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.Net Agents - Magentic Agent Orchestration (#12110)
### Motivation and Context <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> Introducing _Magentic_ agent orchestration. Fixes: #10900 Fixes: #12156 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Add _Magentic_ ledger based orchestration, based on AutoGen _Magentic One_ ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [X] The code builds clean without any errors or warnings - [X] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [X] All unit tests pass, and I have added new tests where possible - [X] I didn't break anyone 😄 --------- Co-authored-by: Tao Chen <taochen@microsoft.com>
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‎dotnet/SK-dotnet.sln‎

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@@ -552,6 +552,8 @@ Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "VectorData.UnitTests", "src
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EndProject
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Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Agents.Orchestration", "src\Agents\Orchestration\Agents.Orchestration.csproj", "{D1A02387-FA60-22F8-C2ED-4676568B6CC3}"
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EndProject
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Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "Agents.Magentic", "src\Agents\Magentic\Agents.Magentic.csproj", "{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}"
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
@@ -1519,6 +1521,12 @@ Global
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{D1A02387-FA60-22F8-C2ED-4676568B6CC3}.Publish|Any CPU.Build.0 = Publish|Any CPU
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{D1A02387-FA60-22F8-C2ED-4676568B6CC3}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{D1A02387-FA60-22F8-C2ED-4676568B6CC3}.Release|Any CPU.Build.0 = Release|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Publish|Any CPU.ActiveCfg = Publish|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Publish|Any CPU.Build.0 = Publish|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7}.Release|Any CPU.Build.0 = Release|Any CPU
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EndGlobalSection
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GlobalSection(SolutionProperties) = preSolution
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HideSolutionNode = FALSE
@@ -1725,6 +1733,7 @@ Global
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{DA6B4ED4-ED0B-D25C-889C-9F940E714891} = {A70ED5A7-F8E1-4A57-9455-3C05989542DA}
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{AAC7B5E8-CC4E-49D0-AF6A-2B4F7B43BD84} = {5A7028A7-4DDF-4E4F-84A9-37CE8F8D7E89}
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{D1A02387-FA60-22F8-C2ED-4676568B6CC3} = {6823CD5E-2ABE-41EB-B865-F86EC13F0CF9}
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{38059FCB-2CD7-C0DE-AE71-DA4D0245ECC7} = {6823CD5E-2ABE-41EB-B865-F86EC13F0CF9}
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EndGlobalSection
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GlobalSection(ExtensibilityGlobals) = postSolution
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SolutionGuid = {FBDC56A3-86AD-4323-AA0F-201E59123B83}

‎dotnet/samples/GettingStartedWithAgents/GettingStartedWithAgents.csproj‎

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<ProjectReference Include="..\..\src\Agents\OpenAI\Agents.OpenAI.csproj" />
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<ProjectReference Include="..\..\src\Agents\Bedrock\Agents.Bedrock.csproj" />
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<ProjectReference Include="..\..\src\Agents\Orchestration\Agents.Orchestration.csproj" />
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<ProjectReference Include="..\..\src\Agents\Magentic\Agents.Magentic.csproj" />
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<ProjectReference Include="..\..\src\Agents\Runtime\InProcess\Runtime.InProcess.csproj" />
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<ProjectReference Include="..\..\src\Agents\Yaml\Agents.Yaml.csproj" />
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<ProjectReference Include="..\..\src\Connectors\Connectors.AzureOpenAI\Connectors.AzureOpenAI.csproj" />

‎dotnet/samples/GettingStartedWithAgents/Orchestration/Step01_Concurrent.cs‎

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@@ -27,13 +27,17 @@ public async Task ConcurrentTaskAsync()
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instructions: "You are an expert in chemistry. You answer questions from a chemistry perspective.",
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description: "An expert in chemistry");
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// Define the orchestration
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// Create a monitor to capturing agent responses (via ResponseCallback)
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// to display at the end of this sample. (optional)
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// NOTE: Create your own callback to capture responses in your application or service.
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OrchestrationMonitor monitor = new();
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// Define the orchestration
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ConcurrentOrchestration orchestration =
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new(physicist, chemist)
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{
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ResponseCallback = monitor.ResponseCallback,
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LoggerFactory = this.LoggerFactory
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LoggerFactory = this.LoggerFactory,
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};
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// Start the runtime

‎dotnet/samples/GettingStartedWithAgents/Orchestration/Step02_Sequential.cs‎

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""",
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description: "An agent that formats and proofreads the marketing copy.");
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// Define the orchestration
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// Create a monitor to capturing agent responses (via ResponseCallback)
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// to display at the end of this sample. (optional)
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// NOTE: Create your own callback to capture responses in your application or service.
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OrchestrationMonitor monitor = new();
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// Define the orchestration
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SequentialOrchestration orchestration =
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new(analystAgent, writerAgent, editorAgent)
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{

‎dotnet/samples/GettingStartedWithAgents/Orchestration/Step03_GroupChat.cs‎

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If not, provide insight on how to refine suggested copy without example.
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""");
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// Define the orchestration
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// Create a monitor to capturing agent responses (via ResponseCallback)
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// to display at the end of this sample. (optional)
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// NOTE: Create your own callback to capture responses in your application or service.
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OrchestrationMonitor monitor = new();
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// Define the orchestration
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GroupChatOrchestration orchestration =
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new(new RoundRobinGroupChatManager()
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{

‎dotnet/samples/GettingStartedWithAgents/Orchestration/Step04_Handoff.cs‎

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description: "A customer support agent that handles order refund.");
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refundAgent.Kernel.Plugins.Add(KernelPluginFactory.CreateFromObject(new OrderRefundPlugin()));
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// Define the orchestration
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// Create a monitor to capturing agent responses (via ResponseCallback)
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// to display at the end of this sample. (optional)
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// NOTE: Create your own callback to capture responses in your application or service.
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OrchestrationMonitor monitor = new();
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// Define user responses for InteractiveCallback (since sample is not interactive)
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Queue<string> responses = new();
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string task = "I am a customer that needs help with my orders";
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responses.Enqueue("I'd like to track the status of my order");
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responses.Enqueue("My order ID is 123");
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responses.Enqueue("I want to return another order of mine");
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responses.Enqueue("Order ID 321");
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responses.Enqueue("Broken item");
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responses.Enqueue("No, bye");
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// Define the orchestration
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HandoffOrchestration orchestration =
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new(OrchestrationHandoffs
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.StartWith(triageAgent)
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await runtime.StartAsync();
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// Run the orchestration
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string task = "I am a customer that needs help with my orders";
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responses.Enqueue("I'd like to track the status of my order");
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responses.Enqueue("My order ID is 123");
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responses.Enqueue("I want to return another order of mine");
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responses.Enqueue("Order ID 321");
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responses.Enqueue("Broken item");
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responses.Enqueue("No, bye");
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Console.WriteLine($"\n# INPUT:\n{task}\n");
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OrchestrationResult<string> result = await orchestration.InvokeAsync(task, runtime);
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‎dotnet/samples/GettingStartedWithAgents/Orchestration/Step05_Magentic.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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using Azure.Identity;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Agents;
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using Microsoft.SemanticKernel.Agents.AzureAI;
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using Microsoft.SemanticKernel.Agents.Magentic;
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using Microsoft.SemanticKernel.Agents.Orchestration;
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using Microsoft.SemanticKernel.Agents.Runtime.InProcess;
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using Microsoft.SemanticKernel.ChatCompletion;
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using Microsoft.SemanticKernel.Connectors.OpenAI;
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using AAIP = Azure.AI.Projects;
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namespace GettingStarted.Orchestration;
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/// <summary>
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/// Demonstrates how to use the <see cref="MagenticOrchestration"/> with two agents:
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/// - A Research agent that can perform web searches
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/// - A Coder agent that can run code using the code interpreter
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/// </summary>
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public class Step05_Magentic(ITestOutputHelper output) : BaseOrchestrationTest(output)
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{
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private const string ManagerModel = "o3-mini";
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private const string ResearcherModel = "gpt-4o-search-preview";
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/// <summary>
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/// Require OpenAI services in order to use "gpt-4o-search-preview" model
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/// </summary>
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protected override bool ForceOpenAI => true;
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[Fact]
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public async Task MagenticTaskAsync()
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{
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// Define the agents
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Kernel researchKernel = CreateKernelWithOpenAIChatCompletion(ResearcherModel);
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ChatCompletionAgent researchAgent =
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this.CreateAgent(
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name: "ResearchAgent",
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description: "A helpful assistant with access to web search. Ask it to perform web searches.",
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instructions: "You are a Researcher. You find information without additional computation or quantitative analysis.",
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kernel: researchKernel);
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AAIP.AIProjectClient projectClient = AzureAIAgent.CreateAzureAIClient(TestConfiguration.AzureAI.ConnectionString, new AzureCliCredential());
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AAIP.AgentsClient agentsClient = projectClient.GetAgentsClient();
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AAIP.Agent definition =
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await agentsClient.CreateAgentAsync(
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TestConfiguration.AzureAI.ChatModelId,
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name: "CoderAgent",
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description: "Write and executes code to process and analyze data.",
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instructions: "You solve questions using code. Please provide detailed analysis and computation process.",
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tools: [new Azure.AI.Projects.CodeInterpreterToolDefinition()]);
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AzureAIAgent coderAgent = new(definition, agentsClient);
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// Create a monitor to capturing agent responses (via ResponseCallback)
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// to display at the end of this sample. (optional)
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// NOTE: Create your own callback to capture responses in your application or service.
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OrchestrationMonitor monitor = new();
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// Define the orchestration
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Kernel managerKernel = this.CreateKernelWithChatCompletion(ManagerModel);
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StandardMagenticManager manager =
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new(managerKernel.GetRequiredService<IChatCompletionService>(), new OpenAIPromptExecutionSettings())
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{
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MaximumInvocationCount = 5,
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};
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MagenticOrchestration orchestration =
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new(manager, researchAgent, coderAgent)
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{
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ResponseCallback = monitor.ResponseCallback,
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LoggerFactory = this.LoggerFactory,
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};
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// Start the runtime
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InProcessRuntime runtime = new();
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await runtime.StartAsync();
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string input =
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"""
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I am preparing a report on the energy efficiency of different machine learning model architectures.
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Compare the estimated training and inference energy consumption of ResNet-50, BERT-base, and GPT-2 on standard datasets
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(e.g., ImageNet for ResNet, GLUE for BERT, WebText for GPT-2).
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Then, estimate the CO2 emissions associated with each, assuming training on an Azure Standard_NC6s_v3 VM for 24 hours.
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Provide tables for clarity, and recommend the most energy-efficient model per task type
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(image classification, text classification, and text generation).
84+
""";
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Console.WriteLine($"\n# INPUT:\n{input}\n");
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OrchestrationResult<string> result = await orchestration.InvokeAsync(input, runtime);
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string text = await result.GetValueAsync(TimeSpan.FromSeconds(ResultTimeoutInSeconds * 10));
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Console.WriteLine($"\n# RESULT: {text}");
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await runtime.RunUntilIdleAsync();
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Console.WriteLine("\n\nORCHESTRATION HISTORY");
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foreach (ChatMessageContent message in monitor.History)
94+
{
95+
this.WriteAgentChatMessage(message);
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}
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}
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private Kernel CreateKernelWithOpenAIChatCompletion(string model)
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{
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IKernelBuilder builder = Kernel.CreateBuilder();
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103+
builder.AddOpenAIChatCompletion(
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model,
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TestConfiguration.OpenAI.ApiKey);
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return builder.Build();
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}
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}

‎dotnet/src/Agents/AzureAI/Extensions/AgentToolDefinitionExtensions.cs‎

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var toolConnections = agentToolDefinition.GetRequiredOption<List<object>>("tool_connections");
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return toolConnections.Select(connectionId => new ToolConnection(connectionId.ToString())).ToList();
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return [.. toolConnections.Select(connectionId => new ToolConnection(connectionId.ToString()))];
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}
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private static T GetRequiredOption<T>(this AgentToolDefinition agentToolDefinition, string key)

‎dotnet/src/Agents/Magentic/Agents.Magentic.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<!-- THIS PROPERTY GROUP MUST COME FIRST -->
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<AssemblyName>Microsoft.SemanticKernel.Agents.Magentic</AssemblyName>
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<RootNamespace>Microsoft.SemanticKernel.Agents.Magentic</RootNamespace>
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<TargetFrameworks>net8.0;netstandard2.0</TargetFrameworks>
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<NoWarn>$(NoWarn);IDE1006;SKEXP0110;SKEXP0001</NoWarn>
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<EnablePackageValidation>false</EnablePackageValidation>
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<VersionSuffix>preview</VersionSuffix>
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</PropertyGroup>
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<Import Project="$(RepoRoot)/dotnet/nuget/nuget-package.props" />
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<PropertyGroup>
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<!-- NuGet Package Settings -->
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<Title>Semantic Kernel Agents - Magentic Agents</Title>
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<Description>Defines Magentic agents and orchestration.</Description>
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</PropertyGroup>
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<ItemGroup>
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<Compile Include="$(RepoRoot)/dotnet/src/InternalUtilities/src/Diagnostics/*" Link="%(RecursiveDir)Utilities/%(Filename)%(Extension)" />
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<Compile Include="$(RepoRoot)/dotnet/src/InternalUtilities/src/System/*" Link="%(RecursiveDir)Utilities/%(Filename)%(Extension)" />
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<Compile Include="$(RepoRoot)/dotnet/src/InternalUtilities/agents/Extensions/AgentExtensions.cs" Link="%(RecursiveDir)Utilities/%(Filename)%(Extension)" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\Orchestration\Agents.Orchestration.csproj" />
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</ItemGroup>
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<ItemGroup>
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<InternalsVisibleTo Include="SemanticKernel.Agents.UnitTests" />
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<InternalsVisibleTo Include="DynamicProxyGenAssembly2" />
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</ItemGroup>
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</Project>

‎dotnet/src/Agents/Magentic/Internal/PromptExecutionSettingsExtensions.cs‎

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// Copyright (c) Microsoft. All rights reserved.
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using System;
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using System.Reflection;
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namespace Microsoft.SemanticKernel.Agents.Magentic.Internal;
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/// <summary>
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/// Extension methods for <see cref="PromptExecutionSettings"/> to support response format operations.
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/// </summary>
11+
public static class PromptExecutionSettingsExtensions
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{
13+
private const string ResponseFormatPropertyName = "ResponseFormat";
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/// <summary>
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/// Determines whether the <paramref name="settings"/> object supports a "ResponseFormat" property of type <see cref="object"/>.
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/// </summary>
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/// <param name="settings">The <see cref="PromptExecutionSettings"/> instance to check.</param>
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/// <returns><c>true</c> if the "ResponseFormat" property exists and is of type <see cref="object"/>; otherwise, <c>false</c>.</returns>
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public static bool SupportsResponseFormat(this PromptExecutionSettings settings)
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{
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Type settingsType = settings.GetType();
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PropertyInfo? property = settingsType.GetProperty(ResponseFormatPropertyName);
24+
return property != null && property.PropertyType == typeof(object);
25+
}
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/// <summary>
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/// Sets the "ResponseFormat" property of the <paramref name="settings"/> object to the specified response type.
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/// </summary>
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/// <typeparam name="TResponse">The type to set as the response format.</typeparam>
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/// <param name="settings">The <see cref="PromptExecutionSettings"/> instance to update.</param>
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public static void SetResponseFormat<TResponse>(this PromptExecutionSettings settings)
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{
34+
Type settingsType = settings.GetType();
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PropertyInfo? property = settingsType.GetProperty(ResponseFormatPropertyName);
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property?.SetValue(settings, typeof(TResponse));
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}
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}

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