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69 changes: 0 additions & 69 deletions
69
dotnet/samples/Concepts/Agents/OpenAIAssistant_FileService.cs
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89 changes: 89 additions & 0 deletions
89
dotnet/samples/Concepts/FunctionCalling/AzureAIInference_FunctionCalling.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,89 @@ | ||
| // Copyright (c) Microsoft. All rights reserved. | ||
|
|
||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.Connectors.AzureAIInference; | ||
|
|
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| namespace FunctionCalling; | ||
| public class AzureAIInference_FunctionCalling : BaseTest | ||
| { | ||
| private readonly LoggingHandler _handler; | ||
| private readonly HttpClient _httpClient; | ||
| private bool _isDisposed; | ||
|
|
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| public AzureAIInference_FunctionCalling(ITestOutputHelper output) : base(output) | ||
| { | ||
| // Create a logging handler to output HTTP requests and responses | ||
| this._handler = new LoggingHandler(new HttpClientHandler(), this.Output); | ||
| this._httpClient = new(this._handler); | ||
| } | ||
|
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| /// <summary> | ||
| /// This example demonstrates usage of <see cref="FunctionChoiceBehavior.Auto"/> that advertises all kernel functions to the AI model. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task FunctionCallingAsync() | ||
| { | ||
| var kernel = CreateKernel(); | ||
| AzureAIInferencePromptExecutionSettings settings = new() { FunctionChoiceBehavior = FunctionChoiceBehavior.Auto() }; | ||
| Console.WriteLine(await kernel.InvokePromptAsync("Given the current time of day and weather, what is the likely color of the sky in Boston?", new(settings))); | ||
| } | ||
|
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| /// <summary> | ||
| /// This example demonstrates usage of <see cref="FunctionChoiceBehavior.Auto"/> that advertises all kernel functions to the AI model. | ||
| /// </summary> | ||
| [Fact] | ||
| public async Task FunctionCallingWithPromptExecutionSettingsAsync() | ||
| { | ||
| var kernel = CreateKernel(); | ||
| PromptExecutionSettings settings = new() { FunctionChoiceBehavior = FunctionChoiceBehavior.Auto() }; | ||
| Console.WriteLine(await kernel.InvokePromptAsync("Given the current time of day and weather, what is the likely color of the sky in Boston?", new(settings))); | ||
| } | ||
|
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| protected override void Dispose(bool disposing) | ||
| { | ||
| if (!this._isDisposed) | ||
| { | ||
| if (disposing) | ||
| { | ||
| this._handler.Dispose(); | ||
| this._httpClient.Dispose(); | ||
| } | ||
|
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| this._isDisposed = true; | ||
| } | ||
| base.Dispose(disposing); | ||
| } | ||
|
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| private Kernel CreateKernel() | ||
| { | ||
| // Create kernel | ||
| var kernel = Kernel.CreateBuilder() | ||
| .AddAzureAIInferenceChatCompletion( | ||
| modelId: TestConfiguration.AzureAIInference.ChatModelId, | ||
| endpoint: new Uri(TestConfiguration.AzureAIInference.Endpoint), | ||
| apiKey: TestConfiguration.AzureAIInference.ApiKey, | ||
| httpClient: this._httpClient) | ||
| .Build(); | ||
|
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| // Add a plugin with some helper functions we want to allow the model to call. | ||
| kernel.ImportPluginFromFunctions("HelperFunctions", | ||
| [ | ||
| kernel.CreateFunctionFromMethod(() => new List<string> { "Squirrel Steals Show", "Dog Wins Lottery" }, "GetLatestNewsTitles", "Retrieves latest news titles."), | ||
| kernel.CreateFunctionFromMethod(() => DateTime.UtcNow.ToString("R"), "GetCurrentUtcDateTime", "Retrieves the current date time in UTC."), | ||
| kernel.CreateFunctionFromMethod((string cityName, string currentDateTime) => | ||
| cityName switch | ||
| { | ||
| "Boston" => "61 and rainy", | ||
| "London" => "55 and cloudy", | ||
| "Miami" => "80 and sunny", | ||
| "Paris" => "60 and rainy", | ||
| "Tokyo" => "50 and sunny", | ||
| "Sydney" => "75 and sunny", | ||
| "Tel Aviv" => "80 and sunny", | ||
| _ => "31 and snowing", | ||
| }, "GetWeatherForCity", "Gets the current weather for the specified city"), | ||
| ]); | ||
|
|
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| return kernel; | ||
| } | ||
| } |
34 changes: 34 additions & 0 deletions
34
dotnet/samples/Concepts/Memory/OpenAI_EmbeddingGeneration.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,34 @@ | ||
| // 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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