January 2023
Intermediate to advanced
288 pages
6h 6m
Chinese
Content preview from 移动端AI与ML应用开发：基于iOS和Android
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iOS
上使用
ML Kit
的文本处理应用程序
|
121
图
7-6
：创建智能回复视图
完成此操作后，分别为上标签和下标签创建名为
conversationLabel
和
txtSuggestions
的
输出。对于按钮，创建一个名为
generateReply
的动作，并在其中调用
getSmartReply()
函数。如果 Xcode 出错，请不要担心
—
你很快就要编写该函数。
完成后，你的代码应如下所示：
@IBOutlet weak var conversationLabel: UILabel!
@IBOutlet weak var txtSuggestions: UILabel!
@IBAction func generateReply(_ sender: Any) {
getSmartReply()
}
7.3.3
第
3
步：创建模拟对话
查看模型运行的最快方法是进行一个我们可以传递给它的对话，所以让我们在这里创建
一个简单的对话。我创建了一个
initializeConversation()
函数，该函数创建对话项
并将它们添加到
TextMessage
类型的数组中。
因此，在类级别，你应该初始化数组：
var conversation: [TextMessage] = []
然后，
initializeConversation
将开始填充数组。
TextMessage
类型包含有关消息的详
细信息，该消息包括其内容、时间戳、来源，以及最重要的，它是本地用户（即你）还
是远程用户（即其他人）。因此，为了创建对话，我编写了一个辅助函数，该函数根据发 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.