Update Azure OpenAI services and Semantic Kernel version

- Updated `VectorSearchService.cs` to replace the text embedding generation service with an embedding generator and adjusted embedding generation and vector search logic.
- Changed `Microsoft.SemanticKernel` package version from 1.50.0 to 1.51.0 in `SqlDatabaseVectorSearch.csproj` and modified `NoWarn` property settings.

SqlDatabaseVectorSearch/Program.cs

@@ -60,8 +60,8 @@ builder.Services.ConfigureHttpClientDefaults(configure =>
 // Semantic Kernel is used to generate embeddings and to reformulate questions taking into account all the previous interactions,
 // so that embeddings themselves can be generated more accurately.
 builder.Services.AddKernel()
-    .AddAzureOpenAITextEmbeddingGeneration(aiSettings.Embedding.Deployment, aiSettings.Embedding.Endpoint, aiSettings.Embedding.ApiKey, dimensions: aiSettings.Embedding.Dimensions)
-    .AddAzureOpenAIChatCompletion(aiSettings.ChatCompletion.Deployment, aiSettings.ChatCompletion.Endpoint, aiSettings.ChatCompletion.ApiKey);
+    .AddAzureOpenAIEmbeddingGenerator(aiSettings.Embedding.Deployment, aiSettings.Embedding.Endpoint, aiSettings.Embedding.ApiKey, modelId: aiSettings.Embedding.ModelId, dimensions: aiSettings.Embedding.Dimensions)
+    .AddAzureOpenAIChatCompletion(aiSettings.ChatCompletion.Deployment, aiSettings.ChatCompletion.Endpoint, aiSettings.ChatCompletion.ApiKey, modelId: aiSettings.ChatCompletion.ModelId);
 
 builder.Services.AddSingleton<TokenizerService>();
 builder.Services.AddSingleton<ChatService>();

SqlDatabaseVectorSearch/Services/VectorSearchService.cs

@@ -1,18 +1,19 @@
 using System.Data;
 using System.Runtime.CompilerServices;
 using Microsoft.EntityFrameworkCore;
+using Microsoft.Extensions.AI;
 using Microsoft.Extensions.Options;
-using Microsoft.SemanticKernel.Embeddings;
 using SqlDatabaseVectorSearch.ContentDecoders;
 using SqlDatabaseVectorSearch.DataAccessLayer;
 using SqlDatabaseVectorSearch.Models;
 using SqlDatabaseVectorSearch.Settings;
 using SqlDatabaseVectorSearch.TextChunkers;
+using ChatResponse = SqlDatabaseVectorSearch.Models.ChatResponse;
 using Entities = SqlDatabaseVectorSearch.DataAccessLayer.Entities;
 
 namespace SqlDatabaseVectorSearch.Services;
 
-public class VectorSearchService(IServiceProvider serviceProvider, ApplicationDbContext dbContext, DocumentService documentService, ITextEmbeddingGenerationService textEmbeddingGenerationService, TokenizerService tokenizerService, ChatService chatService, TimeProvider timeProvider, IOptions<AppSettings> appSettingsOptions, ILogger<VectorSearchService> logger)
+public class VectorSearchService(IServiceProvider serviceProvider, ApplicationDbContext dbContext, DocumentService documentService, IEmbeddingGenerator<string, Embedding<float>> embeddingGenerator, TokenizerService tokenizerService, ChatService chatService, TimeProvider timeProvider, IOptions<AppSettings> appSettingsOptions, ILogger<VectorSearchService> logger)
 {
     private readonly AppSettings appSettings = appSettingsOptions.Value;
 
@@ -42,14 +43,15 @@ public class VectorSearchService(IServiceProvider serviceProvider, ApplicationDb
             // Split the content into chunks and generate the embeddings for each one.
             var textChunker = serviceProvider.GetRequiredKeyedService<ITextChunker>(contentType);
             var paragraphs = textChunker.Split(content);
-            var embeddings = await textEmbeddingGenerationService.GenerateEmbeddingsAsync(paragraphs, cancellationToken: cancellationToken);
+
+            var embeddings = await embeddingGenerator.GenerateAndZipAsync(paragraphs, cancellationToken: cancellationToken);
 
             // Save the document chunks and the corresponding embedding in the database.
-            foreach (var (index, paragraph) in paragraphs.Index())
+            foreach (var (index, embedding) in embeddings.Index())
             {
-                logger.LogDebug("Storing a paragraph of {TokenCount} tokens.", tokenizerService.CountChatCompletionTokens(paragraph));
+                logger.LogDebug("Storing a paragraph of {TokenCount} tokens.", tokenizerService.CountChatCompletionTokens(embedding.Value));
 
-                var documentChunk = new Entities.DocumentChunk { Document = document, Index = index, Content = paragraph!, Embedding = embeddings[index].ToArray() };
+                var documentChunk = new Entities.DocumentChunk { Document = document, Index = index, Content = embedding.Value, Embedding = embedding.Embedding.Vector.ToArray() };
                 dbContext.DocumentChunks.Add(documentChunk);
             }
 
@@ -108,7 +110,7 @@ public class VectorSearchService(IServiceProvider serviceProvider, ApplicationDb
         logger.LogDebug("Embedding Token Count: {EmbeddingTokenCount}", embeddingTokenCount);
 
         // Perform Vector Search on SQL Database.
-        var questionEmbedding = await textEmbeddingGenerationService.GenerateEmbeddingAsync(reformulatedQuestion.Text!, cancellationToken: cancellationToken);
+        var questionEmbedding = await embeddingGenerator.GenerateVectorAsync(reformulatedQuestion.Text!, cancellationToken: cancellationToken);
 
         var chunks = await dbContext.DocumentChunks
                     .OrderBy(c => EF.Functions.VectorDistance("cosine", c.Embedding, questionEmbedding.ToArray()))

SqlDatabaseVectorSearch/SqlDatabaseVectorSearch.csproj

@@ -4,7 +4,7 @@
         <TargetFramework>net9.0</TargetFramework>
         <ImplicitUsings>enable</ImplicitUsings>
         <Nullable>enable</Nullable>
-        <NoWarn>$(NoWarn);SKEXP0001;SKEXP0010;SKEXP0050;EXTEXP0018</NoWarn>
+        <NoWarn>$(NoWarn);SKEXP0010;SKEXP0050</NoWarn>
     </PropertyGroup>
 
     <ItemGroup>
@@ -24,7 +24,7 @@
         <PackageReference Include="Microsoft.ML.Tokenizers" Version="1.0.2" />
         <PackageReference Include="Microsoft.ML.Tokenizers.Data.Cl100kBase" Version="1.0.2" />
         <PackageReference Include="Microsoft.ML.Tokenizers.Data.O200kBase" Version="1.0.2" />
-        <PackageReference Include="Microsoft.SemanticKernel" Version="1.50.0" />
+        <PackageReference Include="Microsoft.SemanticKernel" Version="1.51.0" />
         <PackageReference Include="MimeMapping" Version="3.1.0" />
         <PackageReference Include="MinimalHelpers.FluentValidation" Version="1.1.3" />
         <PackageReference Include="MinimalHelpers.Routing.Analyzers" Version="1.1.3" />