今天在新闻上看到一条消息，OpenAI已经开放了ChatGPT的接口，也就是GPT-3.5，对比原来的GPT-3，增加了gpt-3.5-turbo、gpt-3.5-turbo-0301两个模型。

gpt-3.5-turbo：使用最新的GPT-3.5模型，并针对聊天进行了优化，使用最新的模型进行迭代
gpt-3.5-turbo-0301：属于 gpt-3.5-turbo的快照，此模型不会进行更新，并且在2023年6月1日停止支持
因此，我们使用gpt-3.5-turbo就可以了。

对于GPT-3，GPT-3.5是支持上下文的。通过API，我们可以完成完整的聊天了。gpt-3.5-turbo的API如下：

model：我们使用gpt-3.5-turbo
messages：数组形式，例如：[{"role": "user", "content": "Hello!"}]，role分为三种角色，分别是system、assistant和user。
temperature：取值是0-2，
top_p：默认值是1，
n：默认值是1
stream：默认值是false
stop：默认值是null
max_tokens：最大值是4096
presence_penalty：默认值是0
frequency_penalty：默认值是0
logit_bias：默认值是null
其中，model和messages是必填的，其他，我们采用默认值就可以了
根据上一篇文章，学习.NET MAUI Blazor（六）、基于OpenAI接口的伪ChatGPT，我们还是使用开源的SDK类库OpenAI-DotNet，该类库于3月2日升级到了5.0版本，新增了Chat接口，这样就可以实现聊天应用了。接着上一篇文章，我们来做一个真正的ChatGPT对话功能。

打开Shared/NavMenu.razor，修改内容如下：

<div class="top-row ps-3 navbar navbar-dark"><div class="container-fluid"><a class="navbar-brand" href="">OpenAI</a><button title="Navigation menu" class="navbar-toggler" @onclick="ToggleNavMenu"><span class="navbar-toggler-icon"></span></button></div>
</div><div class="@NavMenuCssClass" @onclick="ToggleNavMenu"><nav class="flex-column"><div class="nav-item px-3"><NavLink class="nav-link" href="" Match="NavLinkMatch.All"><span class="oi oi-home" aria-hidden="true"></span> 文本</NavLink></div><div class="nav-item px-3"><NavLink class="nav-link" href="chat" Match="NavLinkMatch.All"><span class="oi oi-chat" aria-hidden="true"></span> 对话</NavLink></div><div class="nav-item px-3"><NavLink class="nav-link" href="code"><span class="oi oi-plus" aria-hidden="true"></span> 代码</NavLink></div><div class="nav-item px-3"><NavLink class="nav-link" href="image"><span class="oi oi-list-rich" aria-hidden="true"></span> 图像</NavLink></div></nav>
</div>@code {private bool collapseNavMenu = true;private string NavMenuCssClass => collapseNavMenu ? "collapse" : null;private void ToggleNavMenu(){collapseNavMenu = !collapseNavMenu;}
}

接着在Pages目录下，新建一个Chat.razor。页面内容如下：

@using System.Text;
@using Mode;
@page "/chat"
<MContainer Class="spacing-playground pa-6 pr h-100" Fluid><MSkeletonLoader Class="mb-12 h-full w-100" Boilerplate="@Boilerplate" Elevation="2" Loading="@Boilerplate" Type="article, actions"><ChildContent><MRow Class="h-full body_row"><MCol Class="d-flex answers_box" Cols="24" Sm="12"><MVirtualScroll Class="answer_list_box" Items="_items" @ref="_vs"><ItemContent><MListItem Class=" d-flex flex-column"><div class="question_items d-flex flex-row w-100"><div class="quest_img"><img src="image/user.png" /></div><div class="question_txt">@context.question</div></div><div class="answers_items d-flex flex-row  w-100"><div class="answer-img"><svg width="41" height="41" viewBox="0 0 41 41" fill="none" xmlns="http://www.w3.org/2000/svg" stroke-width="1.5" class="h-6 w-6"><path d="M37.5324 16.8707C37.9808 15.5241 38.1363 14.0974 37.9886 12.6859C37.8409 11.2744 37.3934 9.91076 36.676 8.68622C35.6126 6.83404 33.9882 5.3676 32.0373 4.4985C30.0864 3.62941 27.9098 3.40259 25.8215 3.85078C24.8796 2.7893 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class="answer-txt">@context.answer</div></div></MListItem></ItemContent></MVirtualScroll></MCol></MRow><div class="footer_box"><div class="d-flex justify-content-center"><div class="col-18 col-sm-9"><div class="send_box"><textarea class="send_input" @bind="question"></textarea><MButton Class="send_btn" Fab Small Color="primary" OnClick="RequestAnswers"><MIcon Size="14">mdi-send-outline</MIcon></MButton></div></div></div></div></ChildContent></MSkeletonLoader></MContainer>

编写Code代码

@code {public string question = "";private bool Boilerplate = false;private MVirtualScroll<QA> _vs;private List<OpenAI.Chat.ChatPrompt> chatPromptsList = new List<OpenAI.Chat.ChatPrompt>();private List<QA> _items = new();private async Task RequestAnswers(){Boilerplate = true;var api = new OpenAI.OpenAIClient(new OpenAI.OpenAIAuthentication(OpenAIConfig.api_key));OpenAI.Chat.ChatPrompt chatPrompt = new OpenAI.Chat.ChatPrompt("user", question);chatPromptsList.Add(chatPrompt);var chatRequest = new OpenAI.Chat.ChatRequest(chatPromptsList);QA qa = new();qa.question = question;var result = await api.ChatEndpoint.GetCompletionAsync(chatRequest);string answer = result.FirstChoice.Message.Content;answer = answer.ReplaceFirst("\r", "").ReplaceFirst("\n", "");qa.answer = answer;_items.Add(qa);Boilerplate = false;}}