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Ben Thomas c79f886dc3 .NET: Align Foundry sample environment variables and credentials. (#6422)
* 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>

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Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
2026-06-11 17:26:00 +00:00

53 lines
2.7 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
// This sample demonstrates how to use an agent with function tools that require a human in the loop for approvals.
using System.ComponentModel;
using Azure.AI.Projects;
using Azure.Identity;
using Microsoft.Agents.AI;
using Microsoft.Extensions.AI;
[Description("Get the weather for a given location.")]
static string GetWeather([Description("The location to get the weather for.")] string location)
=> $"The weather in {location} is cloudy with a high of 15°C.";
string endpoint = Environment.GetEnvironmentVariable("FOUNDRY_PROJECT_ENDPOINT") ?? throw new InvalidOperationException("FOUNDRY_PROJECT_ENDPOINT is not set.");
string deploymentName = Environment.GetEnvironmentVariable("FOUNDRY_MODEL") ?? "gpt-5.4-mini";
// WARNING: DefaultAzureCredential is convenient for development but requires careful consideration in production.
// In production, consider using a specific credential (e.g., ManagedIdentityCredential) to avoid
// latency issues, unintended credential probing, and potential security risks from fallback mechanisms.
AIProjectClient aiProjectClient = new(new Uri(endpoint), new DefaultAzureCredential());
ApprovalRequiredAIFunction approvalTool = new(AIFunctionFactory.Create(GetWeather, name: nameof(GetWeather)));
AIAgent agent = aiProjectClient.AsAIAgent(deploymentName,
instructions: "You are a helpful assistant that can get weather information.",
name: "WeatherAssistant",
tools: [approvalTool]);
// Call the agent with approval-required function tools.
AgentSession session = await agent.CreateSessionAsync();
AgentResponse response = await agent.RunAsync("What is the weather like in Amsterdam?", session);
// Check if there are any approval requests.
List<ToolApprovalRequestContent> approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
while (approvalRequests.Count > 0)
{
// Ask the user to approve each function call request.
List<ChatMessage> userInputMessages = approvalRequests
.ConvertAll(functionApprovalRequest =>
{
Console.WriteLine($"The agent would like to invoke the following function, please reply Y to approve: Name {((FunctionCallContent)functionApprovalRequest.ToolCall).Name}");
bool approved = Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false;
return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(approved)]);
});
response = await agent.RunAsync(userInputMessages, session);
approvalRequests = response.Messages.SelectMany(m => m.Contents).OfType<ToolApprovalRequestContent>().ToList();
}
Console.WriteLine($"\nAgent: {response}");