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[GenAI] Introduce CausalLMPipelineChatClient for MEAI.IChatClient (do…
…tnet#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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using System; | ||
using System.Collections.Generic; | ||
using System.Linq; | ||
using System.Text; | ||
using System.Text.Json; | ||
using System.Threading.Tasks; | ||
using AutoGen.Core; | ||
using Microsoft.Extensions.AI; | ||
using Microsoft.ML.GenAI.Core; | ||
using Microsoft.ML.GenAI.Core.Extension; | ||
using Microsoft.ML.GenAI.LLaMA; | ||
using Microsoft.ML.Tokenizers; | ||
using TorchSharp; | ||
using static TorchSharp.torch; | ||
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namespace Microsoft.ML.GenAI.Samples.MEAI; | ||
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internal class Llama3_1 | ||
{ | ||
public static async Task RunAsync(string weightFolder, string checkPointName = "model.safetensors.index.json") | ||
{ | ||
var device = "cuda"; | ||
if (device == "cuda") | ||
{ | ||
torch.InitializeDeviceType(DeviceType.CUDA); | ||
} | ||
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var defaultType = ScalarType.BFloat16; | ||
torch.manual_seed(1); | ||
torch.set_default_dtype(defaultType); | ||
var configName = "config.json"; | ||
var originalWeightFolder = Path.Combine(weightFolder, "original"); | ||
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Console.WriteLine("Loading Llama from huggingface model weight folder"); | ||
var stopWatch = System.Diagnostics.Stopwatch.StartNew(); | ||
stopWatch.Start(); | ||
var tokenizer = LlamaTokenizerHelper.FromPretrained(originalWeightFolder); | ||
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 = """ | ||
Write a C# program to print the sum of two numbers. Use top-level statement, put code between ```csharp and ```. | ||
"""; | ||
var chatMessage = new ChatMessage(ChatRole.User, task); | ||
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await foreach (var response in client.CompleteStreamingAsync([chatMessage])) | ||
{ | ||
Console.Write(response.Text); | ||
} | ||
} | ||
} |
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using System; | ||
using System.Collections.Generic; | ||
using System.Linq; | ||
using System.Text; | ||
using System.Threading.Tasks; | ||
using static TorchSharp.torch; | ||
using TorchSharp; | ||
using Microsoft.ML.GenAI.Phi; | ||
using Microsoft.ML.GenAI.Core; | ||
using Microsoft.ML.Tokenizers; | ||
using Microsoft.Extensions.AI; | ||
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namespace Microsoft.ML.GenAI.Samples.MEAI; | ||
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internal class Phi3 | ||
{ | ||
public static async Task RunAsync(string weightFolder) | ||
{ | ||
var device = "cuda"; | ||
if (device == "cuda") | ||
{ | ||
torch.InitializeDeviceType(DeviceType.CUDA); | ||
} | ||
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var defaultType = ScalarType.Float16; | ||
torch.manual_seed(1); | ||
torch.set_default_dtype(defaultType); | ||
var tokenizerPath = Path.Combine(weightFolder, "tokenizer.model"); | ||
var tokenizer = Phi3TokenizerHelper.FromPretrained(tokenizerPath); | ||
var model = Phi3ForCasualLM.FromPretrained(weightFolder, "config.json", layersOnTargetDevice: -1, quantizeToInt8: true); | ||
var pipeline = new CausalLMPipeline<LlamaTokenizer, Phi3ForCasualLM>(tokenizer, model, device); | ||
var client = new Phi3CausalLMChatClient(pipeline); | ||
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var task = """ | ||
Write a C# program to print the sum of two numbers. Use top-level statement, put code between ```csharp and ```. | ||
"""; | ||
var chatMessage = new ChatMessage(ChatRole.User, task); | ||
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await foreach (var response in client.CompleteStreamingAsync([chatMessage])) | ||
{ | ||
Console.Write(response.Text); | ||
} | ||
} | ||
} |
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// See https://aka.ms/new-console-template for more information | ||
using Microsoft.ML.GenAI.Samples.Llama; | ||
using Microsoft.ML.GenAI.Samples.MEAI; | ||
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await LlamaSample.RunLlama(@"C:\Users\xiaoyuz\source\repos\Llama-3.2-3B-Instruct"); | ||
//await Llama3_1.RunAsync(@"C:\Users\xiaoyuz\source\repos\Llama-3.2-1B-Instruct", checkPointName: "model.safetensors"); | ||
await Phi3.RunAsync(@"C:\Users\xiaoyuz\source\repos\Phi-3-mini-4k-instruct"); |
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// Licensed to the .NET Foundation under one or more agreements. | ||
// The .NET Foundation licenses this file to you under the MIT license. | ||
// See the LICENSE file in the project root for more information. | ||
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using System; | ||
using System.Collections.Generic; | ||
using System.Linq; | ||
using System.Runtime.CompilerServices; | ||
using System.Threading; | ||
using System.Threading.Tasks; | ||
using Microsoft.Extensions.AI; | ||
using Microsoft.ML.Tokenizers; | ||
using static TorchSharp.torch; | ||
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namespace Microsoft.ML.GenAI.Core; | ||
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public abstract class CausalLMPipelineChatClient<TTokenizer, TCausalLMModel> : IChatClient | ||
where TTokenizer : Tokenizer | ||
where TCausalLMModel : nn.Module<CausalLMModelInput, CausalLMModelOutput> | ||
{ | ||
private readonly ICausalLMPipeline<TTokenizer, TCausalLMModel> _pipeline; | ||
private readonly IMEAIChatTemplateBuilder _chatTemplateBuilder; | ||
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public CausalLMPipelineChatClient( | ||
ICausalLMPipeline<TTokenizer, TCausalLMModel> pipeline, | ||
IMEAIChatTemplateBuilder chatTemplateBuilder, | ||
ChatClientMetadata? metadata = null) | ||
{ | ||
var classNameWithType = $"{nameof(CausalLMPipelineChatClient<TTokenizer, TCausalLMModel>)}<{typeof(TTokenizer).Name}, {typeof(TCausalLMModel).Name}>"; | ||
Metadata ??= new ChatClientMetadata(providerName: classNameWithType, modelId: typeof(TCausalLMModel).Name); | ||
_chatTemplateBuilder = chatTemplateBuilder; | ||
_pipeline = pipeline; | ||
} | ||
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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) | ||
{ | ||
var prompt = _chatTemplateBuilder.BuildPrompt(chatMessages, options); | ||
var stopSequences = options?.StopSequences ?? Array.Empty<string>(); | ||
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var output = _pipeline.Generate( | ||
prompt, | ||
maxLen: options?.MaxOutputTokens ?? 1024, | ||
temperature: options?.Temperature ?? 0.7f, | ||
stopSequences: stopSequences.ToArray()) ?? throw new InvalidOperationException("Failed to generate a reply."); | ||
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var chatMessage = new ChatMessage(ChatRole.Assistant, output); | ||
return Task.FromResult(new ChatCompletion([chatMessage]) | ||
{ | ||
CreatedAt = DateTime.UtcNow, | ||
FinishReason = ChatFinishReason.Stop, | ||
}); | ||
} | ||
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#pragma warning disable CS1998 // Async method lacks 'await' operators and will run synchronously | ||
public virtual async IAsyncEnumerable<StreamingChatCompletionUpdate> CompleteStreamingAsync( | ||
#pragma warning restore CS1998 // Async method lacks 'await' operators and will run synchronously | ||
IList<ChatMessage> chatMessages, | ||
ChatOptions? options = null, | ||
[EnumeratorCancellation] CancellationToken cancellationToken = default) | ||
{ | ||
var prompt = _chatTemplateBuilder.BuildPrompt(chatMessages, options); | ||
var stopSequences = options?.StopSequences ?? Array.Empty<string>(); | ||
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foreach (var output in _pipeline.GenerateStreaming( | ||
prompt, | ||
maxLen: options?.MaxOutputTokens ?? 1024, | ||
temperature: options?.Temperature ?? 0.7f, | ||
stopSequences: stopSequences.ToArray())) | ||
{ | ||
yield return new StreamingChatCompletionUpdate | ||
{ | ||
Role = ChatRole.Assistant, | ||
Text = output, | ||
CreatedAt = DateTime.UtcNow, | ||
}; | ||
} | ||
} | ||
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public virtual void Dispose() | ||
{ | ||
} | ||
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public virtual TService? GetService<TService>(object? key = null) where TService : class | ||
{ | ||
return null; | ||
} | ||
} |
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// Licensed to the .NET Foundation under one or more agreements. | ||
// The .NET Foundation licenses this file to you under the MIT license. | ||
// See the LICENSE file in the project root for more information. | ||
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using System.Runtime.CompilerServices; | ||
using Microsoft.Extensions.AI; | ||
using Microsoft.ML.GenAI.Core; | ||
using Microsoft.ML.Tokenizers; | ||
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namespace Microsoft.ML.GenAI.LLaMA; | ||
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public class Llama3CausalLMChatClient : CausalLMPipelineChatClient<Tokenizer, LlamaForCausalLM> | ||
{ | ||
private readonly string _eotToken = "<|eot_id|>"; | ||
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public Llama3CausalLMChatClient( | ||
ICausalLMPipeline<Tokenizer, LlamaForCausalLM> pipeline, | ||
IMEAIChatTemplateBuilder? chatTemplateBuilder = null, | ||
ChatClientMetadata? metadata = null) | ||
: base( | ||
pipeline, | ||
chatTemplateBuilder ?? Llama3_1ChatTemplateBuilder.Instance, | ||
metadata ?? new ChatClientMetadata(modelId: nameof(Llama3CausalLMChatClient))) | ||
{ | ||
} | ||
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public override Task<ChatCompletion> CompleteAsync( | ||
IList<ChatMessage> chatMessages, | ||
ChatOptions? options = null, | ||
CancellationToken cancellationToken = default) | ||
{ | ||
options ??= new ChatOptions(); | ||
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if (options.StopSequences != null) | ||
{ | ||
options.StopSequences.Add(_eotToken); | ||
} | ||
else | ||
{ | ||
options.StopSequences = new List<string> { _eotToken }; | ||
} | ||
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return base.CompleteAsync(chatMessages, options, cancellationToken); | ||
} | ||
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public override IAsyncEnumerable<StreamingChatCompletionUpdate> CompleteStreamingAsync( | ||
IList<ChatMessage> chatMessages, | ||
ChatOptions? options = null, | ||
CancellationToken cancellationToken = default) | ||
{ | ||
options ??= new ChatOptions(); | ||
options.StopSequences ??= []; | ||
options.StopSequences.Add(_eotToken); | ||
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return base.CompleteStreamingAsync(chatMessages, options, cancellationToken); | ||
} | ||
} |
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