chore: import upstream snapshot with attribution

2026-07-13 13:21:23 +08:00
commit b957a53def
5423 changed files with 863745 additions and 0 deletions
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+// Copyright (c) Microsoft. All rights reserved.
+
+using Google.Apis.Auth.OAuth2;
+using Microsoft.Extensions.AI;
+using Microsoft.SemanticKernel;
+using xRetry;
+
+namespace Memory;
+
+// The following example shows how to use Semantic Kernel with Google AI and Google's Vertex AI for embedding generation,
+// including the ability to specify custom dimensions.
+public class Google_EmbeddingGeneration(ITestOutputHelper output) : BaseTest(output)
+{
+    /// <summary>
+    /// This test demonstrates how to use the Google Vertex AI embedding generation service with default dimensions.
+    /// </summary>
+    /// <remarks>
+    /// Currently custom dimensions are not supported for Vertex AI.
+    /// </remarks>
+    [RetryFact(typeof(HttpOperationException))]
+    public async Task GenerateEmbeddingWithDefaultDimensionsUsingVertexAI()
+    {
+        string? bearerToken = null;
+
+        Assert.NotNull(TestConfiguration.VertexAI.EmbeddingModelId);
+        Assert.NotNull(TestConfiguration.VertexAI.ClientId);
+        Assert.NotNull(TestConfiguration.VertexAI.ClientSecret);
+        Assert.NotNull(TestConfiguration.VertexAI.Location);
+        Assert.NotNull(TestConfiguration.VertexAI.ProjectId);
+
+        IKernelBuilder kernelBuilder = Kernel.CreateBuilder();
+        kernelBuilder.AddVertexAIEmbeddingGenerator(
+                modelId: TestConfiguration.VertexAI.EmbeddingModelId!,
+                bearerTokenProvider: GetBearerToken,
+                location: TestConfiguration.VertexAI.Location,
+                projectId: TestConfiguration.VertexAI.ProjectId);
+        Kernel kernel = kernelBuilder.Build();
+
+        var embeddingGenerator = kernel.GetRequiredService<IEmbeddingGenerator<string, Embedding<float>>>();
+
+        // Generate embeddings with the default dimensions for the model
+        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 codebase."]);
+
+        Console.WriteLine($"Generated '{embeddings.Count}' embedding(s) with '{embeddings[0].Vector.Length}' dimensions (default) for the provided text");
+
+        // Uses Google.Apis.Auth.OAuth2 to get the bearer token
+        async ValueTask<string> GetBearerToken()
+        {
+            if (!string.IsNullOrEmpty(bearerToken))
+            {
+                return bearerToken;
+            }
+
+            var credential = GoogleWebAuthorizationBroker.AuthorizeAsync(
+                new ClientSecrets
+                {
+                    ClientId = TestConfiguration.VertexAI.ClientId,
+                    ClientSecret = TestConfiguration.VertexAI.ClientSecret
+                },
+                ["https://www.googleapis.com/auth/cloud-platform"],
+                "user",
+                CancellationToken.None);
+
+            var userCredential = await credential.WaitAsync(CancellationToken.None);
+            bearerToken = userCredential.Token.AccessToken;
+
+            return bearerToken;
+        }
+    }
+
+    [RetryFact(typeof(HttpOperationException))]
+    public async Task GenerateEmbeddingWithDefaultDimensionsUsingGoogleAI()
+    {
+        Assert.NotNull(TestConfiguration.GoogleAI.EmbeddingModelId);
+        Assert.NotNull(TestConfiguration.GoogleAI.ApiKey);
+
+        IKernelBuilder kernelBuilder = Kernel.CreateBuilder();
+        kernelBuilder.AddGoogleAIEmbeddingGenerator(
+                modelId: TestConfiguration.GoogleAI.EmbeddingModelId!,
+                apiKey: TestConfiguration.GoogleAI.ApiKey);
+        Kernel kernel = kernelBuilder.Build();
+
+        var embeddingGenerator = kernel.GetRequiredService<IEmbeddingGenerator<string, Embedding<float>>>();
+
+        // Generate embeddings with the default dimensions for the model
+        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 codebase."]);
+
+        Console.WriteLine($"Generated '{embeddings.Count}' embedding(s) with '{embeddings[0].Vector.Length}' dimensions (default) for the provided text");
+    }
+
+    [RetryFact(typeof(HttpOperationException))]
+    public async Task GenerateEmbeddingWithCustomDimensionsUsingGoogleAI()
+    {
+        Assert.NotNull(TestConfiguration.GoogleAI.EmbeddingModelId);
+        Assert.NotNull(TestConfiguration.GoogleAI.ApiKey);
+
+        // Specify custom dimensions for the embeddings
+        const int CustomDimensions = 512;
+
+        IKernelBuilder kernelBuilder = Kernel.CreateBuilder();
+        kernelBuilder.AddGoogleAIEmbeddingGenerator(
+                modelId: TestConfiguration.GoogleAI.EmbeddingModelId!,
+                apiKey: TestConfiguration.GoogleAI.ApiKey,
+                dimensions: CustomDimensions);
+        Kernel kernel = kernelBuilder.Build();
+
+        var embeddingGenerator = kernel.GetRequiredService<IEmbeddingGenerator<string, Embedding<float>>>();
+
+        // Generate embeddings with the specified custom dimensions
+        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 codebase."]);
+
+        Console.WriteLine($"Generated '{embeddings.Count}' embedding(s) with '{embeddings[0].Vector.Length}' dimensions (custom: '{CustomDimensions}') for the provided text");
+
+        // Verify that we received embeddings with our requested dimensions
+        Assert.Equal(CustomDimensions, embeddings[0].Vector.Length);
+    }
+}