wehub-resource-sync
96 lines
4.1 KiB
C#
96 lines
4.1 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.ChatCompletion;
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using Microsoft.SemanticKernel.Connectors.HuggingFace;
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namespace ChatCompletion;
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/// <summary>
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/// This example shows a way of using Hugging Face connector with HuggingFace Text Generation Inference (TGI) API.
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/// Follow steps in <see href="https://huggingface.co/docs/text-generation-inference/main/en/quicktour"/> to setup HuggingFace local Text Generation Inference HTTP server.
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/// <list type="number">
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/// <item>Install HuggingFace TGI via docker</item>
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/// <item><c>docker run -d --gpus all --shm-size 1g -p 8080:80 -v "c:\temp\huggingface:/data" ghcr.io/huggingface/text-generation-inference:latest --model-id teknium/OpenHermes-2.5-Mistral-7B</c></item>
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/// <item>Run the examples</item>
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/// </list>
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/// </summary>
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public class HuggingFace_ChatCompletionStreaming(ITestOutputHelper output) : BaseTest(output)
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{
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/// <summary>
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/// Sample showing how to use <see cref="IChatCompletionService"/> directly with a <see cref="ChatHistory"/>.
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/// </summary>
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[Fact]
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public async Task UsingServiceStreamingWithHuggingFace()
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{
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Console.WriteLine($"======== HuggingFace - Chat Completion - {nameof(UsingServiceStreamingWithHuggingFace)} ========");
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// HuggingFace local HTTP server endpoint
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var endpoint = new Uri("http://localhost:8080"); // Update the endpoint if you chose a different port. (defaults to 8080)
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var modelId = "teknium/OpenHermes-2.5-Mistral-7B"; // Update the modelId if you chose a different model.
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Kernel kernel = Kernel.CreateBuilder()
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.AddHuggingFaceChatCompletion(
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model: modelId,
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endpoint: endpoint)
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.Build();
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var chatService = kernel.GetRequiredService<IChatCompletionService>();
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Console.WriteLine("Chat content:");
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Console.WriteLine("------------------------");
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var chatHistory = new ChatHistory("You are a librarian, expert about books");
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OutputLastMessage(chatHistory);
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// First user message
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chatHistory.AddUserMessage("Hi, I'm looking for book suggestions");
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OutputLastMessage(chatHistory);
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// First assistant message
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await StreamMessageOutputAsync(chatService, chatHistory, AuthorRole.Assistant);
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// Second user message
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chatHistory.AddUserMessage("I love history and philosophy, I'd like to learn something new about Greece, any suggestion?");
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OutputLastMessage(chatHistory);
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// Second assistant message
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await StreamMessageOutputAsync(chatService, chatHistory, AuthorRole.Assistant);
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}
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/// <summary>
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/// This example shows how to setup LMStudio to use with the <see cref="Kernel"/> InvokeAsync (Non-Streaming).
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/// </summary>
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[Fact]
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public async Task UsingKernelStreamingWithHuggingFace()
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{
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Console.WriteLine($"======== HuggingFace - Chat Completion - {nameof(UsingKernelStreamingWithHuggingFace)} ========");
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var endpoint = new Uri("http://localhost:8080"); // Update the endpoint if you chose a different port. (defaults to 8080)
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var modelId = "teknium/OpenHermes-2.5-Mistral-7B"; // Update the modelId if you chose a different model.
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var kernel = Kernel.CreateBuilder()
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.AddHuggingFaceChatCompletion(
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model: modelId,
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apiKey: null,
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endpoint: endpoint)
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.Build();
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var prompt = @"Rewrite the text between triple backticks into a business mail. Use a professional tone, be clear and concise.
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Sign the mail as AI Assistant.
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Text: ```{{$input}}```";
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var mailFunction = kernel.CreateFunctionFromPrompt(prompt, new HuggingFacePromptExecutionSettings
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{
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TopP = 0.5f,
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MaxTokens = 1000,
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});
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await foreach (var word in kernel.InvokeStreamingAsync(mailFunction, new() { ["input"] = "Tell David that I'm going to finish the business plan by the end of the week." }))
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{
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Console.WriteLine(word);
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}
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}
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}
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