// Copyright (c) Microsoft. All rights reserved.
using Microsoft.Extensions.Configuration;
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.ChatCompletion;
using Microsoft.SemanticKernel.Connectors.Onnx;
namespace SemanticKernel.AotCompatibility;
///
/// This class contains samples of how to use ONNX chat completion service in AOT applications.
///
internal static class OnnxChatCompletionSamples
{
///
/// Sends a prompt to the ONNX model and gets the chat message content.
///
public static async Task GetChatMessageContent(IConfigurationRoot config)
{
string chatModelPath = config["Onnx:ModelPath"]!;
string chatModelId = config["Onnx:ModelId"] ?? "phi-3";
// Create kernel builder and add OnnxRuntimeGenAIChatCompletion service.
// If you plan to use the service with Non-ONNX prompt execution settings,
// supply JSON serializer options with a JSON serializer context for this setup.
IKernelBuilder builder = Kernel.CreateBuilder()
.AddOnnxRuntimeGenAIChatCompletion(chatModelId, chatModelPath);
// Build kernel and get the service instance
Kernel kernel = builder.Build();
IChatCompletionService chatService = kernel.GetRequiredService();
string prompt = "Hello, what is the weather in Boston, USA now?";
OnnxRuntimeGenAIPromptExecutionSettings executionSettings = new()
{
Temperature = 0.7f, // Adjusts creativity level
TopP = 0.9f // Limits token choice diversity
};
// Prompt the ONNX model
ChatMessageContent messageContent = await chatService.GetChatMessageContentAsync(prompt, executionSettings);
// Display the result
Console.WriteLine(messageContent);
}
///
/// Sends a prompt to the ONNX model and gets the chat message content in a streaming fashion.
///
public static async Task GetStreamingChatMessageContents(IConfigurationRoot config)
{
string chatModelPath = config["Onnx:ModelPath"]!;
string chatModelId = config["Onnx:ModelId"] ?? "phi-3";
// Create kernel builder and add OnnxRuntimeGenAIChatCompletion service.
// If you plan to use the service with Non-ONNX prompt execution settings,
// supply JSON serializer options with a JSON serializer context for this setup.
IKernelBuilder builder = Kernel.CreateBuilder()
.AddOnnxRuntimeGenAIChatCompletion(chatModelId, chatModelPath);
// Build kernel and get the service instance
Kernel kernel = builder.Build();
IChatCompletionService chatService = kernel.GetRequiredService();
string prompt = "Hello, what is the weather in Boston, USA now?";
OnnxRuntimeGenAIPromptExecutionSettings executionSettings = new()
{
Temperature = 0.7f, // Adjusts creativity level
TopP = 0.9f // Limits token choice diversity
};
// Prompt the ONNX model
await foreach (StreamingChatMessageContent messageContent in chatService.GetStreamingChatMessageContentsAsync(prompt, executionSettings))
{
// Display the result
Console.WriteLine(messageContent);
}
}
}