How to build an intelligent question answering system using Elasticsearch and PHP-PHP Tutorial-php.cn

How to build an intelligent question answering system using Elasticsearch and PHP

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Release： 2023-07-07 15:56:02

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How to use Elasticsearch and PHP to build an intelligent question and answer system

Introduction:
With the rapid development of artificial intelligence technology, intelligent question and answer systems are gradually becoming an important way for people to obtain information. As a powerful search engine, Elasticsearch has fast and efficient full-text search and analysis capabilities, and can provide powerful support for intelligent question and answer systems. This article will introduce how to use Elasticsearch and PHP to build a simple intelligent question and answer system, and provide corresponding code examples.

Step 1: Create an index and import data
First, we need to create an index in Elasticsearch to store questions and answers. Suppose our index is named "qna" and has two fields, "question" and "answer". In Elasticsearch, we can use the PHP Elasticsearch client to create indexes and import data. The example is as follows:

<?php

require 'vendor/autoload.php';

$client = ElasticsearchClientBuilder::create()->build();

$params = [
    'index' => 'qna',
    'body' => [
        'settings' => [
            'number_of_shards' => 1,
            'number_of_replicas' => 0,
        ],
        'mappings' => [
            'properties' => [
                'question' => [
                    'type' => 'text',
                ],
                'answer' => [
                    'type' => 'text',
                ],
            ],
        ],
    ],
];

$response = $client->indices()->create($params);

// 导入数据
$data = [
    ['question' => '什么是Elasticsearch?', 'answer' => 'Elasticsearch是一个开源的分布式搜索引擎。'],
    ['question' => '如何在PHP中使用Elasticsearch?', 'answer' => '可以使用PHP Elasticsearch客户端库来与Elasticsearch进行交互。'],
];

foreach ($data as $row) {
    $params = [
        'index' => 'qna',
        'body' => $row,
    ];

    $client->index($params);
}

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Step 2: Create a search API
Next, we need to write PHP code to implement question search Function. We can use Elasticsearch's search API to implement full-text search, and the search results will be sorted according to relevance. The following is a simple search API example:

<?php

require 'vendor/autoload.php';

$client = ElasticsearchClientBuilder::create()->build();

$params = [
    'index' => 'qna',
    'body' => [
        'query' => [
            'match' => [
                'question' => '什么是Elasticsearch?',
            ],
        ],
    ],
];

$response = $client->search($params);

// 输出搜索结果
foreach ($response['hits']['hits'] as $hit) {
    echo '问题：' . $hit['_source']['question'] . PHP_EOL;
    echo '答案：' . $hit['_source']['answer'] . PHP_EOL;
    echo PHP_EOL;
}

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Step 3: Front-end interface and user interaction
The final step is to create the front-end interface and user interaction. We can use PHP to write a simple web interface that allows users to enter questions and displays search results. The following is a simple example:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <title>智能问答系统</title>
</head>
<body>
    <h1>智能问答系统</h1>

    <form action="search.php" method="get">
        <label for="question">请输入您的问题：</label>
        <input type="text" name="question" id="question">
        <button type="submit">搜索</button>
    </form>

    <h2>搜索结果：</h2>

    <?php

    require 'vendor/autoload.php';

    $client = ElasticsearchClientBuilder::create()->build();

    $question = $_GET['question'] ?? '';

    $params = [
        'index' => 'qna',
        'body' => [
            'query' => [
                'match' => [
                    'question' => $question,
                ],
            ],
        ],
    ];

    $response = $client->search($params);

    foreach ($response['hits']['hits'] as $hit) {
        echo '<p>问题：' . $hit['_source']['question'] . '</p>';
        echo '<p>答案：' . $hit['_source']['answer'] . '</p>';
        echo '<hr>';
    }

    ?>

</body>
</html>

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Conclusion:
This article briefly introduces how to use Elasticsearch and PHP to build a simple intelligent question and answer system. By using Elasticsearch's full-text search and analysis capabilities, we can quickly retrieve relevant questions and provide corresponding answers. The final effect will provide users with a convenient and efficient way to obtain information.

The above is the general process of building an intelligent question and answer system. I hope it will be helpful to you.

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