI001
+
+using Azure.AI.Projects;
+using Azure.Identity;
+using Microsoft.Agents.AI;
+using Microsoft.Agents.AI.Workflows;
+using Microsoft.Agents.AI.Workflows.Specialized.Magentic;
+using Microsoft.Extensions.AI;
+
+namespace WorkflowMagenticOrchestrationSample;
+
+/// <summary>
+/// Demonstrates Magentic orchestration with a researcher, a coder, and an LLM manager.
+/// </summary>
+/// <remarks>
+/// Pre-requisites:
+/// - An Azure AI Foundry project endpoint and model deployment must be configured.
+/// - Run <c>az login</c> before executing the sample.
+/// </remarks>
+public static class Program
+{
+    private const string TaskPrompt =
+        "I am preparing a report on the energy efficiency of different machine learning model architectures. " +
+        "Compare the estimated training and inference energy consumption of ResNet-50, BERT-base, and GPT-2 " +
+        "on standard datasets (e.g., ImageNet for ResNet, GLUE for BERT, WebText for GPT-2). " +
+        "Then, estimate the CO2 emissions associated with each, assuming training on an Azure Standard_NC6s_v3 " +
+        "VM for 24 hours. Provide tables for clarity, and recommend the most energy-efficient model " +
+        "per task type (image classification, text classification, and text generation).";
+
+    private static async Task Main()
+    {
+        string endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
+            ?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
+        string deploymentName = Environment.GetEnvironmentVariable("AZURE_AI_MODEL_DEPLOYMENT_NAME") ?? "gpt-5.4-mini";
+
+        // WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
+        // In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
+        // latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
+        AIProjectClient projectClient = new(new Uri(endpoint), new DefaultAzureCredential());
+
+        AIAgent researcherAgent = projectClient.AsAIAgent(
+            deploymentName,
+            name: "ResearcherAgent",
+            description: "Specialist in research and information gathering.",
+            instructions: "You are a researcher. Find relevant information without doing additional computation or quantitative analysis.");
+
+        AIAgent coderAgent = projectClient.AsAIAgent(
+            deploymentName,
+            name: "CoderAgent",
+            description: "A helpful assistant that writes and executes code to analyze data.",
+            instructions: "You solve quantitative questions by writing and running code. Show the analysis and the computation process clearly.",
+            tools: [new HostedCodeInterpreterTool()]);
+
+        AIAgent managerAgent = projectClient.AsAIAgent(
+            deploymentName,
+            name: "MagenticManager",
+            description: "Orchestrator that coordinates the research and coding workflow.",
+            instructions: "You coordinate the team to complete complex tasks efficiently.");
+
+        Workflow workflow = new MagenticWorkflowBuilder(managerAgent)
+            .AddParticipants([researcherAgent, coderAgent])
+            .WithName("Magentic Orchestration Workflow")
+            .WithDescription("Coordinates a researcher and coder to solve a complex analytical task.")
+            .RequirePlanSignoff(false)
+            .WithMaxRounds(10)
+            .WithMaxStalls(3)
+            .WithMaxResets(2)
+            .Build();
+
+        Console.WriteLine("Building Magentic workflow...");
+        Console.WriteLine();
+        Console.WriteLine($"Task: {TaskPrompt}");
+        Console.WriteLine();
+        Console.WriteLine("Starting workflow execution...");
+
+        await using StreamingRun run = await InProcessExecution.RunStreamingAsync(
+            workflow,
+            new List<ChatMessage> { new(ChatRole.User, TaskPrompt) });
+
+        await run.TrySendMessageAsync(new TurnToken(emitEvents: true));
+
+        string? lastResponseId = null;
+        WorkflowOutputEvent? finalOutput = null;
+
+        await foreach (WorkflowEvent workflowEvent in run.WatchStreamAsync())
+        {
+            switch (workflowEvent)
+            {
+                case AgentResponseUpdateEvent updateEvent:
+                    WriteStreamingUpdate(updateEvent, ref lastResponseId);
+                    break;
+
+                case MagenticPlanCreatedEvent planCreated:
+                    WriteMagenticMessage("Initial Plan", planCreated.FullTaskLedger.Text);
+                    PauseIfInteractive();
+                    break;
+
+                case MagenticReplannedEvent replanned:
+                    WriteMagenticMessage("Replanned", replanned.FullTaskLedger.Text);
+                    PauseIfInteractive();
+                    break;
+
+                case MagenticProgressLedgerUpdatedEvent progressUpdated:
+                    WriteMagenticMessage("Progress Ledger", FormatProgressLedger(progressUpdated.ProgressLedger));
+                    PauseIfInteractive();
+                    break;
+
+                case WorkflowOutputEvent outputEvent when outputEvent.Is<List<ChatMessage>>():
+                    finalOutput = outputEvent;
+                    break;
+
+                case WorkflowErrorEvent workflowError:
+                    Console.ForegroundColor = ConsoleColor.Red;
+                    Console.Error.WriteLine(workflowError.Exception?.ToString() ?? "Unknown workflow error occurred.");
+                    Console.ResetColor();
+                    break;
+
+                case ExecutorFailedEvent executorFailed:
+                    Console.ForegroundColor = ConsoleColor.Red;
+                    Console.Error.WriteLine($"Executor '{executorFailed.ExecutorId}' failed with {(executorFailed.Data is null ? "unknown error" : $"exception {executorFailed.Data}")}.");
+                    Console.ResetColor();
+                    break;
+            }
+        }
+
+        if (finalOutput?.As<List<ChatMessage>>() is { } transcript)
+        {
+            Console.WriteLine();
+            Console.WriteLine(new string('=', 80));
+            Console.WriteLine();
+            Console.WriteLine("Final Conversation Transcript:");
+            Console.WriteLine();
+
+            foreach (ChatMessage message in transcript)
+            {
+                Console.WriteLine($"{message.AuthorName ?? message.Role.ToString()}: {message.Text}");
+                Console.WriteLine();
+            }
+        }
+    }
+
+    private static void WriteStreamingUpdate(AgentResponseUpdateEvent updateEvent, ref string? lastResponseId)
+    {
+        string responseId = updateEvent.Update.ResponseId ?? updateEvent.Update.MessageId ?? updateEvent.ExecutorId;
+        if (!string.Equals(responseId, lastResponseId, StringComparison.Ordinal))
+        {
+            if (lastResponseId is not null)
+            {
+                Console.WriteLine();
+                Console.WriteLine();
+            }
+
+            Console.Write($"- {updateEvent.ExecutorId}: ");
+            lastResponseId = responseId;
+        }
+
+        if (!string.IsNullOrEmpty(updateEvent.Update.Text))
+        {
+            Console.Write(updateEvent.Update.Text);
+        }
+    }
+
+    private static void WriteMagenticMessage(string title, string? content)
+    {
+        Console.WriteLine();
+        Console.WriteLine($"[Magentic {title}]");
+        Console.WriteLine(content);
+    }
+
+    private static string FormatProgressLedger(MagenticProgressLedger ledger) =>
+        string.Join(Environment.NewLine,
+            $"Request satisfied: {ledger.IsRequestSatisfied}",
+            $"In loop: {ledger.IsInLoop}",
+            $"Making progress: {ledger.IsProgressBeingMade}",
+            $"Next speaker: {ledger.NextSpeaker}",
+            $"Instruction: {ledger.InstructionOrQuestion}");
+
+    private static void PauseIfInteractive()
+    {
+        if (Console.IsInputRedirected)
+        {
+            return;
+        }
+
+        Console.Write("Press Enter to continue...");
+        Console.ReadLine();
+        Console.WriteLine();
+    }
+}

dotnet/samples/03-workflows/Orchestration/Magentic/README.md

@@ -0,0 +1,40 @@
+# Magentic Orchestration Sample
+
+This sample ports the Python `magentic.py` workflow sample to .NET. It builds a `MagenticWorkflowBuilder` orchestration that coordinates three roles:
+
+- **ResearcherAgent** gathers factual background information.
+- **CoderAgent** uses `HostedCodeInterpreterTool` for quantitative analysis.
+- **MagenticManager** plans the work, tracks progress, and decides who should act next.
+
+## What This Sample Demonstrates
+
+- Building a Magentic workflow with `MagenticWorkflowBuilder`
+- Combining standard responses-based agents with a code interpreter-enabled participant
+- Streaming orchestration events such as the initial plan, replans, and progress-ledger updates
+- Printing the final multi-agent conversation transcript
+
+## Prerequisites
+
+- `AZURE_AI_PROJECT_ENDPOINT` set to your Azure AI Foundry project endpoint
+- `AZURE_AI_MODEL_DEPLOYMENT_NAME` set to your model deployment name (defaults to `gpt-5.4-mini`)
+- `az login` completed before running the sample
+
+## Running the Sample
+
+```bash
+dotnet run
+```
+
+## Expected Output
+
+The sample prints:
+
+1. The original task prompt
+2. Streamed updates from the participating agents
+3. Magentic plan and progress-ledger events as the workflow coordinates the team
+4. The final conversation transcript returned by the workflow
+
+## Related Samples
+
+- [Handoff Orchestration](../Handoff) - another multi-agent orchestration pattern in .NET workflows
+- [Python Magentic workflow sample](../../../../../python/samples/03-workflows/orchestrations/magentic.py) - the source scenario that this sample ports

dotnet/samples/03-workflows/README.md

@@ -62,3 +62,4 @@ Once completed, please proceed to the other samples listed below.
 | Sample | Concepts |
 |--------|----------|
 | [Handoff Orchestration](./Orchestration/Handoff) | Introduces the Handoff Orchestration pattern |
+| [Magentic Orchestration](./Orchestration/Magentic) | Coordinates multiple agents with a Magentic manager, streamed plan events, and a final transcript |