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.Net: Sample Code Showcasing Usage of Reasoning Models in OpenAI and …
…AzureOpenAI (#10558) ### Motivation and Context 1. Required: showing usage of reasoning effort. 2. Problem: Controlling reasoning effort - no sample 3. Scenario: Using reasoning effort to benefit from the new amazing models :) ### Description This pull request adds sample code that demonstrates how to leverage reasoning models in a ChatCompletion on AzureOpenAI and OpenAI. This implementation how to leverage LLM Reasoning capabilities but also complements the phenomenal code from Roger Barreto (@RogerBarreto), further strengthening Semantic Kernel overall solution. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [ ] The code builds clean without any errors or warnings - [ ] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [ ] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄 --------- Co-authored-by: Roger Barreto <19890735+RogerBarreto@users.noreply.github.com>
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dotnet/samples/Concepts/ChatCompletion/AzureOpenAI_ChatCompletion_WithReasoning.cs
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| // Copyright (c) Microsoft. All rights reserved. | ||
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| using System.Text; | ||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.ChatCompletion; | ||
| using Microsoft.SemanticKernel.Connectors.AzureOpenAI; | ||
| using OpenAI.Chat; | ||
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| namespace ChatCompletion; | ||
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| // The following example shows how to use Semantic Kernel with Azure OpenAI API | ||
| public class AzureOpenAI_ChatCompletion_WithReasoning(ITestOutputHelper output) : BaseTest(output) | ||
| { | ||
| /// <summary> | ||
| /// Sample showing how to use <see cref="Kernel"/> with chat completion and chat prompt syntax. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task ChatPromptWithReasoningAsync() | ||
| { | ||
| Console.WriteLine("======== Azure Open AI - Chat Completion with Reasoning ========"); | ||
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| Assert.NotNull(TestConfiguration.AzureOpenAI.ChatDeploymentName); | ||
| Assert.NotNull(TestConfiguration.AzureOpenAI.Endpoint); | ||
| Assert.NotNull(TestConfiguration.AzureOpenAI.ApiKey); | ||
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| var kernel = Kernel.CreateBuilder() | ||
| .AddAzureOpenAIChatCompletion( | ||
| deploymentName: TestConfiguration.AzureOpenAI.ChatDeploymentName, | ||
| endpoint: TestConfiguration.AzureOpenAI.Endpoint, | ||
| apiKey: TestConfiguration.AzureOpenAI.ApiKey, | ||
| modelId: TestConfiguration.AzureOpenAI.ChatModelId) | ||
| .Build(); | ||
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| // Create execution settings with high reasoning effort. | ||
| var executionSettings = new AzureOpenAIPromptExecutionSettings //OpenAIPromptExecutionSettings | ||
| { | ||
| // Flags Azure SDK to use the new token property. | ||
| SetNewMaxCompletionTokensEnabled = true, | ||
| MaxTokens = 2000, | ||
| // Note: reasoning effort is only available for reasoning models (at this moment o3-mini & o1 models) | ||
| ReasoningEffort = ChatReasoningEffortLevel.Low | ||
| }; | ||
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| // Create KernelArguments using the execution settings. | ||
| var kernelArgs = new KernelArguments(executionSettings); | ||
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| StringBuilder chatPrompt = new(""" | ||
| <message role="developer">You are an expert software engineer, specialized in the Semantic Kernel SDK and NET framework</message> | ||
| <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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| // Invoke the prompt with high reasoning effort. | ||
| var reply = await kernel.InvokePromptAsync(chatPrompt.ToString(), kernelArgs); | ||
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| Console.WriteLine(reply); | ||
| } | ||
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| /// <summary> | ||
| /// Sample showing how to use <see cref="IChatCompletionService"/> directly with a <see cref="ChatHistory"/>. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task ServicePromptWithReasoningAsync() | ||
| { | ||
| Console.WriteLine("======== Azure Open AI - Chat Completion with Azure Default Credential with Reasoning ========"); | ||
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| Assert.NotNull(TestConfiguration.AzureOpenAI.ChatDeploymentName); | ||
| Assert.NotNull(TestConfiguration.AzureOpenAI.Endpoint); | ||
| Assert.NotNull(TestConfiguration.AzureOpenAI.ApiKey); | ||
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| IChatCompletionService chatCompletionService = new AzureOpenAIChatCompletionService( | ||
| deploymentName: TestConfiguration.AzureOpenAI.ChatDeploymentName, | ||
| endpoint: TestConfiguration.AzureOpenAI.Endpoint, | ||
| apiKey: TestConfiguration.AzureOpenAI.ApiKey, | ||
| modelId: TestConfiguration.AzureOpenAI.ChatModelId); | ||
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| // Create execution settings with high reasoning effort. | ||
| var executionSettings = new AzureOpenAIPromptExecutionSettings | ||
| { | ||
| // Flags Azure SDK to use the new token property. | ||
| SetNewMaxCompletionTokensEnabled = true, | ||
| MaxTokens = 2000, | ||
| // Note: reasoning effort is only available for reasoning models (at this moment o3-mini & o1 models) | ||
| ReasoningEffort = ChatReasoningEffortLevel.Low | ||
| }; | ||
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| // Create a ChatHistory and add messages. | ||
| var chatHistory = new ChatHistory(); | ||
| chatHistory.AddDeveloperMessage( | ||
| "You are an expert software engineer, specialized in the Semantic Kernel SDK and .NET framework."); | ||
| chatHistory.AddUserMessage( | ||
| "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. | ||
| var reply = await chatCompletionService.GetChatMessageContentAsync( | ||
| chatHistory: chatHistory, | ||
| executionSettings: executionSettings); | ||
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| Console.WriteLine(reply); | ||
| } | ||
| } |
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dotnet/samples/Concepts/ChatCompletion/OpenAI_ChatCompletion_WithReasoning.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,86 @@ | ||
| // Copyright (c) Microsoft. All rights reserved. | ||
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| using System.Text; | ||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.ChatCompletion; | ||
| using Microsoft.SemanticKernel.Connectors.OpenAI; | ||
| 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 | ||
| public class OpenAI_ChatCompletion_WithReasoning(ITestOutputHelper output) : BaseTest(output) | ||
| { | ||
| /// <summary> | ||
| /// Sample showing how to use <see cref="Kernel"/> with chat completion and chat prompt syntax. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task ChatPromptWithReasoningAsync() | ||
| { | ||
| Console.WriteLine("======== Open AI - Chat Completion with Reasoning ========"); | ||
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| Assert.NotNull(TestConfiguration.OpenAI.ChatModelId); | ||
| Assert.NotNull(TestConfiguration.OpenAI.ApiKey); | ||
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| var kernel = Kernel.CreateBuilder() | ||
| .AddOpenAIChatCompletion( | ||
| modelId: TestConfiguration.OpenAI.ChatModelId, | ||
| apiKey: TestConfiguration.OpenAI.ApiKey) | ||
| .Build(); | ||
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| // Create execution settings with low reasoning effort. | ||
| var executionSettings = new OpenAIPromptExecutionSettings //OpenAIPromptExecutionSettings | ||
| { | ||
| MaxTokens = 2000, | ||
| ReasoningEffort = ChatReasoningEffortLevel.Low // Only available for reasoning models (i.e: o3-mini, o1, ...) | ||
| }; | ||
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| // Create KernelArguments using the execution settings. | ||
| var kernelArgs = new KernelArguments(executionSettings); | ||
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| StringBuilder chatPrompt = new(""" | ||
| <message role="developer">You are an expert software engineer, specialized in the Semantic Kernel SDK and NET framework</message> | ||
| <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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| // Invoke the prompt with high reasoning effort. | ||
| var reply = await kernel.InvokePromptAsync(chatPrompt.ToString(), kernelArgs); | ||
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| Console.WriteLine(reply); | ||
| } | ||
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| /// <summary> | ||
| /// Sample showing how to use <see cref="IChatCompletionService"/> directly with a <see cref="ChatHistory"/>. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task ServicePromptWithReasoningAsync() | ||
| { | ||
| Assert.NotNull(TestConfiguration.OpenAI.ChatModelId); | ||
| 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. | ||
| var executionSettings = new OpenAIPromptExecutionSettings | ||
| { | ||
| MaxTokens = 2000, | ||
| ReasoningEffort = ChatReasoningEffortLevel.Low // Only available for reasoning models (i.e: o3-mini, o1, ...) | ||
| }; | ||
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| // Create a ChatHistory and add messages. | ||
| var chatHistory = new ChatHistory(); | ||
| chatHistory.AddDeveloperMessage( | ||
| "You are an expert software engineer, specialized in the Semantic Kernel SDK and .NET framework."); | ||
| chatHistory.AddUserMessage( | ||
| "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. | ||
| var reply = await chatCompletionService.GetChatMessageContentAsync( | ||
| chatHistory: chatHistory, | ||
| executionSettings: executionSettings); | ||
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| Console.WriteLine(reply); | ||
| } | ||
| } |