Refactor caching and OpenAPI integration

Updated Program.cs to replace Swagger with OpenApi and MemoryCache with HybridCache. Refactored ChatService.cs to use HybridCache asynchronously. Removed MessageLimit from AppSettings.cs and appsettings.json. Updated SqlDatabaseVectorSearch.csproj to include HybridCache package and update dependencies.

SqlDatabaseVectorSearch/Program.cs

@@ -1,14 +1,13 @@
+using System.ComponentModel;
 using Microsoft.AspNetCore.Http.HttpResults;
 using Microsoft.EntityFrameworkCore;
-using Microsoft.OpenApi.Models;
 using Microsoft.SemanticKernel;
-using MinimalHelpers.OpenApi;
 using SqlDatabaseVectorSearch.DataAccessLayer;
 using SqlDatabaseVectorSearch.Models;
 using SqlDatabaseVectorSearch.Services;
 using SqlDatabaseVectorSearch.Settings;
 using TinyHelpers.AspNetCore.Extensions;
-using TinyHelpers.AspNetCore.Swagger;
+using TinyHelpers.AspNetCore.OpenApi;
 
 var builder = WebApplication.CreateBuilder(args);
 builder.Configuration.AddJsonFile("appsettings.local.json", optional: true, reloadOnChange: true);
@@ -22,13 +21,18 @@ builder.Services.AddSingleton(TimeProvider.System);
 builder.Services.AddSqlServer<ApplicationDbContext>(builder.Configuration.GetConnectionString("SqlConnection"), options =>
 {
     options.UseVectorSearch();
-    options.EnableRetryOnFailure();
 }, options =>
 {
     options.UseQueryTrackingBehavior(QueryTrackingBehavior.NoTracking);
 });
 
-builder.Services.AddMemoryCache();
+builder.Services.AddHybridCache(options =>
+{
+    options.DefaultEntryOptions = new()
+    {
+        LocalCacheExpiration = appSettings.MessageExpiration
+    };
+});
 
 // 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.
@@ -40,11 +44,8 @@ builder.Services.AddSingleton<TokenizerService>();
 builder.Services.AddSingleton<ChatService>();
 builder.Services.AddScoped<VectorSearchService>();
 
-builder.Services.AddEndpointsApiExplorer();
+builder.Services.AddOpenApi(options =>
-builder.Services.AddSwaggerGen(options =>
 {
-    options.SwaggerDoc("v1", new OpenApiInfo { Title = "SQL Database Vector Search API", Version = "v1" });
-
     options.AddDefaultResponse();
 });
 
@@ -61,11 +62,11 @@ app.UseStatusCodePages();
 
 if (app.Environment.IsDevelopment())
 {
-    app.UseSwagger();
+    app.MapOpenApi();
     app.UseSwaggerUI(options =>
     {
         options.RoutePrefix = string.Empty;
-        options.SwaggerEndpoint("/swagger/v1/swagger.json", "SQL Database Vector Search API v1");
+        options.SwaggerEndpoint("/openapi/v1.json", builder.Environment.ApplicationName);
     });
 }
 
@@ -76,24 +77,15 @@ documentsApiGroup.MapGet(string.Empty, async (VectorSearchService vectorSearchSe
     var documents = await vectorSearchService.GetDocumentsAsync();
     return TypedResults.Ok(documents);
 })
-.WithOpenApi(operation =>
+.WithSummary("Gets the list of documents");
-{
-    operation.Summary = "Gets the list of documents";
-    return operation;
-});
 
 documentsApiGroup.MapGet("{documentId:guid}/chunks", async (Guid documentId, VectorSearchService vectorSearchService) =>
 {
     var documents = await vectorSearchService.GetDocumentChunksAsync(documentId);
     return TypedResults.Ok(documents);
 })
-.WithOpenApi(operation =>
+.WithSummary("Gets the list of chunks of a given document")
-{
+.WithDescription("The list does not contain embedding. Use '/api/documents/{documentId}/chunks/{documentChunkId}' to get the embedding for a given chunk.");
-    operation.Summary = "Gets the list of chunks of a given document";
-    operation.Description = "The list does not contain embedding. Use '/api/documents/{documentId}/chunks/{documentChunkId}' to get the embedding for a given chunk.";
-
-    return operation;
-});
 
 documentsApiGroup.MapGet("{documentId:guid}/chunks/{documentChunkId:guid}", async Task<Results<Ok<DocumentChunk>, NotFound>> (Guid documentId, Guid documentChunkId, VectorSearchService vectorSearchService) =>
 {
@@ -105,13 +97,11 @@ documentsApiGroup.MapGet("{documentId:guid}/chunks/{documentChunkId:guid}", asyn
 
     return TypedResults.Ok(chunk);
 })
-.WithOpenApi(operation =>
+.ProducesProblem(StatusCodes.Status404NotFound)
-{
+.WithSummary("Gets the details of a given chunk, includings its embedding");
-    operation.Summary = "Gets the details of a given chunk, includings its embedding";
-    return operation;
-});
 
-documentsApiGroup.MapPost(string.Empty, async (IFormFile file, VectorSearchService vectorSearchService, Guid? documentId = null) =>
+documentsApiGroup.MapPost(string.Empty, async (IFormFile file, VectorSearchService vectorSearchService,
+    [Description("The unique identifier of the document. If not provided, a new one will be generated. If you specify an existing documentId, the corresponding document will be overwritten.")] Guid? documentId = null) =>
 {
     using var stream = file.OpenReadStream();
     documentId = await vectorSearchService.ImportAsync(stream, file.FileName, documentId);
@@ -119,43 +109,26 @@ documentsApiGroup.MapPost(string.Empty, async (IFormFile file, VectorSearchServi
     return TypedResults.Ok(new UploadDocumentResponse(documentId.Value));
 })
 .DisableAntiforgery()
-.WithOpenApi(operation =>
+.ProducesProblem(StatusCodes.Status400BadRequest)
-{
+.WithSummary("Uploads a document")
-    operation.Summary = "Uploads a document";
+.WithDescription("Uploads a document to SQL Database and saves its embedding using the new native Vector type. The document will be indexed and used to answer questions. Currently, only PDF files are supported.");
-    operation.Description = "Uploads a document to SQL Database and saves its embedding using the new native Vector type. The document will be indexed and used to answer questions. Currently, only PDF files are supported.";
-
-    operation.Parameter("documentId").Description = "The unique identifier of the document. If not provided, a new one will be generated. If you specify an existing documentId, the corresponding document will be overwritten.";
-
-    return operation;
-});
 
 documentsApiGroup.MapDelete("{documentId:guid}", async (Guid documentId, VectorSearchService vectorSearchService) =>
 {
     await vectorSearchService.DeleteDocumentAsync(documentId);
     return TypedResults.NoContent();
 })
-.WithOpenApi(operation =>
+.WithSummary("Deletes a document")
-{
+.WithDescription("This endpoint deletes the document and all its chunks.");
-    operation.Summary = "Deletes a document";
-    operation.Description = "This endpoint deletes the document and all its chunks.";
 
-    return operation;
+app.MapPost("/api/ask", async (Question question, VectorSearchService vectorSearchService,
-});
+    [Description("If true, the question will be reformulated taking into account the context of the chat identified by the given ConversationId.")] bool reformulate = true) =>
-
-app.MapPost("/api/ask", async (Question question, VectorSearchService vectorSearchService, bool reformulate = true) =>
 {
     var response = await vectorSearchService.AskQuestionAsync(question, reformulate);
     return TypedResults.Ok(response);
 })
-.WithOpenApi(operation =>
+.WithSummary("Asks a question")
-{
+.WithDescription("The question will be reformulated taking into account the context of the chat identified by the given ConversationId.")
-    operation.Summary = "Asks a question";
-    operation.Description = "The question will be reformulated taking into account the context of the chat identified by the given ConversationId.";
-
-    operation.Parameter("reformulate").Description = "If true, the question will be reformulated taking into account the context of the chat identified by the given ConversationId.";
-
-    return operation;
-})
 .WithTags("Ask");
 
 app.Run();

SqlDatabaseVectorSearch/Services/ChatService.cs

@@ -1,5 +1,5 @@
 using System.Text;
-using Microsoft.Extensions.Caching.Memory;
+using Microsoft.Extensions.Caching.Hybrid;
 using Microsoft.Extensions.Options;
 using Microsoft.SemanticKernel.ChatCompletion;
 using Microsoft.SemanticKernel.Connectors.AzureOpenAI;
@@ -7,13 +7,13 @@ using SqlDatabaseVectorSearch.Settings;
 
 namespace SqlDatabaseVectorSearch.Services;
 
-public class ChatService(IMemoryCache cache, IChatCompletionService chatCompletionService, TokenizerService tokenizerService, IOptions<AppSettings> appSettingsOptions)
+public class ChatService(IChatCompletionService chatCompletionService, TokenizerService tokenizerService, HybridCache cache, IOptions<AppSettings> appSettingsOptions)
 {
     private readonly AppSettings appSettings = appSettingsOptions.Value;
 
     public async Task<string> CreateQuestionAsync(Guid conversationId, string question)
     {
-        var chat = new ChatHistory(cache.Get<ChatHistory?>(conversationId) ?? []);
+        var chat = await GetChatHistoryAsync(conversationId);
 
         var embeddingQuestion = $"""
             Reformulate the following question taking into account the context of the chat to perform embeddings search:
@@ -85,23 +85,33 @@ public class ChatService(IMemoryCache cache, IChatCompletionService chatCompleti
         });
 
         // Add question and answer to the chat history.
-        var history = new ChatHistory(cache.Get<ChatHistory?>(conversationId) ?? []);
+        await SetChatHistoryAsync(conversationId, question, answer.Content!);
-        history.AddUserMessage(question);
-        history.AddAssistantMessage(answer.Content!);
-
-        await UpdateCacheAsync(conversationId, history);
 
         return answer.Content!;
     }
 
-    private Task UpdateCacheAsync(Guid conversationId, ChatHistory chat)
+    private async Task UpdateCacheAsync(Guid conversationId, ChatHistory chat)
-    {
+        => await cache.SetAsync(conversationId.ToString(), chat);
-        if (chat.Count > appSettings.MessageLimit)
-        {
-            chat = new ChatHistory(chat.TakeLast(appSettings.MessageLimit));
-        }
 
-        cache.Set(conversationId, chat, appSettings.MessageExpiration);
+    private async Task<ChatHistory> GetChatHistoryAsync(Guid conversationId)
-        return Task.CompletedTask;
+    {
+        var historyCache = await cache.GetOrCreateAsync(conversationId.ToString(),
+        (cancellationToken) =>
+        {
+            return ValueTask.FromResult<ChatHistory>([]);
+        });
+
+        var chat = new ChatHistory(historyCache);
+        return chat;
+    }
+
+    private async Task SetChatHistoryAsync(Guid conversationId, string question, string answer)
+    {
+        var history = await GetChatHistoryAsync(conversationId);
+
+        history.AddUserMessage(question);
+        history.AddAssistantMessage(answer);
+
+        await UpdateCacheAsync(conversationId, history);
     }
 }

SqlDatabaseVectorSearch/Settings/AppSettings.cs

@@ -14,7 +14,5 @@ public class AppSettings
 
     public int MaxOutputTokens { get; init; } = 800;
 
-    public int MessageLimit { get; init; }
-
     public TimeSpan MessageExpiration { get; init; }
 }

SqlDatabaseVectorSearch/SqlDatabaseVectorSearch.csproj

@@ -1,10 +1,10 @@
 <Project Sdk="Microsoft.NET.Sdk.Web">
 
 	<PropertyGroup>
-		<TargetFramework>net9.0</TargetFramework>
+        <TargetFramework>net9.0</TargetFramework>
-		<ImplicitUsings>enable</ImplicitUsings>
+        <ImplicitUsings>enable</ImplicitUsings>
         <Nullable>enable</Nullable>
-        <NoWarn>$(NoWarn);SKEXP0001;SKEXP0010;SKEXP0050;</NoWarn>
+        <NoWarn>$(NoWarn);SKEXP0001;SKEXP0010;SKEXP0050;EXTEXP0018</NoWarn>
 	</PropertyGroup>
 
 	<ItemGroup>
@@ -12,15 +12,15 @@
         <PackageReference Include="EntityFrameworkCore.Exceptions.SqlServer" Version="8.1.3" />
         <PackageReference Include="Microsoft.AspNetCore.OpenApi" Version="9.0.0" />
         <PackageReference Include="Microsoft.EntityFrameworkCore.SqlServer" Version="[8.0.11,9.0.0)" />
+        <PackageReference Include="Microsoft.Extensions.Caching.Hybrid" Version="9.0.0-preview.9.24556.5" />
         <PackageReference Include="Microsoft.ML.Tokenizers" Version="1.0.0" />
         <PackageReference Include="Microsoft.ML.Tokenizers.Data.Cl100kBase" Version="1.0.0" />
         <PackageReference Include="Microsoft.ML.Tokenizers.Data.O200kBase" Version="1.0.0" />
-        <PackageReference Include="Microsoft.SemanticKernel" Version="1.31.0" />
+        <PackageReference Include="Microsoft.SemanticKernel" Version="1.32.0" />
-		<PackageReference Include="MinimalHelpers.OpenApi" Version="2.0.17" />
+        <PackageReference Include="MinimalHelpers.OpenApi" Version="2.0.17" />
-		<PackageReference Include="PdfPig" Version="0.1.9" />
+        <PackageReference Include="PdfPig" Version="0.1.9" />
-		<PackageReference Include="Swashbuckle.AspNetCore" Version="7.1.0" />
+        <PackageReference Include="Swashbuckle.AspNetCore.SwaggerUI" Version="7.1.0" />
-		<PackageReference Include="TinyHelpers.AspNetCore" Version="4.0.5" />
+        <PackageReference Include="TinyHelpers.AspNetCore" Version="4.0.5" />
-		<PackageReference Include="TinyHelpers.AspNetCore.Swashbuckle" Version="4.0.5" />
 	</ItemGroup>
 
 </Project>

SqlDatabaseVectorSearch/appsettings.json

@@ -26,7 +26,6 @@
         "MaxRelevantChunks": 10,
         "MaxInputTokens": 16385,
         "MaxOutputTokens": 800,
-        "MessageLimit": 20,
         "MessageExpiration": "00:05:00"
     },
     "Logging": {