107 lines
4.4 KiB
C#
107 lines
4.4 KiB
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>());
|
|
}
|
|
}
|