wehub-resource-sync
52 lines
1.9 KiB
C#
52 lines
1.9 KiB
C#
// Copyright (c) Microsoft. All rights reserved.
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using Microsoft.SemanticKernel;
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using Microsoft.SemanticKernel.PromptTemplates.Handlebars;
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namespace PromptTemplates;
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// This example shows how to use chat completion handlebars template prompts with base64 encoded images as a parameter.
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public class HandlebarsVisionPrompts(ITestOutputHelper output) : BaseTest(output)
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{
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[Fact]
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public async Task RunAsync()
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{
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const string HandlebarsTemplate = """
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<message role="system">You are an AI assistant designed to help with image recognition tasks.</message>
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<message role="user">
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<text>{{request}}</text>
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<image>{{imageData}}</image>
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</message>
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""";
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var kernel = Kernel.CreateBuilder()
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.AddOpenAIChatCompletion(
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modelId: TestConfiguration.OpenAI.ChatModelId,
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apiKey: TestConfiguration.OpenAI.ApiKey)
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.Build();
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var templateFactory = new HandlebarsPromptTemplateFactory();
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var promptTemplateConfig = new PromptTemplateConfig()
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{
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Template = HandlebarsTemplate,
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TemplateFormat = "handlebars",
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Name = "Vision_Chat_Prompt",
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};
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var function = kernel.CreateFunctionFromPrompt(promptTemplateConfig, templateFactory);
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var arguments = new KernelArguments(new Dictionary<string, object?>
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{
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{"request","Describe this image:"},
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{"imageData", "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAoAAAAKCAYAAACNMs+9AAAAAXNSR0IArs4c6QAAACVJREFUKFNj/KTO/J+BCMA4iBUyQX1A0I10VAizCj1oMdyISyEAFoQbHwTcuS8AAAAASUVORK5CYII="}
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});
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var response = await kernel.InvokeAsync(function, arguments);
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Console.WriteLine(response);
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/*
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Output:
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The image is a solid block of bright red color. There are no additional features, shapes, or textures present.
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*/
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}
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}
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