chore: import upstream snapshot with attribution

2026-07-13 13:21:23 +08:00
commit b957a53def
5423 changed files with 863745 additions and 0 deletions
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+// Copyright (c) Microsoft. All rights reserved.
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.Agents.OpenAI;
+using OpenAI.Responses;
+using Plugins;
+
+namespace GettingStarted.OpenAIResponseAgents;
+
+/// <summary>
+/// This example demonstrates using <see cref="OpenAIResponseAgent"/>.
+/// </summary>
+public class Step03_OpenAIResponseAgent_ReasoningModel(ITestOutputHelper output) : BaseResponsesAgentTest(output, "o4-mini")
+{
+    [Fact]
+    public async Task UseOpenAIResponseAgentWithAReasoningModelAsync()
+    {
+        // Define the agent
+        OpenAIResponseAgent agent = new(this.Client, this.ModelId)
+        {
+            Name = "ResponseAgent",
+            Instructions = "Answer all queries with a detailed response.",
+        };
+
+        // Invoke the agent and output the response
+        var responseItems = agent.InvokeAsync("Which of the last four Olympic host cities has the highest average temperature?");
+        await foreach (ChatMessageContent responseItem in responseItems)
+        {
+            WriteAgentChatMessage(responseItem);
+        }
+    }
+
+    [Fact]
+    public async Task UseOpenAIResponseAgentWithAReasoningModelAndSummariesAsync()
+    {
+        // Define the agent
+        OpenAIResponseAgent agent = new(this.Client, this.ModelId);
+
+        // ResponseCreationOptions allows you to specify tools for the agent.
+        OpenAIResponseAgentInvokeOptions invokeOptions = new()
+        {
+            ResponseCreationOptions = new()
+            {
+                ReasoningOptions = new()
+                {
+                    ReasoningEffortLevel = ResponseReasoningEffortLevel.High,
+                    // This parameter cannot be used due to a known issue in the OpenAI .NET SDK.
+                    // https://github.com/openai/openai-dotnet/issues/457
+                    // ReasoningSummaryVerbosity = ResponseReasoningSummaryVerbosity.Detailed,
+                },
+            },
+        };
+
+        // Invoke the agent and output the response
+        var responseItems = agent.InvokeAsync(
+            """
+            Instructions:
+            - Given the React component below, change it so that nonfiction books have red
+              text. 
+            - Return only the code in your reply
+            - Do not include any additional formatting, such as markdown code blocks
+            - For formatting, use four space tabs, and do not allow any lines of code to 
+              exceed 80 columns
+            const books = [
+              { title: 'Dune', category: 'fiction', id: 1 },
+              { title: 'Frankenstein', category: 'fiction', id: 2 },
+              { title: 'Moneyball', category: 'nonfiction', id: 3 },
+            ];
+            export default function BookList() {
+              const listItems = books.map(book =>
+                <li>
+                  {book.title}
+                </li>
+              );
+              return (
+                <ul>{listItems}</ul>
+              );
+            }
+            """, options: invokeOptions);
+        await foreach (ChatMessageContent responseItem in responseItems)
+        {
+            WriteAgentChatMessage(responseItem);
+        }
+    }
+
+    [Fact]
+    public async Task UseOpenAIResponseAgentWithAReasoningModelAndToolsAsync()
+    {
+        // Define the agent
+        OpenAIResponseAgent agent = new(this.Client, this.ModelId)
+        {
+            Name = "ResponseAgent",
+            Instructions = "Answer all queries with a detailed response.",
+        };
+
+        // Create a plugin that defines the tools to be used by the agent.
+        KernelPlugin plugin = KernelPluginFactory.CreateFromType<MenuPlugin>();
+        agent.Kernel.Plugins.Add(plugin);
+
+        // Invoke the agent and output the response
+        var responseItems = agent.InvokeAsync("What is the best value healthy meal?");
+        await foreach (ChatMessageContent responseItem in responseItems)
+        {
+            WriteAgentChatMessage(responseItem);
+        }
+    }
+}