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https://github.com/microsoft/agent-framework.git
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Roger Barreto
0009e330af
Add #pragma warning disable directives to suppress experimental API diagnostics that cause build errors in Docker isolation (where repo-level Directory.Build.props is not inherited): - AgentWithHostedMCP: suppress MEAI001 (HostedMcpServerTool) and OPENAI001 (GetResponsesClient) - FoundrySingleAgent: suppress CA2252 (AIProjectClient preview features) - FoundryMultiAgent: suppress CA2252 (AIProjectClient preview features) Fixes #4365
52 lines
2.3 KiB
C#
52 lines
2.3 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates a multi-agent workflow with Writer and Reviewer agents
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// using Azure AI Foundry AIProjectClient and the Agent Framework WorkflowBuilder.
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#pragma warning disable CA2252 // AIProjectClient and Agents API require opting into preview features
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using Azure.AI.AgentServer.AgentFramework.Extensions;
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using Azure.AI.Projects;
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using Azure.Identity;
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using Microsoft.Agents.AI;
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using Microsoft.Agents.AI.Workflows;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_AI_PROJECT_ENDPOINT")
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?? throw new InvalidOperationException("AZURE_AI_PROJECT_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("MODEL_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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Console.WriteLine($"Using Azure AI endpoint: {endpoint}");
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Console.WriteLine($"Using model deployment: {deploymentName}");
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// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
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// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
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// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
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AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
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// Create Foundry agents
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AIAgent writerAgent = await aiProjectClient.CreateAIAgentAsync(
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name: "Writer",
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model: deploymentName,
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instructions: "You are an excellent content writer. You create new content and edit contents based on the feedback.");
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AIAgent reviewerAgent = await aiProjectClient.CreateAIAgentAsync(
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name: "Reviewer",
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model: deploymentName,
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instructions: "You are an excellent content reviewer. Provide actionable feedback to the writer about the provided content. Provide the feedback in the most concise manner possible.");
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try
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{
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var workflow = new WorkflowBuilder(writerAgent)
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.AddEdge(writerAgent, reviewerAgent)
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.Build();
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Console.WriteLine("Starting Writer-Reviewer Workflow Agent Server on http://localhost:8088");
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await workflow.AsAgent().RunAIAgentAsync();
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}
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finally
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{
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// Cleanup server-side agents
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await aiProjectClient.Agents.DeleteAgentAsync(writerAgent.Name);
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await aiProjectClient.Agents.DeleteAgentAsync(reviewerAgent.Name);
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}
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