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.NET: Organize the .Net samples (#578)
* Organize the .Net samples * Organize the .Net samples * Merge latest from main * Update sample to also include function calling telemetry (#577) * Move package installation instructions to user-guide (#572) * Move package installation instructions to user-guide * Update user-documentation-dotnet/getting-started/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Update docs/docs-templates/getting-started/README.md Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * .NET: Add SK-AF Migration Samples for Responses API. (#575) * Responses wip * Adding OpenAI Responses Migration samples * Address all samples and code for Azure and OpenAI Responses Migration code * Update dotnet/samples/SemanticKernelMigration/OpenAIResponses/Step02_ReasoningModel/Program.cs Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> --------- Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com> * Organize the .Net samples * Organize the .Net samples * Merge latest from main * Use Agent rather than AIAgent * Rename agents getting started samples * Use singular Agent --------- Co-authored-by: Roger Barreto <19890735+rogerbarreto@users.noreply.github.com> Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
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// Copyright (c) Microsoft. All rights reserved.
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// This sample demonstrates how to use a ChatClientAgent with function tools that require a human in the loop for approvals.
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// It shows both non-streaming and streaming agent interactions using menu-related tools.
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// If the agent is hosted in a service, with a remote user, combine this sample with the Persisted Conversations sample to persist the chat history
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// while the agent is waiting for user input.
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using System;
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using System.ComponentModel;
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using System.Linq;
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using Azure.AI.OpenAI;
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using Azure.Identity;
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using Microsoft.Extensions.AI;
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using Microsoft.Extensions.AI.Agents;
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using OpenAI;
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var endpoint = Environment.GetEnvironmentVariable("AZURE_OPENAI_ENDPOINT") ?? throw new InvalidOperationException("AZURE_OPENAI_ENDPOINT is not set.");
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var deploymentName = Environment.GetEnvironmentVariable("AZURE_OPENAI_DEPLOYMENT_NAME") ?? "gpt-4o-mini";
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// Create a sample function tool that the agent can use.
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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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// Create the chat client and agent.
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// Note that we are wrapping the function tool with ApprovalRequiredAIFunction to require user approval before invoking it.
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AIAgent agent = new AzureOpenAIClient(
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new Uri(endpoint),
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new AzureCliCredential())
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.GetChatClient(deploymentName)
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.CreateAIAgent(instructions: "You are a helpful assistant", tools: [new ApprovalRequiredAIFunction(AIFunctionFactory.Create(GetWeather))]);
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// Call the agent and check if there are any user input requests to handle.
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AgentThread thread = agent.GetNewThread();
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var response = await agent.RunAsync("What is the weather like in Amsterdam?", thread);
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var userInputRequests = response.UserInputRequests.ToList();
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// For streaming use:
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// var updates = await agent.RunStreamingAsync("What is the weather like in Amsterdam?", thread).ToListAsync();
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// userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
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while (userInputRequests.Count > 0)
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{
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// Ask the user to approve each function call request.
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// For simplicity, we are assuming here that only function approval requests are being made.
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var userInputResponses = userInputRequests
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.OfType<FunctionApprovalRequestContent>()
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.Select(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 {functionApprovalRequest.FunctionCall.Name}");
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return new ChatMessage(ChatRole.User, [functionApprovalRequest.CreateResponse(Console.ReadLine()?.Equals("Y", StringComparison.OrdinalIgnoreCase) ?? false)]);
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})
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.ToList();
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// Pass the user input responses back to the agent for further processing.
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response = await agent.RunAsync(userInputResponses, thread);
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userInputRequests = response.UserInputRequests.ToList();
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// For streaming use:
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// updates = await agent.RunStreamingAsync(userInputResponses, thread).ToListAsync();
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// userInputRequests = updates.SelectMany(x => x.UserInputRequests).ToList();
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}
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Console.WriteLine($"\nAgent: {response}");
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// For streaming use:
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// Console.WriteLine($"\nAgent: {updates.ToAgentRunResponse()}");
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