whetstone.chatgpt
1.8.1
一个简单的轻量级库，它包裹开放的AI API并支持依赖注入。
支持的功能包括：
有关在此图书馆构建的Blazor Web应用程序的视频演练，请参阅：
将其部署到github页面，并在以下网站上找到：打开AI UI。 Blazor Web应用程序的来源位于whetstone.chatgpt.blazor.app上。
示例包括：
services . Configure < ChatGPTCredentials > ( options =>
{
options . ApiKey = " YOURAPIKEY " ;
options . Organization = " YOURORGANIZATIONID " ;
} ) ;使用：
services . AddHttpClient ( ) ;或者：
services . AddHttpClient < IChatGPTClient , ChatGPTClient > ( ) ;配置IChatGPTClient服务：
services . AddScoped < IChatGPTClient , ChatGPTClient > ( ) ; 聊天完成是一种特殊的完成类型，可用于聊天。它们被设计为在对话环境中使用。
这显示了GPT-3.5涡轮模型的使用。
using Whetstone . ChatGPT ;
using Whetstone . ChatGPT . Models ;
. . .
var gptRequest = new ChatGPTChatCompletionRequest
{
Model = ChatGPT35Models . Turbo ,
Messages = new List < ChatGPTChatCompletionMessage > ( )
{
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . System , " You are a helpful assistant. " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . User , " Who won the world series in 2020? " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . Assistant , " The Los Angeles Dodgers won the World Series in 2020. " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . User , " Where was it played? " )
} ,
Temperature = 0.9f ,
MaxTokens = 100
} ;
using IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
var response = await client . CreateChatCompletionAsync ( gptRequest ) ;
Console . WriteLine ( response ? . GetCompletionText ( ) ) ;GPT-4型号也可以使用，只要您的帐户已获得访问有限的Beta的访问权限即可。
完成使用模型来回答各种任务，包括但不限于分类，情感分析，回答问题等。
这显示了GPT-3.5-Turbo-Instruct模型的直接使用，没有任何提示。
请注意， CreateCompletionasync已过时。使用ChatgptChatCompletionRequest ， ChatgptChatCompletionResponse和createChatCompletionAsync方法。
using Whetstone . ChatGPT ;
using Whetstone . ChatGPT . Models ;
. . .
var gptRequest = new ChatGPTCompletionRequest
{
Model = ChatGPT35Models . Gpt35TurboInstruct ,
Prompt = " How is the weather? "
} ;
using IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
var response = await client . CreateCompletionAsync ( gptRequest ) ;
Console . WriteLine ( response . GetCompletionText ( ) ) ;GPT-3.5不是确定性的。上面样本的测试之一返回：
天气可能会因位置而异。通常，您可以期望温度适中和气候会感到舒适，但是最好检查您特定区域的预测。
AC＃使用完成的控制台应用程序可获得以下网址：
whetstone.chatgpt.commandlinebot（chatgpt-marv）
该样本包括：
如何创建一个上传新的微调文件。
List < ChatGPTTurboFineTuneLine > tuningInput = new ( )
{
new ChatGPTTurboFineTuneLine ( )
{
Messages = new List < ChatGPTTurboFineTuneLineMessage > ( )
{
new ( ChatGPTMessageRoles . System , " Marv is a factual chatbot that is also sarcastic. " ) ,
new ( ChatGPTMessageRoles . User , " What's the capital of France? " ) ,
new ( ChatGPTMessageRoles . Assistant , " Paris, as if everyone doesn't know that already. " )
} ,
} ,
new ChatGPTTurboFineTuneLine ( )
{
Messages = new List < ChatGPTTurboFineTuneLineMessage > ( )
{
new ( ChatGPTMessageRoles . System , " Marv is a factual chatbot that is also sarcastic. " ) ,
new ( ChatGPTMessageRoles . User , " Who wrote 'Romeo and Juliet'? " ) ,
new ( ChatGPTMessageRoles . Assistant , " Oh, just some guy named William Shakespeare. Ever heard of him? " )
} ,
} ,
. . .
} ;
byte [ ] tuningText = tuningInput . ToJsonLBinary ( ) ;
string fileName = " marvin.jsonl " ;
ChatGPTUploadFileRequest ? uploadRequest = new ChatGPTUploadFileRequest
{
File = new ChatGPTFileContent
{
FileName = fileName ,
Content = tuningText
}
} ;
ChatGPTFileInfo ? newTurboTestFile ;
using ( IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) )
{
newTurboTestFile = await client . UploadFileAsync ( uploadRequest ) ;
} 创建文件后，获取文件ID，并在创建新的微调时引用它。
IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
uploadedFileInfo = await client . UploadFileAsync ( uploadRequest ) ;
var fileList = await client . ListFilesAsync ( ) ;
var foundFile = fileList ? . Data ? . First ( x => x . Filename . Equals ( " marvin.jsonl " ) ) ;
ChatGPTCreateFineTuneRequest tuningRequest = new ChatGPTCreateFineTuneRequest
{
TrainingFileId = foundFile ? . Id ,
Model = " gpt-3.5-turbo-1106 "
} ;
ChatGPTFineTuneJob ? tuneResponse = await client . CreateFineTuneAsync ( tuningRequest ) ;
string ? fineTuneId = tuneResponse ? . Id ;处理微调请求将需要一些时间。结束后，状态将报告“成功”，并准备在完成请求中使用。
using IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
ChatGPTFineTuneJob ? tuneResponse = await client . RetrieveFineTuneAsync ( " FINETUNEID " ) ;
if ( tuneResponse . Status . Equals ( " succeeded " ) )
{
var gptRequest = new ChatGPTChatCompletionRequest
{
Model = " FINETUNEID " ,
Messages = new List < ChatGPTChatCompletionMessage > ( )
{
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . System , " You are a helpful assistant. " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . User , " Who won the world series in 2020? " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . Assistant , " The Los Angeles Dodgers won the World Series in 2020. " ) ,
new ChatGPTChatCompletionMessage ( ChatGPTMessageRoles . User , " Where was it played? " )
} ,
Temperature = 0.9f ,
MaxTokens = 100
} ;
var response = await client . CreateChatCompletionAsync ( gptRequest ) ;
Console . WriteLine ( response ? . GetCompletionText ( ) ) ; 这是生成1024x1024图像的示例。
ChatGPTCreateImageRequest imageRequest = new ( )
{
Prompt = " A sail boat " ,
Size = CreatedImageSize . Size1024 ,
ResponseFormat = CreatedImageFormat . Base64
} ;
using IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
ChatGPTImageResponse ? imageResponse = await client . CreateImageAsync ( imageRequest ) ;
var imageData = imageResponse ? . Data ? [ 0 ] ;
if ( imageData != null )
{
byte [ ] ? imageBytes = await client . DownloadImageAsync ( imageData ) ;
} 她是使用耳语转录音频文件的例子。
string audioFile = @"audiofilestranscriptiontest.mp3" ;
byte [ ] fileContents = File . ReadAllBytes ( audioFile ) ;
ChatGPTFileContent gptFile = new ChatGPTFileContent
{
FileName = audioFile ,
Content = fileContents
} ;
ChatGPTAudioTranscriptionRequest ? transcriptionRequest = new ChatGPTAudioTranscriptionRequest
{
File = gptFile
} ;
using IChatGPTClient client = new ChatGPTClient ( " YOURAPIKEY " ) ;
ChatGPTAudioResponse ? audioResponse = await client . CreateTranscriptionAsync ( transcriptionRequest , true ) ;
Console . WriteLine ( audioResponse ? . Text ) ;
