今年.NET Conf China 2023技术大会,我给大家分享了 .NET应用国际化-AIGC智能翻译+代码生成的议题
.NET Conf China 2023分享-.NET应用国际化-AIGC智能翻译+代码生成
今天将详细的代码实现和大家分享一下。
一、前提准备
1. 新建一个Console类的Project
2. 引用SK的Nuget包,SK的最新Nuget包
dotnet add package Microsoft.SemanticKernel --version 1.4.0
<ItemGroup> <PackageReference Include="Microsoft.SemanticKernel" Version="1.4.0" /> <PackageReference Include="Newtonsoft.Json" Version="13.0.3" /> </ItemGroup>
3. 在Azure OpenAI Service中创建一个GPT4的服务,这个可能大家没有账号,那就先看代码如何实现吧
部署好GPT4模型后,可以拿到以下三个重要的值
{{$input}} 请将上面的输入翻译为英文,不要返回任何解释说明, 请扮演一个美国电动汽车充电服务运营商(精通中文和英文),用户的输入数据是JSON格式,例如{"1":"充电站", "2":"充电桩"}, 如果不是JSON格式,请返回无效的输入。 请使用以下专业术语进行翻译 { "充电站":"Charging station", "电站":"Charging station", "场站":"Charging station", "充电桩":"Charging point", "充电终端":"Charging point", "终端":"Charging point", "电动汽车":"Electric Vehicle", "直流快充":"DC Fast Charger", "超级充电站":"Supercharger", "智能充电":"Smart Charging", "交流慢充":"AC Slow Charging" } 翻译结果请以JSON格式返回,例如 {"1":"Charging station", "2":"Charging point"}
类似的还有葡萄牙下的翻译Prompt
{{$input}} 请将上面的输入翻译为葡萄牙语,不要返回任何解释说明,请扮演一个巴西的电动汽车充电服务运营商(精通葡萄牙语、中文和英文) 用户的输入数据是JSON格式,例如{"1":"充电站", "2":"充电桩"}, 如果不是JSON格式,请返回无效的输入 请使用以下专业术语进行翻译 { "充电站": "Estação de carregamento", "电站": "Estação de carregamento", "场站": "Estação de carregamento", "充电桩": "Ponto de carregamento", "充电终端": "Ponto de carregamento", "终端": "Ponto de carregamento", "电动汽车": "Veículo Elétrico", "直流快充": "Carregador Rápido DC", "超级充电站": "Supercharger", "智能充电": "Carregamento Inteligente", "交流慢充": "Carregamento AC Lento" } 请以JSON格式返回,例如 {"1":"Estação de carregamento", "2":"Ponto de carregamento"}
在项目工程下新建Plugins目录和TranslatePlugin子目录,同时新建Translator_en和Translator_pt等多个子目录
config.json文件下的内容如下:
{ "schema": 1, "type": "completion", "description": "Translate.", "completion": { "max_tokens": 2000, "temperature": 0.5, "top_p": 0.0, "presence_penalty": 0.0, "frequency_penalty": 0.0 }, "input": { "parameters": [ { "name": "input", "description": "The user's input.", "defaultValue": "" } ] } }
三、Translator翻译类,实现文本多语言翻译
这个类主要实现将用户输入的文本(系统处理为JSON格式),翻译为指定的语言
这个类中构造函数中接收传入的Kernel对象,这个Kernel对象是指
// // Summary: // Provides state for use throughout a Semantic Kernel workload. // // Remarks: // An instance of Microsoft.SemanticKernel.Kernel is passed through to every function // invocation and service call throughout the system, providing to each the ability // to access shared state and services. public sealed class Kernel
暂且理解为调用各类大模型的Kernel核心类,基于这个Kernel实例对象完成大模型的调用和交互
另外,上述代码中有个Prompt模板文件读取的操作。
从Plugins/TranslatePlugin目录下读取指定的KernelPlugin,例如Translator_en英语翻译插件和Translator_pt 葡萄牙翻译插件
var output = kernel.InvokeAsync(plugin["Translator_" + language + ""], new() { ["input"] = json }).Result.ToString();
调用KernelFunction方式实现GPT4大模型调用
// // Summary: // Invokes the Microsoft.SemanticKernel.KernelFunction. // // Parameters: // function: // The Microsoft.SemanticKernel.KernelFunction to invoke. // // arguments: // The arguments to pass to the function's invocation, including any Microsoft.SemanticKernel.PromptExecutionSettings. // // // cancellationToken: // The System.Threading.CancellationToken to monitor for cancellation requests. // The default is System.Threading.CancellationToken.None. // // Returns: // The result of the function's execution. // // Exceptions: // T:System.ArgumentNullException: // function is null. // // T:Microsoft.SemanticKernel.KernelFunctionCanceledException: // The Microsoft.SemanticKernel.KernelFunction's invocation was canceled. // // Remarks: // This behaves identically to invoking the specified function with this Microsoft.SemanticKernel.Kernel // as its Microsoft.SemanticKernel.Kernel argument. public Task<FunctionResult> InvokeAsync(KernelFunction function, KernelArguments? arguments = null, CancellationToken cancellationToken = default(CancellationToken)) { Verify.NotNull(function, "function"); return function.InvokeAsync(this, arguments, cancellationToken); }
继续封装GPT4TranslateService,构造Microsoft.SemanticKernel.Kernel 类实例。
using System.Globalization; using Microsoft.SemanticKernel; namespace LLM_SK; public class GPT4TranslateService { public IDictionary<int,string> Translate(IDictionary<int, string> texts, CultureInfo cultureInfo) { var kernel = BuildKernel(); var translator = new Translator(kernel); return translator.Translate(texts, cultureInfo.TwoLetterISOLanguageName ); } //私有方法,构造IKernel private Kernel BuildKernel() { var builder = Kernel.CreateBuilder(); builder.AddAzureOpenAIChatCompletion( "xxxxgpt4", // Azure OpenAI Deployment Name "https://****.openai.azure.com/", // Azure OpenAI Endpoint "***************"); // Azure OpenAI Key return builder.Build(); } }
四、测试调用
这里我们设计了2种语言,英语和葡萄牙的文本翻译
var culture = new CultureInfo("en-US"); var translator = new GPT4TranslateService(); translator.Translate(new Dictionary<int, string>(){{ 1,"电站"}, {2,"终端不可用"},{3,"充电桩不可用"} , {4,"场站"},{5,"充电站暂未运营" }},culture); culture = new CultureInfo("pt-BR"); translator.Translate(new Dictionary<int, string>(){{ 1,"电站"}, {2,"终端不可用"},{3,"充电桩不可用"} , {4,"场站"},{5,"充电站暂未运营" }},culture);
输出的结果
{"1":"Charging station","2":"Charging point unavailable","3":"Charging station unavailable","4":"Charging station","5":"Charging station not in operation yet"}
{"1":"Estação de carregamento","2":"Ponto de carregamento não está disponível","3":"Ponto de carregamento não está disponível","4":"Estação de carregamento","5":"A estação de carregamento ainda não está em operação"}
五、总结
以上是基于SemanticKernel和GPT4实现一个智能翻译服务的Demo和框架,大家可以基于这个示例继续完善,增加更多动态的数据和API调用,例如将JSON数据写入数据库
同时还可以记录翻译不稳定的异常,手工处理或者继续完善Prompt。
周国庆文章来源:https://www.toymoban.com/news/detail-825328.html
2024/2/17文章来源地址https://www.toymoban.com/news/detail-825328.html
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