.Net: Fix: include taskType in Google AI embedding request (fixes #13250) (#13277)

### Motivation and Context
This PR fixes issue
[#13250](#13250)
by ensuring that the Google AI embedding connector correctly includes
the taskType field in outgoing requests when EmbeddingGenerationOptions
contains a task_type value.
Previously, the connector ignored this field, causing task-specific
embeddings (RETRIEVAL_DOCUMENT, RETRIEVAL_QUERY, etc.) to default to
generic embeddings.

### Description
Changes
Extended GoogleAIEmbeddingRequest.FromData() to include an optional
taskType parameter.
Updated GoogleAIEmbeddingClient to extract task_type from
EmbeddingGenerationOptions.AdditionalProperties.
Added a new overload in GoogleAITextEmbeddingGenerationService to pass
EmbeddingGenerationOptions while maintaining backward compatibility.
Added unit test FromData_Should_Include_TaskType_When_Provided to verify
that "taskType" appears correctly in serialized JSON.

### Contribution Checklist

<!-- Before submitting this PR, please make sure: -->

- [ Done] The code builds clean without any errors or warnings
- [ Done] The PR follows the [SK Contribution
Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md)
and the [pre-submission formatting
script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts)
raises no violations
- [ Done] All unit tests pass, and I have added new tests where possible
- [ Done] I didn't break anyone 😄

---------

Co-authored-by: Mark Wallace <[email protected]>
Co-authored-by: Roger Barreto <[email protected]>

Author: 3 people

dotnet/src/Connectors/Connectors.Google.UnitTests/Core/GoogleAI/GoogleAIClientEmbeddingsGenerationTests.cs

@@ -219,6 +219,35 @@ public async Task ShouldNotIncludeDimensionsInAllRequestsWhenNotProvidedAsync()
         Assert.All(request.Requests, item => Assert.Null(item.Dimensions));
     }
 
+    [Fact]
+    public async Task GenerateEmbeddingsUsingEmbeddingGenerationOptionsShouldOverrideDimensionsAndModelAsync()
+    {
+        // Arrange
+        var client = this.CreateEmbeddingsClient();
+        var dataToEmbed = new List<string>()
+        {
+            "First text to embed",
+            "Second text to embed",
+            "Third text to embed"
+        };
+
+        var options = new Microsoft.Extensions.AI.EmbeddingGenerationOptions { Dimensions = 10, ModelId = "override-model" };
+
+        // Act
+        await client.GenerateEmbeddingsAsync(dataToEmbed, options);
+
+        // Assert
+        var request = JsonSerializer.Deserialize<GoogleAIEmbeddingRequest>(this._messageHandlerStub.RequestContent);
+        Assert.NotNull(request);
+        Assert.Equal(dataToEmbed.Count, request.Requests.Count);
+        Assert.All(request.Requests,
+            item =>
+            {
+                Assert.Contains(options.ModelId, item.Model);
+                Assert.Equal(options.Dimensions, item.Dimensions);
+            });
+    }
+
     private GoogleAIEmbeddingClient CreateEmbeddingsClient(
         string modelId = "fake-model",
         int? dimensions = null)

dotnet/src/Connectors/Connectors.Google.UnitTests/Core/GoogleAI/GoogleAIEmbeddingRequestTests.cs

@@ -1,6 +1,7 @@
 // Copyright (c) Microsoft. All rights reserved.
 
 using System.Text.Json;
+using Microsoft.Extensions.AI;
 using Microsoft.SemanticKernel.Connectors.Google.Core;
 using Xunit;
 
@@ -83,4 +84,32 @@ public void FromDataJsonIncludesDimensionsWhenProvided()
         // Assert
         Assert.Contains($"{DimensionalityJsonPropertyName}:{Dimensions}", json);
     }
+
+    [Theory]
+    [InlineData("TaskType")]
+    [InlineData("Task_Type")]
+    [InlineData("taskType")]
+    [InlineData("task_Type")]
+    [InlineData("tasktype")]
+    [InlineData("task_type")]
+    public void FromDataShouldIncludeTaskTypeWhenProvided(string additionalPropertyKeyName)
+    {
+        // Arrange
+        var input = new[] { "This is a retrieval document." };
+        var modelId = "embedding-001";
+        var dimensions = 1024;
+        var taskType = "RETRIEVAL_DOCUMENT";
+
+        var options = new EmbeddingGenerationOptions { AdditionalProperties = new AdditionalPropertiesDictionary { [additionalPropertyKeyName] = taskType } };
+
+        // Act
+        var request = GoogleAIEmbeddingRequest.FromData(input, modelId, dimensions, options);
+
+        // Serialize to JSON (this is what would be sent in the HTTP request)
+        var json = System.Text.Json.JsonSerializer.Serialize(request);
+
+        // Assert
+        Assert.Contains("\"taskType\":\"RETRIEVAL_DOCUMENT\"", json);
+        Assert.Contains("\"model\":\"models/embedding-001\"", json);
+    }
 }

dotnet/src/Connectors/Connectors.Google/Core/GoogleAI/GoogleAIEmbeddingClient.cs

@@ -6,6 +6,7 @@
 using System.Net.Http;
 using System.Threading;
 using System.Threading.Tasks;
+using Microsoft.Extensions.AI;
 using Microsoft.Extensions.Logging;
 
 namespace Microsoft.SemanticKernel.Connectors.Google.Core;
@@ -54,15 +55,18 @@ public GoogleAIEmbeddingClient(
     /// Generates embeddings for the given data asynchronously.
     /// </summary>
     /// <param name="data">The list of strings to generate embeddings for.</param>
+    /// <param name="options">The embedding generation options.</param>
     /// <param name="cancellationToken">The cancellation token to cancel the operation.</param>
     /// <returns>Result contains a list of read-only memories of floats representing the generated embeddings.</returns>
     public async Task<IList<ReadOnlyMemory<float>>> GenerateEmbeddingsAsync(
         IList<string> data,
+        EmbeddingGenerationOptions? options = null,
         CancellationToken cancellationToken = default)
     {
         Verify.NotNullOrEmpty(data);
 
-        var geminiRequest = this.GetEmbeddingRequest(data);
+        var geminiRequest = this.GetEmbeddingRequest(data, options);
+
         using var httpRequestMessage = await this.CreateHttpRequestAsync(geminiRequest, this._embeddingEndpoint).ConfigureAwait(false);
 
         string body = await this.SendRequestAndGetStringBodyAsync(httpRequestMessage, cancellationToken)
@@ -71,8 +75,8 @@ public async Task<IList<ReadOnlyMemory<float>>> GenerateEmbeddingsAsync(
         return DeserializeAndProcessEmbeddingsResponse(body);
     }
 
-    private GoogleAIEmbeddingRequest GetEmbeddingRequest(IEnumerable<string> data)
-        => GoogleAIEmbeddingRequest.FromData(data, this._embeddingModelId, this._dimensions);
+    private GoogleAIEmbeddingRequest GetEmbeddingRequest(IEnumerable<string> data, EmbeddingGenerationOptions? options = null)
+    => GoogleAIEmbeddingRequest.FromData(data, options?.ModelId ?? this._embeddingModelId, options?.Dimensions ?? this._dimensions, options);
 
     private static List<ReadOnlyMemory<float>> DeserializeAndProcessEmbeddingsResponse(string body)
         => ProcessEmbeddingsResponse(DeserializeResponse<GoogleAIEmbeddingResponse>(body));

dotnet/src/Connectors/Connectors.Google/Core/GoogleAI/GoogleAIEmbeddingRequest.cs

@@ -3,6 +3,7 @@
 using System.Collections.Generic;
 using System.Linq;
 using System.Text.Json.Serialization;
+using Microsoft.Extensions.AI;
 
 namespace Microsoft.SemanticKernel.Connectors.Google.Core;
 
@@ -11,24 +12,48 @@ internal sealed class GoogleAIEmbeddingRequest
     [JsonPropertyName("requests")]
     public IList<RequestEmbeddingContent> Requests { get; set; } = null!;
 
-    public static GoogleAIEmbeddingRequest FromData(IEnumerable<string> data, string modelId, int? dimensions = null) => new()
+    public static GoogleAIEmbeddingRequest FromData(IEnumerable<string> data, string modelId, int? dimensions = null, EmbeddingGenerationOptions? options = null)
     {
-        Requests = data.Select(text => new RequestEmbeddingContent
+        static string? GetTaskType(EmbeddingGenerationOptions? options)
         {
-            Model = $"models/{modelId}",
-            Content = new()
+            if (options?.AdditionalProperties is not null)
             {
-                Parts =
-                [
-                    new()
-                    {
-                        Text = text
-                    }
-                ]
-            },
-            Dimensions = dimensions
-        }).ToList()
-    };
+                object? taskType = null;
+                object? task_type = null;
+
+                // AdditionalProperties is case-insensitive
+                if (options?.AdditionalProperties.TryGetValue("task_type", out task_type) == true ||
+                    options?.AdditionalProperties.TryGetValue("tasktype", out taskType) == true)
+                {
+                    return (task_type ?? taskType)?.ToString();
+                }
+            }
+
+            return null;
+        }
+
+        var request = new GoogleAIEmbeddingRequest
+        {
+            Requests = [.. data.Select(text => new RequestEmbeddingContent
+            {
+                Model = $"models/{modelId}",
+                Content = new()
+                {
+                    Parts =
+                    [
+                        new()
+                        {
+                            Text = text
+                        }
+                    ]
+                },
+                Dimensions = dimensions,
+                TaskType = GetTaskType(options)
+            })]
+        };
+
+        return request;
+    }
 
     internal sealed class RequestEmbeddingContent
     {

dotnet/src/Connectors/Connectors.Google/Services/GoogleAITextEmbeddingGenerationService.cs

@@ -5,6 +5,7 @@
 using System.Net.Http;
 using System.Threading;
 using System.Threading.Tasks;
+using Microsoft.Extensions.AI;
 using Microsoft.Extensions.Logging;
 using Microsoft.SemanticKernel.Connectors.Google.Core;
 using Microsoft.SemanticKernel.Embeddings;
@@ -68,6 +69,31 @@ public Task<IList<ReadOnlyMemory<float>>> GenerateEmbeddingsAsync(
         Kernel? kernel = null,
         CancellationToken cancellationToken = default)
     {
-        return this._embeddingClient.GenerateEmbeddingsAsync(data, cancellationToken);
+        return this._embeddingClient.GenerateEmbeddingsAsync(data, null, cancellationToken);
+    }
+
+    /// <summary>
+    /// Generates an embedding from the given <paramref name="data"/>.
+    /// </summary>
+    /// <param name="data">List of strings to generate embeddings for</param>
+    /// <param name="options">Additional options for embedding generation</param>
+    /// <param name="kernel">The <see cref="Kernel"/> containing services, plugins, and other state for use throughout the operation.</param>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests. The default is <see cref="CancellationToken.None"/>.</param>
+    /// <returns>List of embeddings</returns>
+    /// <remarks>
+    /// <para>
+    /// The <paramref name="options"/> parameter can be used to override default settings such as <see cref="EmbeddingGenerationOptions.ModelId"/> and <see cref="EmbeddingGenerationOptions.Dimensions"/>
+    /// </para>
+    /// <para>
+    /// Additionally a key/value of <c>"taskType"</c> can be provided in the <see cref="EmbeddingGenerationOptions.AdditionalProperties"/> for specific embedding tasks.
+    /// </para>
+    /// </remarks>
+    public Task<IList<ReadOnlyMemory<float>>> GenerateEmbeddingsAsync(
+        IList<string> data,
+        EmbeddingGenerationOptions? options,
+        Kernel? kernel = null,
+        CancellationToken cancellationToken = default)
+    {
+        return this._embeddingClient.GenerateEmbeddingsAsync(data, options, cancellationToken);
     }
 }