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dotnet/samples/Concepts/Memory/OpenAI_EmbeddingGeneration.cs
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// Copyright (c) Microsoft. All rights reserved. | ||
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using Microsoft.SemanticKernel; | ||
using Microsoft.SemanticKernel.Embeddings; | ||
using xRetry; | ||
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#pragma warning disable format // Format item can be simplified | ||
#pragma warning disable CA1861 // Avoid constant arrays as arguments | ||
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namespace Memory; | ||
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// 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); | ||
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IKernelBuilder kernelBuilder = Kernel.CreateBuilder(); | ||
kernelBuilder.AddOpenAITextEmbeddingGeneration( | ||
modelId: TestConfiguration.OpenAI.EmbeddingModelId!, | ||
apiKey: TestConfiguration.OpenAI.ApiKey!); | ||
Kernel kernel = kernelBuilder.Build(); | ||
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var embeddingGenerator = kernel.GetRequiredService<ITextEmbeddingGenerationService>(); | ||
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// Generate embeddings for the specified text. | ||
var embeddings = await embeddingGenerator.GenerateEmbeddingsAsync(["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."]); | ||
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Console.WriteLine($"Generated {embeddings.Count} embeddings for the provided text"); | ||
} | ||
} |
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