wehub-resource-sync
87 lines
3.6 KiB
C#
87 lines
3.6 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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using System.Text;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.ChatCompletion;
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using Microsoft.SemanticKernel.Connectors.OpenAI;
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using OpenAI.Chat;
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namespace ChatCompletion;
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// The following example shows how to use Semantic Kernel with OpenAI API
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public class OpenAI_ChatCompletionWithReasoning(ITestOutputHelper output) : BaseTest(output)
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{
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/// <summary>
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/// Sample showing how to use <see cref="Kernel"/> with chat completion and chat prompt syntax.
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/// </summary>
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[Fact]
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public async Task ChatPromptWithReasoningAsync()
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{
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Console.WriteLine("======== Open AI - Chat Completion with Reasoning ========");
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Assert.NotNull(TestConfiguration.OpenAI.ChatModelId);
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Assert.NotNull(TestConfiguration.OpenAI.ApiKey);
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var kernel = Kernel.CreateBuilder()
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.AddOpenAIChatCompletion(
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modelId: TestConfiguration.OpenAI.ChatModelId,
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apiKey: TestConfiguration.OpenAI.ApiKey)
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.Build();
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// Create execution settings with low reasoning effort.
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var executionSettings = new OpenAIPromptExecutionSettings //OpenAIPromptExecutionSettings
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{
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MaxTokens = 2000,
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ReasoningEffort = ChatReasoningEffortLevel.Low // Only available for reasoning models (i.e: o3-mini, o1, ...)
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};
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// Create KernelArguments using the execution settings.
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var kernelArgs = new KernelArguments(executionSettings);
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StringBuilder chatPrompt = new("""
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<message role="developer">You are an expert software engineer, specialized in the Semantic Kernel SDK and NET framework</message>
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<message role="user">Hi, Please craft me an example code in .NET using Semantic Kernel that implements a chat loop .</message>
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""");
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// Invoke the prompt with high reasoning effort.
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var reply = await kernel.InvokePromptAsync(chatPrompt.ToString(), kernelArgs);
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Console.WriteLine(reply);
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}
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/// <summary>
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/// Sample showing how to use <see cref="IChatCompletionService"/> directly with a <see cref="ChatHistory"/>.
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/// </summary>
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[Fact]
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public async Task ServicePromptWithReasoningAsync()
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{
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Assert.NotNull(TestConfiguration.OpenAI.ChatModelId);
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Assert.NotNull(TestConfiguration.OpenAI.ApiKey);
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Console.WriteLine("======== Open AI - Chat Completion with Reasoning ========");
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OpenAIChatCompletionService chatCompletionService = new(TestConfiguration.OpenAI.ChatModelId, TestConfiguration.OpenAI.ApiKey);
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// Create execution settings with low reasoning effort.
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var executionSettings = new OpenAIPromptExecutionSettings
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{
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MaxTokens = 2000,
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ReasoningEffort = ChatReasoningEffortLevel.Low // Only available for reasoning models (i.e: o3-mini, o1, ...)
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};
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// Create a ChatHistory and add messages.
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var chatHistory = new ChatHistory();
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chatHistory.AddDeveloperMessage(
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"You are an expert software engineer, specialized in the Semantic Kernel SDK and .NET framework.");
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chatHistory.AddUserMessage(
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"Hi, Please craft me an example code in .NET using Semantic Kernel that implements a chat loop.");
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// Instead of a prompt string, call GetChatMessageContentAsync with the chat history.
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var reply = await chatCompletionService.GetChatMessageContentAsync(
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chatHistory: chatHistory,
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executionSettings: executionSettings);
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Console.WriteLine(reply);
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}
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}
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