如何让其他模型也能在SemanticKernel中调用本地函数

// Import packages
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel.Connectors.OpenAI;
// Create a kernel with Azure OpenAI chat completion
var builder = Kernel.CreateBuilder().AddAzureOpenAIChatCompletion(modelId, endpoint, apiKey);
// Add enterprise components
builder.Services.AddLogging(services => services.AddConsole().SetMinimumLevel(LogLevel.Trace));
// Build the kernel
Kernel kernel = builder.Build();
var chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
// Add a plugin (the LightsPlugin class is defined below)
kernel.Plugins.AddFromType<LightsPlugin>("Lights");
// Enable planning
OpenAIPromptExecutionSettings openAIPromptExecutionSettings = new() 
{
    ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions
};
// Create a history store the conversation
var history = new ChatHistory();
// Initiate a back-and-forth chat
string? userInput;
do {
    // Collect user input
    Console.Write("User > ");
    userInput = Console.ReadLine();
    // Add user input
    history.AddUserMessage(userInput);
    // Get the response from the AI
    var result = await chatCompletionService.GetChatMessageContentAsync(
        history,
        executionSettings: openAIPromptExecutionSettings,
        kernel: kernel);
    // Print the results
    Console.WriteLine("Assistant > " + result);
    // Add the message from the agent to the chat history
    history.AddMessage(result.Role, result.Content ?? string.Empty);
} while (userInput is not null)

// Enable planning
OpenAIPromptExecutionSettings openAIPromptExecutionSettings = new() 
{
    ToolCallBehavior = ToolCallBehavior.AutoInvokeKernelFunctions
};

var handler = new OpenAIHttpClientHandler();
 var builder = Kernel.CreateBuilder()
 .AddOpenAIChatCompletion(
    modelId: "",
    apiKey: "",
    httpClient: new HttpClient(handler));
 _kernel = builder.Build();          
 _kernel.ImportPluginFromType<TimePlugin>("Time");
 _kernel.ImportPluginFromType<MathPlugin>("Math");

UniversalLLMFunctionCaller planner = new(_kernel);
   string ask = "What is the current hour number, plus 6?";
   Debug.WriteLine(ask);
   string result = await planner.RunAsync("What is the current hour number, plus 6?");
   Debug.WriteLine(result);