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