10000 [GenAI] Introduce CausalLMPipelineChatClient for MEAI.IChatClient (#7… · dotnet/machinelearning@3659a48 · GitHub
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[GenAI] Introduce CausalLMPipelineChatClient for MEAI.IChatClient (#7270)
* leverage MEAI abstraction * Update src/Microsoft.ML.GenAI.LLaMA/Llama3CausalLMChatClient.cs Co-authored-by: Stephen Toub <stoub@microsoft.com> * Update src/Microsoft.ML.GenAI.LLaMA/Llama3CausalLMChatClient.cs Co-authored-by: Stephen Toub <stoub@microsoft.com> * Update src/Microsoft.ML.GenAI.Phi/Phi3/Phi3CausalLMChatClient.cs Co-authored-by: Stephen Toub <stoub@microsoft.com> * fix comments * Update Microsoft.ML.GenAI.Core.csproj --------- Co-authored-by: Stephen Toub <stoub@microsoft.com>
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‎docs/samples/Microsoft.ML.GenAI.Samples/MEAI/Llama3_1.cs

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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Text.Json;
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using System.Threading.Tasks;
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using AutoGen.Core;
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using Microsoft.Extensions.AI;
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using Microsoft.ML.GenAI.Core;
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using Microsoft.ML.GenAI.Core.Extension;
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using Microsoft.ML.GenAI.LLaMA;
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using Microsoft.ML.Tokenizers;
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using TorchSharp;
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using static TorchSharp.torch;
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namespace Microsoft.ML.GenAI.Samples.MEAI;
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internal class Llama3_1
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{
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public static async Task RunAsync(string weightFolder, string checkPointName = "model.safetensors.index.json")
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{
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var device = "cuda";
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if (device == "cuda")
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{
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torch.InitializeDeviceType(DeviceType.CUDA);
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}
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var defaultType = ScalarType.BFloat16;
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torch.manual_seed(1);
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torch.set_default_dtype(defaultType);
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var configName = "config.json";
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var originalWeightFolder = Path.Combine(weightFolder, "original");
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Console.WriteLine("Loading Llama from huggingface model weight folder");
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var stopWatch = System.Diagnostics.Stopwatch.StartNew();
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stopWatch.Start();
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var tokenizer = LlamaTokenizerHelper.FromPretrained(originalWeightFolder);
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var model = LlamaForCausalLM.FromPretrained(weightFolder, configName, checkPointName: checkPointName, layersOnTargetDevice: 26, quantizeToInt8: true);
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var pipeline = new CausalLMPipeline<TiktokenTokenizer, LlamaForCausalLM>(tokenizer, model, device);
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var client = new Llama3CausalLMChatClient(pipeline);
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var task = """
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Write a C# program to print the sum of two numbers. Use top-level statement, put code between ```csharp and ```.
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""";
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var chatMessage = new ChatMessage(ChatRole.User, task);
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await foreach (var response in client.CompleteStreamingAsync([chatMessage]))
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{
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Console.Write(response.Text);
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}
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}
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}

‎docs/samples/Microsoft.ML.GenAI.Samples/MEAI/Phi3.cs

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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text;
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using System.Threading.Tasks;
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using static TorchSharp.torch;
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using TorchSharp;
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using Microsoft.ML.GenAI.Phi;
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using Microsoft.ML.GenAI.Core;
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using Microsoft.ML.Tokenizers;
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using Microsoft.Extensions.AI;
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namespace Microsoft.ML.GenAI.Samples.MEAI;
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internal class Phi3
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{
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public static async Task RunAsync(string weightFolder)
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{
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var device = "cuda";
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if (device == "cuda")
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{
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torch.InitializeDeviceType(DeviceType.CUDA);
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}
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var defaultType = ScalarType.Float16;
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torch.manual_seed(1);
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torch.set_default_dtype(defaultType);
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var tokenizerPath = Path.Combine(weightFolder, "tokenizer.model");
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var tokenizer = Phi3TokenizerHelper.FromPretrained(tokenizerPath);
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var model = Phi3ForCasualLM.FromPretrained(weightFolder, "config.json", layersOnTargetDevice: -1, quantizeToInt8: true);
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var pipeline = new CausalLMPipeline<LlamaTokenizer, Phi3ForCasualLM>(tokenizer, model, device);
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var client = new Phi3CausalLMChatClient(pipeline);
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var task = """
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Write a C# program to print the sum of two numbers. Use top-level statement, put code between ```csharp and ```.
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""";
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var chatMessage = new ChatMessage(ChatRole.User, task);
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await foreach (var response in client.CompleteStreamingAsync([chatMessage]))
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{
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Console.Write(response.Text);
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}
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}
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}

‎docs/samples/Microsoft.ML.GenAI.Samples/Program.cs

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// See https://aka.ms/new-console-template for more information
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using Microsoft.ML.GenAI.Samples.Llama;
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using Microsoft. E377 ML.GenAI.Samples.MEAI;
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await LlamaSample.RunLlama(@"C:\Users\xiaoyuz\source\repos\Llama-3.2-3B-Instruct");
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//await Llama3_1.RunAsync(@"C:\Users\xiaoyuz\source\repos\Llama-3.2-1B-Instruct", checkPointName: "model.safetensors");
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await Phi3.RunAsync(@"C:\Users\xiaoyuz\source\repos\Phi-3-mini-4k-instruct");

‎eng/Versions.props

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<SystemRuntimeCompilerServicesUnsafeVersion>6.0.0</SystemRuntimeCompilerServicesUnsafeVersion>
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<SystemSecurityPrincipalWindows>5.0.0</SystemSecurityPrincipalWindows>
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<SystemTextEncodingsWebVersion>8.0.0</SystemTextEncodingsWebVersion>
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<SystemTextJsonVersion>8.0.4</SystemTextJsonVersion>
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<SystemTextJsonVersion>8.0.5</SystemTextJsonVersion>
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<SystemThreadingChannelsVersion>8.0.0</SystemThreadingChannelsVersion>
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<!-- Other product dependencies -->
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<ApacheArrowVersion>14.0.2</ApacheArrowVersion>
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<MicrosoftDotNetInteractiveVersion>1.0.0-beta.24375.2</MicrosoftDotNetInteractiveVersion>
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<MicrosoftMLOnnxRuntimeVersion>1.18.1</MicrosoftMLOnnxRuntimeVersion>
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<MlNetMklDepsVersion>0.0.0.12</MlNetMklDepsVersion>
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<MicrosoftExtensionsAIVersion>9.0.0-preview.9.24507.7</MicrosoftExtensionsAIVersion>
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<!--
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@("inteltbb.devel", "win", "2021.7.1.15305")
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-->

‎src/Microsoft.ML.GenAI.Core/CausalLMPipelineChatClient.cs

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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Runtime.CompilerServices;
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using System.Threading;
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using System.Threading.Tasks;
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using Microsoft.Extensions.AI;
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using Microsoft.ML.Tokenizers;
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using static TorchSharp.torch;
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namespace Microsoft.ML.GenAI.Core;
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public abstract class CausalLMPipelineChatClient<TTokenizer, TCausalLMModel> : IChatClient
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where TTokenizer : Tokenizer
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where TCausalLMModel : nn.Module<CausalLMModelInput, CausalLMModelOutput>
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{
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private readonly ICausalLMPipeline<TTokenizer, TCausalLMModel> _pipeline;
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private readonly IMEAIChatTemplateBuilder _chatTemplateBuilder;
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public CausalLMPipelineChatClient(
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ICausalLMPipeline<TTokenizer, TCausalLMModel> pipeline,
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IMEAIChatTemplateBuilder chatTemplateBuilder,
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ChatClientMetadata? metadata = null)
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{
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var classNameWithType = $"{nameof(CausalLMPipelineChatClient<TTokenizer, TCausalLMModel>)}<{typeof(TTokenizer).Name}, {typeof(TCausalLMModel).Name}>";
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Metadata ??= new ChatClientMetadata(providerName: classNameWithType, modelId: typeof(TCausalLMModel).Name);
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_chatTemplateBuilder = chatTemplateBuilder;
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_pipeline = pipeline;
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}
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public ChatClientMetadata Metadata { get; }
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public virtual Task<ChatCompletion> CompleteAsync(IList<ChatMessage> chatMessages, ChatOptions? options = null, CancellationToken cancellationToken = default)
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{
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var prompt = _chatTemplateBuilder.BuildPrompt(chatMessages, options);
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var stopSequences = options?.StopSequences ?? Array.Empty<string>();
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var output = _pipeline.Generate(
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prompt,
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maxLen: options?.MaxOutputTokens ?? 1024,
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temperature: options?.Temperature ?? 0.7f,
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stopSequences: stopSequences.ToArray()) ?? throw new InvalidOperationException("Failed to generate a reply.");
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var chatMessage = new ChatMessage(ChatRole.Assistant, output);
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return Task.FromResult(new ChatCompletion([chatMessage])
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{
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CreatedAt = DateTime.UtcNow,
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FinishReason = ChatFinishReason.Stop,
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});
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}
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#pragma warning disable CS1998 // Async method lacks 'await' operators and will run synchronously
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public virtual async IAsyncEnumerable<StreamingChatCompletionUpdate> CompleteStreamingAsync(
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#pragma warning restore CS1998 // Async method lacks 'await' operators and will run synchronously
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IList<ChatMessage> chatMessages,
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ChatOptions? options = null,
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[EnumeratorCancellation] CancellationToken cancellationToken = default)
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{
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var prompt = _chatTemplateBuilder.BuildPrompt(chatMessages, options);
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var stopSequences = options?.StopSequences ?? Array.Empty<string>();
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foreach (var output in _pipeline.GenerateStreaming(
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prompt,
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maxLen: options?.MaxOutputTokens ?? 1024,
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temperature: options?.Temperature ?? 0.7f,
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stopSequences: stopSequences.ToArray()))
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{
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yield return new StreamingChatCompletionUpdate
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{
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Role = ChatRole.Assistant,
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Text = output,
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CreatedAt = DateTime.UtcNow,
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};
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}
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}
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public virtual void Dispose()
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{
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}
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public virtual TService? GetService<TService>(object? key = null) where TService : class
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{
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return null;
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}
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}

‎src/Microsoft.ML.GenAI.Core/Microsoft.ML.GenAI.Core.csproj

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<ItemGroup>
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<PackageReference Include="AutoGen.Core" Version="$(AutoGenVersion)" />
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<PackageReference Include="Microsoft.Extensions.AI.Abstractions" Version="$(MicrosoftExtensionsAIVersion)" />
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<PackageReference Include="Microsoft.SemanticKernel.Abstractions" Version="$(SemanticKernelVersion)" />
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<PackageReference Include="System.Memory" Version="$(SystemMemoryVersion)" />
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<PackageReference Include="TorchSharp" Version="$(TorchSharpVersion)" />

‎src/Microsoft.ML.GenAI.Core/Utility/IChatTemplateBuilder.cs

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using System.Text;
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using System.Threading.Tasks;
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using AutoGen.Core;
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using Microsoft.Extensions.AI;
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using Microsoft.SemanticKernel.ChatCompletion;
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namespace Microsoft.ML.GenAI.Core;
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string BuildPrompt(IEnumerable<IMessage> messages, IEnumerable<FunctionContract>? tools = null);
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}
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public interface IMEAIChatTemplateBuilder
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{
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string BuildPrompt(IList<ChatMessage> messages, ChatOptions? options = null);
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}
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public interface IChatTemplateBuilder : IAutoGenChatTemplateBuilder, ISemanticKernelChatTemplateBuilder
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{
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}

‎src/Microsoft.ML.GenAI.LLaMA/Llama3CausalLMChatClient.cs

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// Licensed to the .NET Foundation under one or more agreements.
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// The .NET Foundation licenses this file to you under the MIT license.
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// See the LICENSE file in the project root for more information.
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using System.Runtime.CompilerServices;
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using Microsoft.Extensions.AI;
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using Microsoft.ML.GenAI.Core;
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using Microsoft.ML.Tokenizers;
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namespace Microsoft.ML.GenAI.LLaMA;
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public class Llama3CausalLMChatClient : CausalLMPipelineChatClient<Tokenizer, LlamaForCausalLM>
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{
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private readonly string _eotToken = "<|eot_id|>";
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public Llama3CausalLMChatClient(
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ICausalLMPipeline<Tokenizer, LlamaForCausalLM> pipeline,
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IMEAIChatTemplateBuilder? chatTemplateBuilder = null,
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ChatClientMetadata? metadata = null)
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: base(
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pipeline,
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chatTemplateBuilder ?? Llama3_1ChatTemplateBuilder.Instance,
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metadata ?? new ChatClientMetadata(modelId: nameof(Llama3CausalLMChatClient)))
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{
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}
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public override Task<ChatCompletion> CompleteAsync(
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IList<ChatMessage> chatMessages,
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ChatOptions? options = null,
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CancellationToken cancellationToken = default)
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{
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options ??= new ChatOptions();
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if (options.StopSequences != null)
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{
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options.StopSequences.Add(_eotToken);
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}
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else
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{
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options.StopSequences = new List<string> { _eotToken };
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}
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return base.CompleteAsync(chatMessages, options, cancellationToken);
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}
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public override IAsyncEnumerable<StreamingChatCompletionUpdate> CompleteStreamingAsync(
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IList<ChatMessage> chatMessages,
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ChatOptions? options = null,
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CancellationToken cancellationToken = default)
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{
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options ??= new ChatOptions();
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options.StopSequences ??= [];
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options.StopSequences.Add(_eotToken);
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return base.CompleteStreamingAsync(chatMessages, options, cancellationToken);
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}
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}

‎src/Microsoft.ML.GenAI.LLaMA/Llama3_1ChatTemplateBuilder.cs

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using System.Text;
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using AutoGen.Core;
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using Microsoft.Extensions.AI;
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using Microsoft.ML.GenAI.Core;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.ChatCompletion;
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using TextContent = Microsoft.SemanticKernel.TextContent;
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namespace Microsoft.ML.GenAI.LLaMA;
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#pragma warning disable MSML_GeneralName // This name should be PascalCased
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public class Llama3_1ChatTemplateBuilder : IChatTemplateBuilder
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public class Llama3_1ChatTemplateBuilder : IChatTemplateBuilder, IMEAIChatTemplateBuilder
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#pragma warning restore MSML_GeneralName // This name should be PascalCased
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{
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private const char Newline = '\n';
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return sb.ToString();
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}
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public string BuildPrompt(IList<ChatMessage> messages, ChatOptions? options = null)
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{
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var availableRoles = new[] { ChatRole.System, ChatRole.User, ChatRole.Assistant };
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if (messages.Any(m => m.Text is null))
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{
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throw new InvalidOperationException("Please provide a message with content.");
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}
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if (messages.Any(m => availableRoles.Any(availableRole => availableRole == m.Role) == false))
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{
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throw new InvalidOperationException("Please provide a message with a valid role. The valid roles are System, User, and Assistant.");
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}
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var sb = new StringBuilder();
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sb.Append("<|begin_of_text|>");
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foreach (var message in messages)
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{
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var role = message.Role.Value;
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var content = message.Text!;
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sb.Append(message switch
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{
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_ when message.Role == ChatRole.System => $"<|start_header_id|>system<|end_header_id|>{Newline}{content.Trim()}<|eot_id|>{Newline}",
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_ when message.Role == ChatRole.User => $"<|start_header_id|>user<|end_header_id|>{Newline}{content.Trim()}<|eot_id|>{Newline}",
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_ when message.Role == ChatRole.Assistant => $"<|start_header_id|>assistant<|end_header_id|>{Newline}{content.Trim()}<|eot_id|>{Newline}",
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_ => throw new InvalidOperationException("Invalid role.")
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});
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}
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sb.Append($"<|start_header_id|>assistant<|end_header_id|>{Newline}");
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var input = sb.ToString();
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return input;
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}
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public static Llama3_1ChatTemplateBuilder Instance { get; } = new Llama3_1ChatTemplateBuilder();
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}

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