Spring AI自然语言操作MySQL实战指南

Spring AI Tool 实现自然语言操作 MySQL 数据库详解

技术背景与目标

Spring AI 是 Spring 生态中集成人工智能能力的工具，支持通过自然语言生成数据库操作代码。MySQL 作为广泛应用的关系型数据库，结合自然语言交互可显著降低开发门槛。以下详解实现方案。

环境配置与依赖

确保项目基于 Spring Boot 3.x 并添加依赖：

<dependency>
    <groupId>org.springframework.ai</groupId>
    <artifactId>spring-ai-mysql-ai</artifactId>
    <version>1.0.0</version>
</dependency>
<dependency>
    <groupId>mysql</groupId>
    <artifactId>mysql-connector-java</artifactId>
    <version>8.0.33</version>
</dependency>

自然语言到 SQL 转换

通过 Spring AI 的 NaturalLanguageToSql 组件实现转换。需配置数据库 Schema 信息供模型理解表结构：

@Bean
public NaturalLanguageToSqlConverter sqlConverter() {
    return new NaturalLanguageToSqlConverter.Builder()
        .withSchema("your_schema_name")
        .withModel("gpt-3.5-turbo") 
        .build();
}

示例操作流程

查询请求处理 用户输入："查找年龄大于25的用户"

String sql = sqlConverter.convert("查找年龄大于25的用户");
// 生成SQL: SELECT * FROM users WHERE age > 25

复杂操作支持 用户输入："将订单状态为pending的记录更新为completed"

String sql = sqlConverter.convert("将订单状态为pending的记录更新为completed");
// 生成SQL: UPDATE orders SET status = 'completed' WHERE status = 'pending'

安全校验机制

为防止 SQL 注入，需添加验证层：

public void validateSql(String sql) {
    if (sql.contains("DROP") || sql.contains("TRUNCATE")) {
        throw new SecurityException("危险操作被拦截");
    }
}

执行与结果返回

通过 JdbcTemplate 执行生成的 SQL：

@Autowired
private JdbcTemplate jdbcTemplate;

public List<Map<String, Object>> executeQuery(String naturalLanguage) {
    String sql = sqlConverter.convert(naturalLanguage);
    validateSql(sql);
    return jdbcTemplate.queryForList(sql);
}

性能优化建议

缓存高频查询的 SQL 转换结果
对大数据量查询添加 LIMIT 子句限制
使用连接池管理数据库连接

错误处理方案

捕获常见异常并提供自然语言反馈：

try {
    return executeQuery(userInput);
} catch (EmptyResultDataAccessException e) {
    return "未找到匹配数据";
} catch (DataAccessException e) {
    return "数据库操作失败，请检查查询条件";
}

扩展应用场景

结合 Spring Data REST 暴露自然语言 API 端点
集成到管理后台实现无代码查询
开发 CLI 工具支持命令行交互

该方案显著降低数据库操作的技术门槛，适合需要快速原型开发或非技术人员参与数据查询的场景。实际应用中需根据业务需求调整提示词模板和校验规则。

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