Flutter集成Mistral AI服务插件mistralai_client_dart_flutter_flow的使用

本教程将介绍如何在Flutter项目中集成Mistral AI服务插件mistralai_client_dart_flutter_flow。通过该插件，您可以轻松地调用Mistral AI的各种API功能。

插件描述

mistralai_client_dart_flutter_flow 是一个非官方的Dart/Flutter客户端库，用于与Mistral AI API进行交互。该实现受到官方Mistral AI JavaScript客户端的启发。

使用场景

支持版本

• FlutterFlow: 4.1
• Flutter: 3.13.7+

安装

在您的pubspec.yaml文件中添加以下依赖项：

dependencies:
  mistralai_client_dart_flutter_flow: ^最新版本号

然后运行以下命令以安装依赖：

dart pub get

基本使用

创建客户端

首先，导入插件并创建一个MistralAIClient实例：

import 'package:mistralai_client_dart_flutter_flow/mistralai_client_dart_flutter_flow.dart';

// 替换为您的API密钥
final client = MistralAIClient(apiKey: 'your_api_key_here');

列出模型

使用listModels方法获取可用的Mistral AI模型列表：

final modelsResult = await client.listModels();
final models = modelsResult.data.map((e) => e.id).toList();
print(models.join(', ')); // 输出模型ID列表

聊天功能

使用chat方法与Mistral AI进行对话：

final params = ChatParams(
  model: 'mistral-small-latest',
  messages: const [
    ChatMessage(role: 'user', content: 'Hello chat!'),
  ],
);

final chatCompletion = await client.chat(params);
final chatMessage = chatCompletion.choices[0].message;
print(chatMessage); // 输出AI回复

流式聊天

如果您希望实时接收AI的回复，可以使用streamChat方法：

final stream = client.streamChat(params);
await for (final completionChunk in stream) {
  final chatMessage = completionChunk.choices[0].delta?.content;
  if (chatMessage != null) {
    print(chatMessage); // 实时打印AI的逐段回复
  }
}

获取嵌入向量

使用embeddings方法生成文本嵌入向量：

final embeddings = await client.embeddings(
  const EmbeddingParams(
    model: 'mistral-embed',
    input: ['Hello chat!'],
  ),
);

for (final data in embeddings.data) {
  print(data.embedding); // 输出嵌入向量
}

函数调用

如果需要调用外部函数，可以配置tools参数：

String retrievePaymentStatus(Map<String, String> data, String transactionId) =>
    '{"status": ${data[transactionId]}}';

final namesToFunctions = {
  'retrievePaymentStatus': (String transactionId) =>
      retrievePaymentStatus(paymentStatusData, transactionId),
};

final tools = [
  const ToolsFunction(
    name: 'retrievePaymentStatus',
    description: 'Get payment status of a transaction',
    parameters: [
      ToolsFunctionParameter(
        name: 'transactionId',
        type: 'string',
        description: 'The transaction ID',
        isRequired: true,
      ),
    ],
  ).toChatParamsFormat(),
];

var chatResponse = await client.chat(
    ChatParams(
        model: 'mistral-large-latest',
        messages: messages,
        tools: tools,
        toolChoice: 'auto',
    ),
);

final toolCall = chatResponse.choices[0].message.toolCalls?[0];
if (toolCall != null && toolCall.type == 'function') {
    final functionName = toolCall.function!.name;
    final functionParams = toolCall.function!.argumentsMap;

    print('calling functionName: $functionName');
    print('functionParams: $functionParams');

    final functionResult = namesToFunctions[functionName]!(
        functionParams['transactionId']! as String,
    );

    messages.add(
        ChatMessage(role: 'tool', content: functionResult, name: functionName),
    );

    chatResponse = await client.chat(
        ChatParams(
            model: model,
            messages: messages,
            tools: tools,
            toolChoice: 'auto',
        ),
    );

    print(chatResponse.choices[0].message.content);
}

示例完整代码

以下是一个完整的Flutter示例，展示了如何集成mistralai_client_dart_flutter_flow插件并使用其核心功能：

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

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

class MyApp extends StatelessWidget {
  [@override](/user/override)
  Widget build(BuildContext context) {
    return MaterialApp(
      home: HomeScreen(),
    );
  }
}

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

class _HomeScreenState extends State<HomeScreen> {
  final client = MistralAIClient(apiKey: 'your_api_key_here');
  String response = '';

  Future<void> listModels() async {
    final modelsResult = await client.listModels();
    final models = modelsResult.data.map((e) => e.id).toList();
    setState(() {
      response = models.join(', ');
    });
  }

  Future<void> chat() async {
    final params = ChatParams(
      model: 'mistral-small-latest',
      messages: const [
        ChatMessage(role: 'user', content: 'Hello chat!'),
      ],
    );

    final chatCompletion = await client.chat(params);
    setState(() {
      response = chatCompletion.choices[0].message.content;
    });
  }

  [@override](/user/override)
  Widget build(BuildContext context) {
    return Scaffold(
      appBar: AppBar(
        title: Text('Mistral AI Client Demo'),
      ),
      body: Center(
        child: Column(
          mainAxisAlignment: MainAxisAlignment.center,
          children: [
            ElevatedButton(
              onPressed: listModels,
              child: Text('List Models'),
            ),
            SizedBox(height: 20),
            ElevatedButton(
              onPressed: chat,
              child: Text('Start Chat'),
            ),
            SizedBox(height: 20),
            Text(response),
          ],
        ),
      ),
    );
  }
}