Files
semantic-kernel/dotnet/samples/GettingStarted/Step1_Create_Kernel.cs
Roger Barreto f66a30bbd9 .Net Samples Restructure - Phase 4 (#6057)
### Motivation and Context

Make samples more console friendly.

This change allows the code to be copy and pasted in a Console App,
which virtually no code changes to the core code in sample
implementations.
2024-04-30 11:34:44 +00:00

53 lines
2.3 KiB
C#

// Copyright (c) Microsoft. All rights reserved.
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.OpenAI;
namespace GettingStarted;
/// <summary>
/// This example shows how to create and use a <see cref="Kernel"/>.
/// </summary>
public sealed class Step1_Create_Kernel(ITestOutputHelper output) : BaseTest(output)
{
/// <summary>
/// Show how to create a <see cref="Kernel"/> and use it to execute prompts.
/// </summary>
[Fact]
public async Task RunAsync()
{
// Create a kernel with OpenAI chat completion
Kernel kernel = Kernel.CreateBuilder()
.AddOpenAIChatCompletion(
modelId: TestConfiguration.OpenAI.ChatModelId,
apiKey: TestConfiguration.OpenAI.ApiKey)
.Build();
// Example 1. Invoke the kernel with a prompt and display the result
Console.WriteLine(await kernel.InvokePromptAsync("What color is the sky?"));
Console.WriteLine();
// Example 2. Invoke the kernel with a templated prompt and display the result
KernelArguments arguments = new() { { "topic", "sea" } };
Console.WriteLine(await kernel.InvokePromptAsync("What color is the {{$topic}}?", arguments));
Console.WriteLine();
// Example 3. Invoke the kernel with a templated prompt and stream the results to the display
await foreach (var update in kernel.InvokePromptStreamingAsync("What color is the {{$topic}}? Provide a detailed explanation.", arguments))
{
Console.Write(update);
}
Console.WriteLine(string.Empty);
// Example 4. Invoke the kernel with a templated prompt and execution settings
arguments = new(new OpenAIPromptExecutionSettings { MaxTokens = 500, Temperature = 0.5 }) { { "topic", "dogs" } };
Console.WriteLine(await kernel.InvokePromptAsync("Tell me a story about {{$topic}}", arguments));
// Example 5. Invoke the kernel with a templated prompt and execution settings configured to return JSON
#pragma warning disable SKEXP0010
arguments = new(new OpenAIPromptExecutionSettings { ResponseFormat = "json_object" }) { { "topic", "chocolate" } };
Console.WriteLine(await kernel.InvokePromptAsync("Create a recipe for a {{$topic}} cake in JSON format", arguments));
}
}