Generate Smart Replies with ML Kit on iOS

You can use ML Kit to generate message replies using an on-device model.

To generate smart replies, you pass ML Kit a log of recent messages in a conversation. If ML Kit determines the conversation is in English, and that the conversation doesn't have potentially sensitive subject matter, ML Kit generates up to three replies, which you can suggest to your user.

Before you begin

1. If you have not already added Firebase to your app, do so by following the steps in the getting started guide.
2. Include the ML Kit libraries in your Podfile:

   pod 'Firebase/MLCommon', '6.25.0'
   pod 'Firebase/MLNLSmartReply', '6.25.0'
   

   After you install or update your project's Pods, be sure to open your Xcode project using its .xcworkspace.
3. In your app, import Firebase:

   Swift

   import Firebase

   Objective-C

   @import Firebase;

1. Create a conversation history object

To generate smart replies, you pass ML Kit a chronologically-ordered array of TextMessage objects, with the earliest timestamp first. Whenever the user sends or receives a message, add the message, its timestamp, and the message sender's user ID to the conversation history.

The user ID can be any string that uniquely identifies the sender within the conversation. The user ID doesn't need to correspond to any user data, and the user ID doesn't need to be consistent between conversations or invocations of the smart reply generator.

If the message was sent by the user you want to suggest replies to, set isLocalUser to true.

var conversation: [TextMessage] = []

// Then, for each message sent and received:
let message = TextMessage(
    text: "How are you?",
    timestamp: Date().timeIntervalSince1970,
    userID: "userId",
    isLocalUser: false)
conversation.append(message)

NSMutableArray *conversation = [NSMutableArray array];

// Then, for each message sent and received:
FIRTextMessage *message = [[FIRTextMessage alloc]
        initWithText:@"How are you?"
        timestamp:[NSDate date].timeIntervalSince1970
        userID:userId
        isLocalUser:NO];
[conversation addObject:message];

A conversation history object looks like the following example:

Note that the most recent message in the example above is from a non-local user. This is important because ML Kit suggests replies intended to be sent by the user of your app: the local user. You should be sure you're passing ML Kit a conversation log that ends with a message to which your user might want to reply.

2. Get message replies

To generate smart replies to a message, get an instance of SmartReply and pass the conversation history to its suggestReplies(for:completion:) method:

let naturalLanguage = NaturalLanguage.naturalLanguage()
naturalLanguage.smartReply().suggestReplies(for: conversation) { result, error in
    guard error == nil, let result = result else {
        return
    }
    if (result.status == .notSupportedLanguage) {
        // The conversation's language isn't supported, so the
        // the result doesn't contain any suggestions.
    } else if (result.status == .success) {
        // Successfully suggested smart replies.
        // ...
    }
}

FIRNaturalLanguage *naturalLanguage = [FIRNaturalLanguage naturalLanguage];
FIRSmartReply *smartReply = [naturalLanguage smartReply];
[smartReply suggestRepliesForMessages:inputText
                           completion:^(FIRSmartReplySuggestionResult * _Nullable result,
                                        NSError * _Nullable error) {
  if (error || !result) {
    return;
  }
  if (result.status == FIRSmartReplyResultStatusNotSupportedLanguage) {
      // The conversation's language isn't supported, so the
      // the result doesn't contain any suggestions.
  } else if (result.status == FIRSmartReplyResultStatusSuccess) {
      // Successfully suggested smart replies.
      // ...
  }
}];
]

If the operation succeeds, a SmartReplySuggestionResult object is passed to the completion handler. This object contains a list of up to 3 suggested replies, which you can present to your user:

for suggestion in result.suggestions {
  print("Suggested reply: \(suggestion.text)")
}

for (FIRSmartReplySuggestion *suggestion in result.suggestions) {
  NSLog(@"Suggested reply: %@", suggestion.text);
}

Note that ML Kit might not return results if the model isn't confident in the relevance of the suggested replies, the input conversation isn't in English, or if the model detects sensitive subject matter.