chore: import upstream snapshot with attribution
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// Copyright (c) Microsoft. All rights reserved.
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using System.Text.Json;
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.Connectors.OpenAI;
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namespace KernelExamples;
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public sealed class ConfigureExecutionSettings(ITestOutputHelper output) : BaseTest(output)
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{
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/// <summary>
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/// Show how to configure model execution settings
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/// </summary>
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[Fact]
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public async Task RunAsync()
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{
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Console.WriteLine("======== ConfigureExecutionSettings ========");
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string serviceId = TestConfiguration.AzureOpenAI.ServiceId;
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string apiKey = TestConfiguration.AzureOpenAI.ApiKey;
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string chatDeploymentName = TestConfiguration.AzureOpenAI.ChatDeploymentName;
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string chatModelId = TestConfiguration.AzureOpenAI.ChatModelId;
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string endpoint = TestConfiguration.AzureOpenAI.Endpoint;
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if (apiKey is null || chatDeploymentName is null || endpoint is null)
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{
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Console.WriteLine("AzureOpenAI endpoint, apiKey, or deploymentName not found. Skipping example.");
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return;
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}
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Kernel kernel = Kernel.CreateBuilder()
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.AddAzureOpenAIChatCompletion(
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deploymentName: chatDeploymentName,
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endpoint: endpoint,
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serviceId: serviceId,
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apiKey: apiKey,
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modelId: chatModelId)
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.Build();
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var prompt = "Hello AI, what can you do for me?";
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// Option 1:
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// Invoke the prompt function and pass an OpenAI specific instance containing the execution settings
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var result = await kernel.InvokePromptAsync(
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prompt,
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new(new OpenAIPromptExecutionSettings()
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{
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MaxTokens = 60,
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Temperature = 0.7
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}));
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Console.WriteLine(result.GetValue<string>());
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// Option 2:
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// Load prompt template configuration including the execution settings from a JSON payload
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// Create the prompt functions using the prompt template and the configuration (loaded in the previous step)
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// Invoke the prompt function using the implicitly set execution settings
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string configPayload = """
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{
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"schema": 1,
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"name": "HelloAI",
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"description": "Say hello to an AI",
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"type": "completion",
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"completion": {
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"max_tokens": 256,
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"temperature": 0.5,
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"top_p": 0.0,
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"presence_penalty": 0.0,
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"frequency_penalty": 0.0
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}
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}
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""";
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var promptConfig = JsonSerializer.Deserialize<PromptTemplateConfig>(configPayload)!;
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promptConfig.Template = prompt;
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var func = kernel.CreateFunctionFromPrompt(promptConfig);
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result = await kernel.InvokeAsync(func);
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Console.WriteLine(result.GetValue<string>());
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/* OUTPUT (using gpt4):
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Hello! As an AI language model, I can help you with a variety of tasks, such as:
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1. Answering general questions and providing information on a wide range of topics.
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2. Assisting with problem-solving and brainstorming ideas.
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3. Offering recommendations for books, movies, music, and more.
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4. Providing definitions, explanations, and examples of various concepts.
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5. Helping with language-related tasks, such as grammar, vocabulary, and writing tips.
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6. Generating creative content, such as stories, poems, or jokes.
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7. Assisting with basic math and science problems.
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8. Offering advice on various topics, such as productivity, motivation, and personal development.
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Please feel free to ask me anything, and I'll do my best to help you!
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Hello! As an AI language model, I can help you with a variety of tasks, including:
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1. Answering general questions and providing information on a wide range of topics.
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2. Offering suggestions and recommendations.
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3. Assisting with problem-solving and brainstorming ideas.
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4. Providing explanations and
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*/
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}
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}
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