chore: import upstream snapshot with attribution

dotnet/samples/Demos/VectorStoreRAG/RAGChatService.cs

@@ -0,0 +1,187 @@
+// Copyright (c) Microsoft. All rights reserved.
+
+using Microsoft.Extensions.DependencyInjection;
+using Microsoft.Extensions.Hosting;
+using Microsoft.Extensions.Options;
+using Microsoft.SemanticKernel;
+using Microsoft.SemanticKernel.Data;
+using Microsoft.SemanticKernel.PromptTemplates.Handlebars;
+using VectorStoreRAG.Options;
+
+namespace VectorStoreRAG;
+
+/// <summary>
+/// Main service class for the application.
+/// </summary>
+/// <typeparam name="TKey">The type of the data model key.</typeparam>
+/// <param name="dataLoader">Used to load data into the vector store.</param>
+/// <param name="vectorStoreTextSearch">Used to search the vector store.</param>
+/// <param name="kernel">Used to make requests to the LLM.</param>
+/// <param name="ragConfigOptions">The configuration options for the application.</param>
+/// <param name="appShutdownCancellationTokenSource">Used to gracefully shut down the entire application when cancelled.</param>
+internal sealed class RAGChatService<TKey>(
+    IDataLoader dataLoader,
+    VectorStoreTextSearch<TextSnippet<TKey>> vectorStoreTextSearch,
+    Kernel kernel,
+    IOptions<RagConfig> ragConfigOptions,
+    [FromKeyedServices("AppShutdown")] CancellationTokenSource appShutdownCancellationTokenSource) : IHostedService
+{
+    private Task? _dataLoaded;
+    private Task? _chatLoop;
+
+    /// <summary>
+    /// Start the service.
+    /// </summary>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests.</param>
+    /// <returns>An async task that completes when the service is started.</returns>
+    public Task StartAsync(CancellationToken cancellationToken)
+    {
+        // Start to load all the configured PDFs into the vector store.
+        if (ragConfigOptions.Value.BuildCollection)
+        {
+            this._dataLoaded = this.LoadDataAsync(cancellationToken);
+        }
+        else
+        {
+            this._dataLoaded = Task.CompletedTask;
+        }
+
+        // Start the chat loop.
+        this._chatLoop = this.ChatLoopAsync(cancellationToken);
+
+        return Task.CompletedTask;
+    }
+
+    /// <summary>
+    /// Stop the service.
+    /// </summary>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests.</param>
+    /// <returns>An async task that completes when the service is stopped.</returns>
+    public Task StopAsync(CancellationToken cancellationToken)
+    {
+        return Task.CompletedTask;
+    }
+
+    /// <summary>
+    /// Contains the main chat loop for the application.
+    /// </summary>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests.</param>
+    /// <returns>An async task that completes when the chat loop is shut down.</returns>
+    private async Task ChatLoopAsync(CancellationToken cancellationToken)
+    {
+        var pdfFiles = string.Join(", ", ragConfigOptions.Value.PdfFilePaths ?? []);
+
+        // Wait for the data to be loaded before starting the chat loop.
+        while (this._dataLoaded != null && !this._dataLoaded.IsCompleted && !cancellationToken.IsCancellationRequested)
+        {
+            await Task.Delay(1_000, cancellationToken).ConfigureAwait(false);
+        }
+
+        // If data loading failed, don't start the chat loop.
+        if (this._dataLoaded != null && this._dataLoaded.IsFaulted)
+        {
+            Console.WriteLine("Failed to load data");
+            return;
+        }
+
+        Console.WriteLine("PDF loading complete\n");
+
+        Console.ForegroundColor = ConsoleColor.Green;
+        Console.WriteLine("Assistant > Press enter with no prompt to exit.");
+
+        // Add a search plugin to the kernel which we will use in the template below
+        // to do a vector search for related information to the user query.
+        kernel.Plugins.Add(vectorStoreTextSearch.CreateWithGetTextSearchResults("SearchPlugin"));
+
+        // Start the chat loop.
+        while (!cancellationToken.IsCancellationRequested)
+        {
+            // Prompt the user for a question.
+            Console.ForegroundColor = ConsoleColor.Green;
+            Console.WriteLine($"Assistant > What would you like to know from the loaded PDFs: ({pdfFiles})?");
+
+            // Read the user question.
+            Console.ForegroundColor = ConsoleColor.White;
+            Console.Write("User > ");
+            var question = Console.ReadLine();
+
+            // Exit the application if the user didn't type anything.
+            if (string.IsNullOrWhiteSpace(question))
+            {
+                appShutdownCancellationTokenSource.Cancel();
+                break;
+            }
+
+            // Invoke the LLM with a template that uses the search plugin to
+            // 1. get related information to the user query from the vector store
+            // 2. add the information to the LLM prompt.
+            var response = kernel.InvokePromptStreamingAsync(
+                promptTemplate: """
+                    Please use this information to answer the question:
+                    {{#with (SearchPlugin-GetTextSearchResults question)}}  
+                      {{#each this}}  
+                        Name: {{Name}}
+                        Value: {{Value}}
+                        Link: {{Link}}
+                        -----------------
+                      {{/each}}
+                    {{/with}}
+
+                    Include citations to the relevant information where it is referenced in the response.
+                    
+                    Question: {{question}}
+                    """,
+                arguments: new KernelArguments()
+                {
+                    { "question", question },
+                },
+                templateFormat: "handlebars",
+                promptTemplateFactory: new HandlebarsPromptTemplateFactory(),
+                cancellationToken: cancellationToken);
+
+            // Stream the LLM response to the console with error handling.
+            Console.ForegroundColor = ConsoleColor.Green;
+            Console.Write("\nAssistant > ");
+
+            try
+            {
+                await foreach (var message in response.ConfigureAwait(false))
+                {
+                    Console.Write(message);
+                }
+                Console.WriteLine();
+            }
+            catch (Exception ex)
+            {
+                Console.ForegroundColor = ConsoleColor.Red;
+                Console.WriteLine($"Call to LLM failed with error: {ex}");
+            }
+        }
+    }
+
+    /// <summary>
+    /// Load all configured PDFs into the vector store.
+    /// </summary>
+    /// <param name="cancellationToken">The <see cref="CancellationToken"/> to monitor for cancellation requests.</param>
+    /// <returns>An async task that completes when the loading is complete.</returns>
+    private async Task LoadDataAsync(CancellationToken cancellationToken)
+    {
+        try
+        {
+            foreach (var pdfFilePath in ragConfigOptions.Value.PdfFilePaths ?? [])
+            {
+                Console.WriteLine($"Loading PDF into vector store: {pdfFilePath}");
+                await dataLoader.LoadPdf(
+                    pdfFilePath,
+                    ragConfigOptions.Value.DataLoadingBatchSize,
+                    ragConfigOptions.Value.DataLoadingBetweenBatchDelayInMilliseconds,
+                    cancellationToken).ConfigureAwait(false);
+            }
+        }
+        catch (Exception ex)
+        {
+            Console.WriteLine($"Failed to load PDFs: {ex}");
+            throw;
+        }
+    }
+}