wehub-resource-sync
79 lines
4.0 KiB
C#
79 lines
4.0 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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// ==========================================================================================================
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// The easier way to instantiate the Semantic Kernel is to use KernelBuilder.
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// You can access the builder using Kernel.CreateBuilder().
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using System.Diagnostics;
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using Microsoft.Extensions.DependencyInjection;
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using Microsoft.Extensions.Logging;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Plugins.Core;
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namespace DependencyInjection;
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public class Kernel_Building(ITestOutputHelper output) : BaseTest(output)
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{
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[Fact]
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public void BuildKernelUsingServiceCollection()
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{
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// For greater flexibility and to incorporate arbitrary services, KernelBuilder.Services
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// provides direct access to an underlying IServiceCollection.
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IKernelBuilder builder = Kernel.CreateBuilder();
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builder.Services.AddLogging(c => c.AddConsole().SetMinimumLevel(LogLevel.Information))
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.AddHttpClient()
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.AddAzureOpenAIChatCompletion(
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deploymentName: TestConfiguration.AzureOpenAI.ChatDeploymentName,
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endpoint: TestConfiguration.AzureOpenAI.Endpoint,
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apiKey: TestConfiguration.AzureOpenAI.ApiKey,
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modelId: TestConfiguration.AzureOpenAI.ChatModelId);
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Kernel kernel2 = builder.Build();
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}
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[Fact]
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public void BuildKernelUsingServiceProvider()
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{
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// Every call to KernelBuilder.Build creates a new Kernel instance, with a new service provider
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// and a new plugin collection.
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var builder = Kernel.CreateBuilder();
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Debug.Assert(!ReferenceEquals(builder.Build(), builder.Build()));
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// KernelBuilder provides a convenient API for creating Kernel instances. However, it is just a
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// wrapper around a service collection, ultimately constructing a Kernel
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// using the public constructor that's available for anyone to use directly if desired.
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var services = new ServiceCollection();
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services.AddLogging(c => c.AddConsole().SetMinimumLevel(LogLevel.Information));
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services.AddHttpClient();
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services.AddAzureOpenAIChatCompletion(
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deploymentName: TestConfiguration.AzureOpenAI.ChatDeploymentName,
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endpoint: TestConfiguration.AzureOpenAI.Endpoint,
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apiKey: TestConfiguration.AzureOpenAI.ApiKey,
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modelId: TestConfiguration.AzureOpenAI.ChatModelId);
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Kernel kernel4 = new(services.BuildServiceProvider());
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// Kernels can also be constructed and resolved via such a dependency injection container.
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services.AddTransient<Kernel>();
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Kernel kernel5 = services.BuildServiceProvider().GetRequiredService<Kernel>();
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}
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[Fact]
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public void BuildKernelUsingServiceCollectionExtension()
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{
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// In fact, the AddKernel method exists to simplify this, registering a singleton KernelPluginCollection
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// that can be populated automatically with all IKernelPlugins registered in the collection, and a
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// transient Kernel that can then automatically be constructed from the service provider and resulting
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// plugins collection.
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var services = new ServiceCollection();
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services.AddLogging(c => c.AddConsole().SetMinimumLevel(LogLevel.Information));
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services.AddHttpClient();
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services.AddKernel().AddAzureOpenAIChatCompletion(
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deploymentName: TestConfiguration.AzureOpenAI.ChatDeploymentName,
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endpoint: TestConfiguration.AzureOpenAI.Endpoint,
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apiKey: TestConfiguration.AzureOpenAI.ApiKey,
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modelId: TestConfiguration.AzureOpenAI.ChatModelId);
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services.AddSingleton<KernelPlugin>(sp => KernelPluginFactory.CreateFromType<TimePlugin>(serviceProvider: sp));
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services.AddSingleton<KernelPlugin>(sp => KernelPluginFactory.CreateFromType<HttpPlugin>(serviceProvider: sp));
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Kernel kernel6 = services.BuildServiceProvider().GetRequiredService<Kernel>();
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}
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}
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