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Add samples showing how to use the multiple LLM support
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dotnet/samples/KernelSyntaxExamples/Example61_MultipleLLMs.cs
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| @@ -0,0 +1,69 @@ | ||
| // Copyright (c) Microsoft. All rights reserved. | ||
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| using System; | ||
| using System.Threading.Tasks; | ||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.AI; | ||
| using RepoUtils; | ||
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| // ReSharper disable once InconsistentNaming | ||
| public static class Example61_MultipleLLMs | ||
| { | ||
| /// <summary> | ||
| /// Show how to run a semantic function and specify a specific service to use. | ||
| /// </summary> | ||
| public static async Task RunAsync() | ||
| { | ||
| Console.WriteLine("======== Example61_MultipleLLMs ========"); | ||
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| string apiKey = TestConfiguration.AzureOpenAI.ApiKey; | ||
| string chatDeploymentName = TestConfiguration.AzureOpenAI.ChatDeploymentName; | ||
| string endpoint = TestConfiguration.AzureOpenAI.Endpoint; | ||
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| if (apiKey == null || chatDeploymentName == null || endpoint == null) | ||
| { | ||
| Console.WriteLine("Azure endpoint, apiKey, or deploymentName not found. Skipping example."); | ||
| return; | ||
| } | ||
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| string openAIModelId = TestConfiguration.OpenAI.ChatModelId; | ||
| string openAIApiKey = TestConfiguration.OpenAI.ApiKey; | ||
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| if (openAIModelId == null || openAIApiKey == null) | ||
| { | ||
| Console.WriteLine("OpenAI credentials not found. Skipping example."); | ||
| return; | ||
| } | ||
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| IKernel kernel = new KernelBuilder() | ||
| .WithLoggerFactory(ConsoleLogger.LoggerFactory) | ||
| .WithAzureChatCompletionService( | ||
| deploymentName: chatDeploymentName, | ||
| endpoint: endpoint, | ||
| serviceId: "AzureOpenAIChat", | ||
| apiKey: apiKey) | ||
| .WithOpenAIChatCompletionService( | ||
| modelId: openAIModelId, | ||
| serviceId: "OpenAIChat", | ||
| apiKey: openAIApiKey) | ||
| .Build(); | ||
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| await RunSemanticFunctionAsync(kernel, "AzureOpenAIChat"); | ||
| await RunSemanticFunctionAsync(kernel, "OpenAIChat"); | ||
| } | ||
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| public static async Task RunSemanticFunctionAsync(IKernel kernel, string serviceId) | ||
| { | ||
| Console.WriteLine($"======== {serviceId} ========"); | ||
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| var prompt = "Hello AI, what can you do for me?"; | ||
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| var result = await kernel.InvokeSemanticFunctionAsync( | ||
| prompt, | ||
| requestSettings: new AIRequestSettings() | ||
| { | ||
| ServiceId = serviceId | ||
| }); | ||
| Console.WriteLine(result.GetValue<string>()); | ||
| } | ||
| } |
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dotnet/samples/KernelSyntaxExamples/Example62_CustomAIServiceSelector.cs
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,162 @@ | ||
| // Copyright (c) Microsoft. All rights reserved. | ||
|
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| using System; | ||
| using System.Collections.Generic; | ||
| using System.Threading.Tasks; | ||
| using Microsoft.ML.Tokenizers; | ||
| using Microsoft.SemanticKernel; | ||
| using Microsoft.SemanticKernel.AI; | ||
| using Microsoft.SemanticKernel.Connectors.AI.OpenAI; | ||
| using Microsoft.SemanticKernel.Diagnostics; | ||
| using Microsoft.SemanticKernel.Services; | ||
| using Microsoft.SemanticKernel.TemplateEngine; | ||
| using RepoUtils; | ||
|
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| // ReSharper disable once InconsistentNaming | ||
| public static class Example62_CustomAIServiceSelector | ||
| { | ||
| /// <summary> | ||
| /// Show how to configure model request settings | ||
| /// </summary> | ||
| public static async Task RunAsync() | ||
| { | ||
| Console.WriteLine("======== Example61_CustomAIServiceSelector ========"); | ||
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| string apiKey = TestConfiguration.AzureOpenAI.ApiKey; | ||
| string chatDeploymentName = TestConfiguration.AzureOpenAI.ChatDeploymentName; | ||
| string endpoint = TestConfiguration.AzureOpenAI.Endpoint; | ||
|
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| if (apiKey == null || chatDeploymentName == null || endpoint == null) | ||
| { | ||
| Console.WriteLine("Azure endpoint, apiKey, or deploymentName not found. Skipping example."); | ||
| return; | ||
| } | ||
|
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| string openAIModelId = TestConfiguration.OpenAI.ChatModelId; | ||
| string openAIApiKey = TestConfiguration.OpenAI.ApiKey; | ||
|
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| if (openAIModelId == null || openAIApiKey == null) | ||
| { | ||
| Console.WriteLine("OpenAI credentials not found. Skipping example."); | ||
| return; | ||
| } | ||
|
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| IKernel kernel = new KernelBuilder() | ||
| .WithLoggerFactory(ConsoleLogger.LoggerFactory) | ||
| .WithAzureChatCompletionService( | ||
| deploymentName: chatDeploymentName, | ||
| endpoint: endpoint, | ||
| serviceId: "AzureOpenAIChat", | ||
| apiKey: apiKey) | ||
| .WithOpenAIChatCompletionService( | ||
| modelId: openAIModelId, | ||
| serviceId: "OpenAIChat", | ||
| apiKey: openAIApiKey) | ||
| .Build(); | ||
|
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| var modelSettings = new List<AIRequestSettings>(); | ||
| modelSettings.Add(new OpenAIRequestSettings() { ServiceId = "AzureOpenAIChat", MaxTokens = 400 }); | ||
| modelSettings.Add(new OpenAIRequestSettings() { ServiceId = "OpenAIChat", MaxTokens = 200 }); | ||
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| await RunSemanticFunctionAsync(kernel, "Hello AI, what can you do for me?", modelSettings); | ||
| await RunSemanticFunctionAsync(kernel, "Hello AI, provide an indepth description of what can you do for me as a bulleted list?", modelSettings); | ||
| } | ||
|
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| public static async Task RunSemanticFunctionAsync(IKernel kernel, string prompt, List<AIRequestSettings> modelSettings) | ||
| { | ||
| Console.WriteLine($"======== {prompt} ========"); | ||
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| var promptTemplateConfig = new PromptTemplateConfig() { ModelSettings = modelSettings }; | ||
| var promptTemplate = new PromptTemplate(prompt, promptTemplateConfig, kernel); | ||
| var serviceSelector = new MyAIServiceSelector(); | ||
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| var skfunction = kernel.RegisterSemanticFunction( | ||
| "MyFunction", | ||
| promptTemplateConfig, | ||
| promptTemplate, | ||
| serviceSelector); | ||
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| var result = await kernel.RunAsync(skfunction); | ||
| Console.WriteLine(result.GetValue<string>()); | ||
| } | ||
| } | ||
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| public class MyAIServiceSelector : IAIServiceSelector | ||
| { | ||
| private readonly int _defaultMaxTokens = 300; | ||
| private readonly int _minResponseTokens = 150; | ||
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| public (T?, AIRequestSettings?) SelectAIService<T>(string renderedPrompt, IAIServiceProvider serviceProvider, IReadOnlyList<AIRequestSettings>? modelSettings) where T : IAIService | ||
| { | ||
| if (modelSettings is null || modelSettings.Count == 0) | ||
| { | ||
| var service = serviceProvider.GetService<T>(null); | ||
| if (service is not null) | ||
| { | ||
| return (service, null); | ||
| } | ||
| } | ||
| else | ||
| { | ||
| var tokens = this.CountTokens(renderedPrompt); | ||
|
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| string? serviceId = null; | ||
| int fewestTokens = 0; | ||
| AIRequestSettings? requestSettings = null; | ||
| AIRequestSettings? defaultRequestSettings = null; | ||
| foreach (var model in modelSettings) | ||
| { | ||
| if (!string.IsNullOrEmpty(model.ServiceId)) | ||
| { | ||
| if (model is OpenAIRequestSettings openAIModel) | ||
| { | ||
| var responseTokens = (openAIModel.MaxTokens ?? this._defaultMaxTokens) - tokens; | ||
| if (serviceId is null || (responseTokens > this._minResponseTokens && responseTokens < fewestTokens)) | ||
| { | ||
| fewestTokens = responseTokens; | ||
| serviceId = model.ServiceId; | ||
| requestSettings = model; | ||
| } | ||
| } | ||
| } | ||
| else | ||
| { | ||
| // First request settings with empty or null service id is the default | ||
| defaultRequestSettings ??= model; | ||
| } | ||
| } | ||
|
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| if (serviceId is not null) | ||
| { | ||
| Console.WriteLine($"Selected service: {serviceId}"); | ||
| var service = serviceProvider.GetService<T>(serviceId); | ||
| if (service is not null) | ||
| { | ||
| return (service, requestSettings); | ||
| } | ||
| } | ||
|
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| if (defaultRequestSettings is not null) | ||
| { | ||
| var service = serviceProvider.GetService<T>(null); | ||
| if (service is not null) | ||
| { | ||
| return (service, defaultRequestSettings); | ||
| } | ||
| } | ||
| } | ||
|
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| throw new SKException("Unable to find AI service to handled request."); | ||
| } | ||
|
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| /// <summary> | ||
| /// MicrosoftML token counter implementation. | ||
| /// </summary> | ||
| private int CountTokens(string input) | ||
| { | ||
| Tokenizer tokenizer = new(new Bpe()); | ||
| var tokens = tokenizer.Encode(input).Tokens; | ||
|
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| return tokens.Count; | ||
| } | ||
| } |
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