安裝或更新專案的 Pod 後,請使用
.xcworkspace。Xcode 12.4 以上版本支援 ML Kit。
1. 建立對話記錄物件
如要產生智慧回覆功能,您必須傳送 ML Kit 依時間順序排序的
TextMessage 物件,具有最早的時間戳記。每當使用者
新增或接收訊息、新增訊息、其時間戳記以及
並將傳送者的使用者 ID 加入對話記錄中。
使用者 ID 可以是任何能用來識別
對話。User-ID 不需要對應至任何使用者資料
而且使用者 ID 不必保持一致
叫用智慧回覆產生器。
如果訊息是由您想建議回覆的使用者所寄送,請設定
isLocalUser 設為 true。
Swift
varconversation:[TextMessage]=[]// Then, for each message sent and received:letmessage=TextMessage(text:"How are you?",timestamp:Date().timeIntervalSince1970,userID:"userId",isLocalUser:false)conversation.append(message)
Objective-C
NSMutableArray*conversation=[NSMutableArrayarray];// Then, for each message sent and received:MLKTextMessage*message=[[MLKTextMessagealloc]initWithText:@"How are you?"timestamp:[NSDatedate].timeIntervalSince1970userID:userIdisLocalUser:NO];[conversationaddObject:message];
對話記錄物件如下列範例所示:
時間戳記
userID
isLocalUser
訊息
2019 年 2 月 21 日星期四 13:13:39 (太平洋標準時間)
true
你正在路上嗎?
2019 年 2 月 21 日星期四 13:15:03 (太平洋標準時間)
朋友
false
抱歉,我遲到了!
ML Kit 建議回覆對話記錄中的最後一則訊息。最後一則訊息
應為非本機使用者。在上述範例中,對話中的最後一則訊息
來自非當地使用者 FRIEND0。使用 Pass ML Kit 這項記錄時
回覆 FRIENDO 的訊息:「運作中遲到了,很抱歉!」
SmartReply.smartReply().suggestReplies(for:conversation){result,erroringuarderror==nil,letresult=resultelse{return}if(result.status==.notSupportedLanguage){// The conversation's language isn't supported, so// the result doesn't contain any suggestions.}elseif(result.status==.success){// Successfully suggested smart replies.// ...}}
Objective-C
MLKSmartReply*smartReply=[MLKSmartReplysmartReply];[smartReplysuggestRepliesForMessages:inputTextcompletion:^(MLKSmartReplySuggestionResult*_Nullableresult,NSError*_Nullableerror){if(error||!result){return;}if(result.status==MLKSmartReplyResultStatusNotSupportedLanguage){// The conversation's language isn't supported, so// the result doesn't contain any suggestions.}elseif(result.status==MLKSmartReplyResultStatusSuccess){// Successfully suggested smart replies.// ...}}];
[null,null,["上次更新時間:2025-08-29 (世界標準時間)。"],[[["\u003cp\u003eML Kit provides an on-device model to generate smart replies for messages in English conversations, enhancing user experience and engagement.\u003c/p\u003e\n"],["\u003cp\u003eBy passing a conversation history to ML Kit, developers can receive up to three suggested replies for the latest message, which can then be displayed to the user.\u003c/p\u003e\n"],["\u003cp\u003eBefore utilizing the API, ensure the device is 64-bit and include the necessary ML Kit pods in your project.\u003c/p\u003e\n"],["\u003cp\u003eThe smart reply feature is optimized for non-sensitive conversations, and may not generate results if the language is unsupported or sensitive topics are detected.\u003c/p\u003e\n"]]],[],null,["ML Kit can generate short replies to messages using an on-device model.\n\nTo generate smart replies, you pass ML Kit a log of recent messages in a\nconversation. If ML Kit determines the conversation is in English, and that\nthe conversation doesn't have potentially sensitive subject matter, ML Kit\ngenerates up to three replies, which you can suggest to your user.\n\n\u003cbr /\u003e\n\n| **Note:** ML Kit iOS APIs only run on 64-bit devices. If you build your app with 32-bit support, check the device's architecture before using this API.\n\nTry it out\n\n- Play around with [the sample app](https://github.com/googlesamples/mlkit/tree/master/ios/quickstarts/smartreply) to see an example usage of this API.\n\nBefore you begin\n\n1. Include the following ML Kit pods in your Podfile: \n\n ```\n pod 'GoogleMLKit/SmartReply', '8.0.0'\n ```\n2. After you install or update your project's Pods, open your Xcode project using its `.xcworkspace`. ML Kit is supported in Xcode version 12.4 or greater.\n\n1. Create a conversation history object\n\nTo generate smart replies, you pass ML Kit a chronologically-ordered array of\n`TextMessage` objects, with the earliest timestamp first. Whenever the user\nsends or receives a message, add the message, its timestamp, and the message\nsender's user ID to the conversation history.\n\nThe user ID can be any string that uniquely identifies the sender within the\nconversation. The user ID doesn't need to correspond to any user data,\nand the user ID doesn't need to be consistent between conversations or\ninvocations of the smart reply generator.\n\nIf the message was sent by the user you want to suggest replies to, set\n`isLocalUser` to true. \n\nSwift \n\n```swift\nvar conversation: [TextMessage] = []\n\n// Then, for each message sent and received:\nlet message = TextMessage(\n text: \"How are you?\",\n timestamp: Date().timeIntervalSince1970,\n userID: \"userId\",\n isLocalUser: false)\nconversation.append(message)\n```\n\nObjective-C \n\n```objective-c\nNSMutableArray *conversation = [NSMutableArray array];\n\n// Then, for each message sent and received:\nMLKTextMessage *message = [[MLKTextMessage alloc]\n initWithText:@\"How are you?\"\n timestamp:[NSDate date].timeIntervalSince1970\n userID:userId\n isLocalUser:NO];\n[conversation addObject:message];\n```\n\nA conversation history object looks like the following example:\n\n| Timestamp | userID | isLocalUser | Message |\n|------------------------------|---------|-------------|----------------------|\n| Thu Feb 21 13:13:39 PST 2019 | | true | are you on your way? |\n| Thu Feb 21 13:15:03 PST 2019 | FRIEND0 | false | Running late, sorry! |\n\nML Kit suggests replies to the last message in a conversation history. The last message\nshould be from a non-local user. In the example above, the last message in the conversation\nis from the non-local user FRIEND0. When you use pass ML Kit this log, it suggests\nreplies to FRIENDO's message: \"Running late, sorry!\"\n\n2. Get message replies\n\nTo generate smart replies to a message, get an instance of `SmartReply` and pass\nthe conversation history to its `suggestReplies(for:completion:)` method: \n\nSwift \n\n```swift\nSmartReply.smartReply().suggestReplies(for: conversation) { result, error in\n guard error == nil, let result = result else {\n return\n }\n if (result.status == .notSupportedLanguage) {\n // The conversation's language isn't supported, so\n // the result doesn't contain any suggestions.\n } else if (result.status == .success) {\n // Successfully suggested smart replies.\n // ...\n }\n}\n```\n\nObjective-C \n\n```objective-c\nMLKSmartReply *smartReply = [MLKSmartReply smartReply];\n[smartReply suggestRepliesForMessages:inputText\n completion:^(MLKSmartReplySuggestionResult * _Nullable result,\n NSError * _Nullable error) {\n if (error || !result) {\n return;\n }\n if (result.status == MLKSmartReplyResultStatusNotSupportedLanguage) {\n // The conversation's language isn't supported, so\n // the result doesn't contain any suggestions.\n } else if (result.status == MLKSmartReplyResultStatusSuccess) {\n // Successfully suggested smart replies.\n // ...\n }\n}];\n```\n\nIf the operation succeeds, a `SmartReplySuggestionResult` object is passed to\nthe completion handler. This object contains a list of up to three suggested\nreplies, which you can present to your user: \n\nSwift \n\n```swift\nfor suggestion in result.suggestions {\n print(\"Suggested reply: \\(suggestion.text)\")\n}\n```\n\nObjective-C \n\n```objective-c\nfor (MLKSmartReplySuggestion *suggestion in result.suggestions) {\n NSLog(@\"Suggested reply: %@\", suggestion.text);\n}\n```\n\nNote that ML Kit might not return results if the model isn't confident in\nthe relevance of the suggested replies, the input conversation isn't in\nEnglish, or if the model detects sensitive subject matter."]]