How to add files Dynamically after creation of AzureAiAgent

[lovedeepatsgit]

I have created an AzureAiAgent and a ChatCompletionAgent. I have provided some sample files to the AzureAiAgent, and added both agents in a AgentGroupChat. My ultimate aim is to create a Ui ( Preferably using Blazor). But currently I am using hard coded file strings, so if there are any suggestions of sample how I can achieve this, are most welcomed.
Below is my Current Approach:

using Microsoft.AspNetCore.Builder;
using Microsoft.AspNetCore.Hosting;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using Microsoft.Extensions.Configuration;
using System.IO;
using System.Threading.Tasks;
using Azure.AI.Projects;
using Azure.Identity;
using Azure;
using Microsoft.SemanticKernel.Agents.AzureAI;
using Microsoft.SemanticKernel.Agents.Chat;
using Microsoft.SemanticKernel.Agents;
using Microsoft.SemanticKernel.Connectors.AzureOpenAI;
using Microsoft.SemanticKernel;
using CustomChatLogic;
using Backend.Hubs;

public class Program
{
    public static async Task Main(string[] args)
    {
        var builder = WebApplication.CreateBuilder(args);

        var connectionString = "ABC";
        AIProjectClient client = AzureAIAgent.CreateAzureAIClient(connectionString, new AzureCliCredential());

        AgentsClient agentsClient = client.GetAgentsClient();

        // List of multiple files to upload
        List<string> filePaths = new List<string>
        {
            "employees.pdf",
            "Grimms-The-King-of-the-Golden-Mountain.txt",
            "Grimms-The-Water-of-Life.txt",
            "Grimms-The-White-Snake.txt",
        };

        List<string> uploadedFileIds = new List<string>();

        // Upload multiple files
        foreach (string filePath in filePaths)
        {
            Response<AgentFile> uploadAgentFileResponse = await agentsClient.UploadFileAsync(
                filePath: filePath,
                purpose: AgentFilePurpose.Agents);

            uploadedFileIds.Add(uploadAgentFileResponse.Value.Id);
        }

        // Create a vector store with the file and wait for it to be processed.
        // If you do not specify a vector store, create_message will create a vector store with a default expiration policy of seven days after they were last active
        VectorStore vectorStore = await agentsClient.CreateVectorStoreAsync(
            fileIds: uploadedFileIds,
            name: "my_vector_store",
            expiresAfter: new VectorStoreExpirationPolicy(VectorStoreExpirationPolicyAnchor.LastActiveAt, 1));

        // Define an agent on the Azure AI agent service
        Azure.AI.Projects.Agent definition = await agentsClient.CreateAgentAsync(
            model: "gpt-4o-2",
            name: "FileExplorerAgent",
            description: "Agent Used to Answer User Queries.",
            instructions: "You are helpful AI Assistant Agent",
            tools: [new FileSearchToolDefinition()],
            toolResources:
                        new()
                        {
                            FileSearch = new()
                            {
                                VectorStoreIds = { vectorStore.Id },
                            }
                        });

        AzureAIAgent FileExplorerAgent = new(definition, agentsClient);

        var configuration = new ConfigurationBuilder()
           .SetBasePath(Directory.GetCurrentDirectory())
           .AddJsonFile("appsettings.json", optional: false, reloadOnChange: true)
           .AddJsonFile($"appsettings.{Environment.GetEnvironmentVariable("ASPNETCORE_ENVIRONMENT")}.json", optional: true)
           .Build();

        string AZURE_OPEN_AI_ENDPOINT = configuration["LlmModels:AiFoundryEndpoint"]!;
        string AZURE_OPEN_AI_KEY = configuration["LlmModels:AiFoundryApiKey"]!;
        string DEPLOYMENT_MODEL = configuration["LlmModels:GPT-4o-2"]!;

        Console.WriteLine("Creating kernel...");

        IKernelBuilder kernelbuilder = Kernel.CreateBuilder();

        kernelbuilder.AddAzureOpenAIChatCompletion(DEPLOYMENT_MODEL!, AZURE_OPEN_AI_ENDPOINT!, AZURE_OPEN_AI_KEY!);

        Kernel kernel = kernelbuilder.Build();


        Console.WriteLine("Defining agents...");

        const string FileExplorerAgentName = "FileExplorerAgent";
        const string ReviewerName = "Reviewer";

        ChatCompletionAgent agentReviewer =
            new()
            {
                Name = ReviewerName,
                Instructions =
                    """
                    You are an AI assistant that help other, and Also check the mistake in queries.
                    """,
                Kernel = kernel,
                Arguments = new KernelArguments(new AzureOpenAIPromptExecutionSettings() { FunctionChoiceBehavior = FunctionChoiceBehavior.Auto() })
            };

        KernelFunction selectionFunction =
            AgentGroupChat.CreatePromptFunctionForStrategy(
                $$$"""
                Examine the provided RESPONSE and choose the next participant.
                State only the name of the chosen participant without explanation.
                Never choose the participant named in the RESPONSE.

                Choose only from these participants:
                - {{{ReviewerName}}}
                - {{{FileExplorerAgentName}}}

                Always follow these rules when choosing the next participant:
                - If RESPONSE is by {{{ReviewerName}}}, it is {{{FileExplorerAgentName}}}'s turn.
                - If RESPONSE is by {{{FileExplorerAgentName}}}, it is {{{ReviewerName}}}'s turn.

                RESPONSE:
                {{$history}}
                """,
                safeParameterNames: "history");

        const string TerminationToken = "yes";

        KernelFunction terminationFunction =
            AgentGroupChat.CreatePromptFunctionForStrategy(
                $$$"""
                Examine the RESPONSE and determine whether the content has been deemed satisfactory.
                If content is satisfactory and both agents have replied, respond with a single word without explanation: {{{TerminationToken}}}.
                If specific suggestions are being provided, it is not satisfactory.
                If no correction is suggested, it is satisfactory.

                RESPONSE:
                {{$history}}
                """,
                safeParameterNames: "history");


        AgentGroupChat chat =
            new(agentReviewer, FileExplorerAgent)
            {
                ExecutionSettings = new AgentGroupChatSettings
                {
                    SelectionStrategy =
                        new KernelFunctionSelectionStrategy(selectionFunction, kernel)
                        {
                            // Always start with the editor agent.
                            InitialAgent = FileExplorerAgent,
                            // The prompt variable name for the history argument.
                            HistoryVariableName = "history",
                            // Returns the entire result value as a string.
                            ResultParser = (result) => result.GetValue<string>() ?? agentReviewer.Name
                        },
                    TerminationStrategy =
                        new KernelFunctionTerminationStrategy(terminationFunction, kernel)
                        {
                            // Only evaluate for editor's response
                            Agents = [agentReviewer],
                            // The prompt variable name for the history argument.
                            HistoryVariableName = "history",
                            // Limit total number of turns
                            MaximumIterations = 3,
                            // Customer result parser to determine if the response is "yes"
                            ResultParser = (result) => result.GetValue<string>()?.Contains(TerminationToken, StringComparison.OrdinalIgnoreCase) ?? false
                        }
                }
            };

        Console.WriteLine("Ready!");

        // Register Dependencies
        builder.Services.AddSingleton(kernel);
        builder.Services.AddSingleton(chat);
        builder.Services.AddSingleton(new ChatLogic(chat));
        builder.Services.AddCors(options =>
        {
            options.AddPolicy("AllowBlazorUI",
                builder =>
                {
                    builder.WithOrigins("http://localhost:7096",
                        "http://localhost:7230", "http://localhost:5027")
                           .AllowAnyHeader()
                           .AllowAnyMethod()
                           .AllowCredentials();
                });
        });

        builder.Services.AddRazorPages();
        builder.Services.AddSignalR();

        var app = builder.Build();

        app.UseCors("AllowBlazorUI");

        app.UseRouting();
        app.UseAuthorization();
        app.MapRazorPages();
        app.MapHub<ChatHub>("/chatHub");

        await app.RunAsync();
    }
}

[sophialagerkranspandey]

There is a specific client for file uploads. I'm tagging @crickman to dive into this further. Thanks!

[crickman]

Since you are referencing a vector-store, you may add the file to that store in the same manner you uploaded the initial files.

You you desire to switch from the initial vector-store to a different one, this can be done during thread creation.