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* dotnet: refresh Foundry sample guidance Carry forward the still-relevant sample guidance and Foundry-specific documentation fixes from the old stacked sample migration work, adapted to the current repo layout and policy. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * dotnet: rename Foundry sample env vars Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * dotnet: remove persistent provider sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * dotnet: drop SAMPLE_GUIDELINES.md from this PR Defer the guidelines doc and its cross-link to a follow-on PR to avoid broken-link failures in CI. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * dotnet: add DefaultAzureCredential warning to remaining samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * dotnet: address PR review feedback Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
53 lines
2.7 KiB
C#
53 lines
2.7 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates how to use an agent with function tools that require a human in the loop for approvals.
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using System.ComponentModel;
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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.Extensions.AI;
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[Description("Get the weather for a given location.")]
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static string GetWeather([Description("The location to get the weather for.")] string location)
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=> $"The weather in {location} is cloudy with a high of 15°C.";
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string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
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string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
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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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ApprovalRequiredAIFunction approvalTool = new(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)));
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AIAgent agent = aiProjectClient.AsAIAgent(deploymentName,
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instructions: "You are a helpful assistant that can get weather information.",
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name: "WeatherAssistant",
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tools: [approvalTool]);
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// Call the agent with approval-required function tools.
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AgentSession session = await agent.CreateSessionAsync();
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AgentResponse response = await agent.RunAsync("What is the weather like in Amsterdam?", session);
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// Check if there are any approval requests.
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List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
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while (approvalRequests.Count > 0)
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{
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// Ask the user to approve each function call request.
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List<ChatMessage> userInputMessages = approvalRequests
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.ConvertAll(functionApprovalRequest =>
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{
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Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
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bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
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return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
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});
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response = await agent.RunAsync(userInputMessages, session);
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approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
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}
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Console.WriteLine($"\nAgent: {response}");
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