Flutter智能回复插件learning_smart_reply的使用

发布于 1周前 作者 zlyuanteng 来自 Flutter

Flutter智能回复插件learning_smart_reply的使用

ML Smart Reply 是一个在Flutter中使用 ML Kit 生成智能回复的简便方法。通过 ML Kit 的智能回复功能,您可以自动生成与消息相关的回复,帮助用户快速响应消息,并使在输入能力有限的设备上更容易回复消息。

开始使用

  1. 将依赖项添加到您的 Flutter 项目:

    $ flutter pub add learning_smart_reply
    

    或者在 pubspec.yaml 文件中添加:

    dependencies:
      learning_smart_reply: ^0.0.2
    

    然后运行 flutter pub get

使用方法

首先导入包:

import 'package:learning_smart_reply/learning_smart_reply.dart';
生成智能回复

我们可以通过将聊天消息历史记录提供给 SmartReplyGenerator 来生成智能回复。

// 导入必要的包
import 'package:learning_smart_reply/learning_smart_reply.dart';
import 'package:uuid/uuid.dart';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      theme: ThemeData(
        primarySwatch: Colors.lightBlue,
        visualDensity: VisualDensity.adaptivePlatformDensity,
        primaryTextTheme: TextTheme(headline6: TextStyle(color: Colors.white)),
      ),
      home: SmartReplyPage(),
    );
  }
}

class SmartReplyPage extends StatefulWidget {
  [@override](/user/override)
  _SmartReplyPageState createState() => _SmartReplyPageState();
}

class _SmartReplyPageState extends State<SmartReplyPage> {
  SmartReplyGenerator _smartReply = SmartReplyGenerator();

  [@override](/user/override)
  void initState() {
    super.initState();
    WidgetsBinding.instance?.addPostFrameCallback((_) async {
      await testSmartReply();
    });
  }

  [@override](/user/override)
  void dispose() {
    // 释放资源
    _smartReply.dispose();
    super.dispose();
  }

  Future<void> testSmartReply() async {
    print('testSmartReply...');
    Uuid uuid = Uuid();
    String userId = uuid.v4(); // 生成唯一的用户ID
    int now = DateTime.now().millisecondsSinceEpoch;

    // 创建消息历史记录
    List<Message> history = [
      Message('Hi', user: userId, timestamp: now - (60 * 60 * 1000)), // 一小时前的消息
      Message('How are you?', timestamp: now - (20 * 60 * 1000)), // 20分钟前的消息
      Message('I am fine. Thanks.', user: userId, timestamp: now - (10 * 60 * 1000)), // 10分钟前的消息
    ];

    var result = await _smartReply.generateReplies(history); // 生成智能回复
    print('testSmartReply Result:');
    print(result);
  }

  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      theme: ThemeData(
        primarySwatch: Colors.lightBlue,
        visualDensity: VisualDensity.adaptivePlatformDensity,
        primaryTextTheme: TextTheme(headline6: TextStyle(color: Colors.white)),
      ),
      home: Scaffold(
        appBar: AppBar(
          centerTitle: true,
          title: Text('Smart Reply'),
        ),
        body: Container(),
      ),
    );
  }
}
资源释放

记得在不再需要时释放资源:

smartReply.dispose();

示例项目

您可以在示例项目中学习更多内容。

完整示例代码如下:

import 'package:flutter/material.dart';
import 'package:learning_smart_reply/learning_smart_reply.dart';
import 'package:uuid/uuid.dart';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      theme: ThemeData(
        primarySwatch: Colors.lightBlue,
        visualDensity: VisualDensity.adaptivePlatformDensity,
        primaryTextTheme: TextTheme(headline6: TextStyle(color: Colors.white)),
      ),
      home: SmartReplyPage(),
    );
  }
}

class SmartReplyPage extends StatefulWidget {
  [@override](/user/override)
  _SmartReplyPageState createState() => _SmartReplyPageState();
}

class _SmartReplyPageState extends State<SmartReplyPage> {
  SmartReplyGenerator _smartReply = SmartReplyGenerator();

  [@override](/user/override)
  void initState() {
    super.initState();
    WidgetsBinding.instance?.addPostFrameCallback((_) async {
      await testSmartReply();
    });
  }

  [@override](/user/override)
  void dispose() {
    _smartReply.dispose();
    super.dispose();
  }

  Future<void> testSmartReply() async {
    print('testSmartReply...');
    Uuid uuid = Uuid();
    String userId = uuid.v4();
    int now = DateTime.now().millisecondsSinceEpoch;

    List<Message> history = [
      Message('Hi', user: userId, timestamp: now - (60 * 60 * 1000)),
      Message('How are you?', timestamp: now - (20 * 60 * 1000)),
      Message('I am fine. Thanks.', user: userId, timestamp: now - (10 * 60 * 1000)),
    ];

    var result = await _smartReply.generateReplies(history);
    print('testSmartReply Result:');
    print(result);
  }

  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      debugShowCheckedModeBanner: false,
      theme: ThemeData(
        primarySwatch: Colors.lightBlue,
        visualDensity: VisualDensity.adaptivePlatformDensity,
        primaryTextTheme: TextTheme(headline6: TextStyle(color: Colors.white)),
      ),
      home: Scaffold(
        appBar: AppBar(
          centerTitle: true,
          title: Text('Smart Reply'),
        ),
        body: Container(),
      ),
    );
  }
}

更多关于Flutter智能回复插件learning_smart_reply的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html

1 回复

更多关于Flutter智能回复插件learning_smart_reply的使用的实战系列教程也可以访问 https://www.itying.com/category-92-b0.html


当然,以下是如何在Flutter项目中集成和使用learning_smart_reply插件的示例代码。learning_smart_reply是一个假设的插件名称,用于演示目的,因为在实际中,可能需要查找具体的智能回复插件并参考其官方文档。不过,以下代码提供了一个通用的集成和使用插件的方法。

1. 添加依赖

首先,在你的pubspec.yaml文件中添加该插件的依赖。请注意,这里使用的是假设的插件名和版本号,你需要替换为实际的插件名和版本。

dependencies:
  flutter:
    sdk: flutter
  learning_smart_reply: ^0.1.0  # 假设的版本号,请使用实际版本

2. 安装依赖

在终端中运行以下命令来安装依赖:

flutter pub get

3. 导入插件

在你的Dart文件中导入该插件:

import 'package:learning_smart_reply/learning_smart_reply.dart';

4. 初始化插件

通常,插件需要在应用启动时进行初始化。你可以在MainActivity.kt(对于Android)或AppDelegate.swift(对于iOS)中进行必要的初始化,但大多数Flutter插件主要通过Dart代码进行初始化。

5. 使用插件

以下是一个简单的示例,展示如何使用learning_smart_reply插件来获取智能回复建议:

import 'package:flutter/material.dart';
import 'package:learning_smart_reply/learning_smart_reply.dart';

void main() {
  runApp(MyApp());
}

class MyApp extends StatelessWidget {
  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: SmartReplyScreen(),
    );
  }
}

class SmartReplyScreen extends StatefulWidget {
  @override
  _SmartReplyScreenState createState() => _SmartReplyScreenState();
}

class _SmartReplyScreenState extends State<SmartReplyScreen> {
  final TextEditingController _controller = TextEditingController();
  List<String> _suggestions = [];

  void _getSmartReplies() async {
    try {
      String userMessage = _controller.text;
      List<String> replies = await LearningSmartReply.getSmartReplies(userMessage);
      setState(() {
        _suggestions = replies;
      });
    } catch (e) {
      print("Error getting smart replies: $e");
    }
  }

  @override
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Smart Reply Demo'),
      ),
      body: Padding(
        padding: const EdgeInsets.all(16.0),
        child: Column(
          crossAxisAlignment: CrossAxisAlignment.start,
          children: [
            TextField(
              controller: _controller,
              maxLines: 4,
              decoration: InputDecoration(
                labelText: 'Enter your message',
                border: OutlineInputBorder(),
              ),
            ),
            SizedBox(height: 16),
            ElevatedButton(
              onPressed: _getSmartReplies,
              child: Text('Get Smart Replies'),
            ),
            SizedBox(height: 16),
            if (_suggestions.isNotEmpty)
              Wrap(
                spacing: 8,
                runSpacing: 8,
                children: _suggestions.map((suggestion) => Chip(
                  label: Text(suggestion),
                )).toList(),
              ),
          ],
        ),
      ),
    );
  }
}

注意事项

  1. 插件文档:务必查看learning_smart_reply(或你实际使用的插件)的官方文档,以获取最新的集成和使用指南。
  2. 权限:某些智能回复插件可能需要特定的权限(如访问网络),请确保在AndroidManifest.xmlInfo.plist中声明必要的权限。
  3. 错误处理:在实际应用中,应添加更多的错误处理逻辑,以确保应用的健壮性。

由于learning_smart_reply是一个假设的插件名称,上述代码需要根据你的实际插件进行调整。如果找不到符合你需求的插件,可以考虑使用现有的机器学习库(如TensorFlow Lite)来构建自定义的智能回复系统。

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