35 lines
1.4 KiB
C#
35 lines
1.4 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
|
|
|
|
using Microsoft.Extensions.AI;
|
|
using Microsoft.SemanticKernel;
|
|
using xRetry;
|
|
|
|
#pragma warning disable format // Format item can be simplified
|
|
#pragma warning disable CA1861 // Avoid constant arrays as arguments
|
|
|
|
namespace Memory;
|
|
|
|
// The following example shows how to use Semantic Kernel with OpenAI.
|
|
public class OpenAI_EmbeddingGeneration(ITestOutputHelper output) : BaseTest(output)
|
|
{
|
|
[RetryFact(typeof(HttpOperationException))]
|
|
public async Task RunEmbeddingAsync()
|
|
{
|
|
Assert.NotNull(TestConfiguration.OpenAI.EmbeddingModelId);
|
|
Assert.NotNull(TestConfiguration.OpenAI.ApiKey);
|
|
|
|
IKernelBuilder kernelBuilder = Kernel.CreateBuilder();
|
|
kernelBuilder.AddOpenAIEmbeddingGenerator(
|
|
modelId: TestConfiguration.OpenAI.EmbeddingModelId!,
|
|
apiKey: TestConfiguration.OpenAI.ApiKey!);
|
|
Kernel kernel = kernelBuilder.Build();
|
|
|
|
var embeddingGenerator = kernel.GetRequiredService<IEmbeddingGenerator<string, Embedding<float>>>();
|
|
|
|
// Generate embeddings for the specified text.
|
|
var embeddings = await embeddingGenerator.GenerateAsync(["Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase."]);
|
|
|
|
Console.WriteLine($"Generated {embeddings.Count} embeddings for the provided text");
|
|
}
|
|
}
|