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microsoft--semantic-kernel/dotnet/samples/Concepts/TextGeneration/HuggingFace_TextGeneration.cs
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C#

// Copyright (c) Microsoft. All rights reserved.
using Microsoft.SemanticKernel;
using Microsoft.SemanticKernel.Connectors.HuggingFace;
using xRetry;
#pragma warning disable format // Format item can be simplified
#pragma warning disable CA1861 // Avoid constant arrays as arguments
namespace TextGeneration;
// The following example shows how to use Semantic Kernel with HuggingFace API.
public class HuggingFace_TextGeneration(ITestOutputHelper helper) : BaseTest(helper)
{
private const string DefaultModel = "HuggingFaceH4/zephyr-7b-beta";
/// <summary>
/// This example uses HuggingFace Inference API to access hosted models.
/// More information here: <see href="https://huggingface.co/inference-api"/>
/// </summary>
[Fact]
public async Task RunInferenceApiExampleAsync()
{
Console.WriteLine("\n======== HuggingFace Inference API example ========\n");
Kernel kernel = Kernel.CreateBuilder()
.AddHuggingFaceTextGeneration(
model: TestConfiguration.HuggingFace.ModelId ?? DefaultModel,
apiKey: TestConfiguration.HuggingFace.ApiKey)
.Build();
var questionAnswerFunction = kernel.CreateFunctionFromPrompt("Question: {{$input}}; Answer:");
var result = await kernel.InvokeAsync(questionAnswerFunction, new() { ["input"] = "What is New York?" });
Console.WriteLine(result.GetValue<string>());
}
/// <summary>
/// Some Hugging Face models support streaming responses, configure using the HuggingFace ModelId setting.
/// </summary>
/// <remarks>
/// Tested with HuggingFaceH4/zephyr-7b-beta model.
/// </remarks>
[RetryFact(typeof(HttpOperationException))]
public async Task RunStreamingExampleAsync()
{
string model = TestConfiguration.HuggingFace.ModelId ?? DefaultModel;
Console.WriteLine($"\n======== HuggingFace {model} streaming example ========\n");
Kernel kernel = Kernel.CreateBuilder()
.AddHuggingFaceTextGeneration(
model: model,
apiKey: TestConfiguration.HuggingFace.ApiKey)
.Build();
var settings = new HuggingFacePromptExecutionSettings { UseCache = false };
var questionAnswerFunction = kernel.CreateFunctionFromPrompt("Question: {{$input}}; Answer:", new HuggingFacePromptExecutionSettings
{
UseCache = false
});
await foreach (string text in kernel.InvokePromptStreamingAsync<string>("Question: {{$input}}; Answer:", new(settings) { ["input"] = "What is New York?" }))
{
Console.Write(text);
}
}
/// <summary>
/// This example uses HuggingFace Llama 2 model and local HTTP server from Semantic Kernel repository.
/// How to setup local HTTP server: <see href="https://github.com/microsoft/semantic-kernel/blob/main/samples/apps/hugging-face-http-server/README.md"/>.
/// <remarks>
/// Additional access is required to download Llama 2 model and run it locally.
/// How to get access:
/// 1. Visit <see href="https://ai.meta.com/resources/models-and-libraries/llama-downloads/"/> and complete request access form.
/// 2. Visit <see href="https://huggingface.co/meta-llama/Llama-2-7b-hf"/> and complete form "Access Llama 2 on Hugging Face".
/// Note: Your Hugging Face account email address MUST match the email you provide on the Meta website, or your request will not be approved.
/// </remarks>
/// </summary>
[Fact(Skip = "Requires local model or Huggingface Pro subscription")]
public async Task RunLlamaExampleAsync()
{
Console.WriteLine("\n======== HuggingFace Llama 2 example ========\n");
// HuggingFace Llama 2 model: https://huggingface.co/meta-llama/Llama-2-7b-hf
const string Model = "meta-llama/Llama-2-7b-hf";
// HuggingFace local HTTP server endpoint
// const string Endpoint = "http://localhost:5000/completions";
Kernel kernel = Kernel.CreateBuilder()
.AddHuggingFaceTextGeneration(
model: Model,
//endpoint: Endpoint,
apiKey: TestConfiguration.HuggingFace.ApiKey)
.Build();
var questionAnswerFunction = kernel.CreateFunctionFromPrompt("Question: {{$input}}; Answer:");
var result = await kernel.InvokeAsync(questionAnswerFunction, new() { ["input"] = "What is New York?" });
Console.WriteLine(result.GetValue<string>());
}
}