修改bug

@@ -63,7 +63,7 @@
         <artifactId>swagger-bootstrap-ui</artifactId>
         <artifactId>swagger-bootstrap-ui</artifactId>
         <version>${swagger-ui.version}</version>
         <version>${swagger-ui.version}</version>
     </dependency>
     </dependency>
-    </dependencies>
+</dependencies>
 
 
     <build>
     <build>
         <finalName>lh-alarm</finalName>
         <finalName>lh-alarm</finalName>

+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0"
+         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <parent>
+        <artifactId>Luhui</artifactId>
+        <groupId>com.zhonglai.luhui</groupId>
+        <version>1.0-SNAPSHOT</version>
+    </parent>
+    <modelVersion>4.0.0</modelVersion>
+
+    <artifactId>lh-openai</artifactId>
+
+    <dependencies>
+        <!-- spring-boot-devtools -->
+        <dependency>
+            <groupId>org.springframework.boot</groupId>
+            <artifactId>spring-boot-devtools</artifactId>
+            <optional>true</optional> <!-- 表示依赖不会传递 -->
+        </dependency>
+
+        <!-- Mysql驱动包 -->
+        <dependency>
+            <groupId>mysql</groupId>
+            <artifactId>mysql-connector-java</artifactId>
+        </dependency>
+
+        <!-- 核心模块-->
+        <dependency>
+            <groupId>com.zhonglai.luhui</groupId>
+            <artifactId>ruoyi-framework</artifactId>
+        </dependency>
+        <!-- 文档 -->
+        <dependency >
+            <groupId>io.springfox</groupId>
+            <artifactId>springfox-swagger2</artifactId>
+            <version>${swagger.version}</version>
+            <exclusions>
+                <exclusion>
+                    <groupId>io.swagger</groupId>
+                    <artifactId>swagger-models</artifactId>
+                </exclusion>
+                <exclusion>
+                    <groupId>com.google.guava</groupId>
+                    <artifactId>guava</artifactId>
+                </exclusion>
+            </exclusions>
+        </dependency>
+        <!--https://mvnrepository.com/artifact/io.swagger/swagger-models-->
+        <dependency>
+            <groupId>io.swagger</groupId>
+            <artifactId>swagger-models</artifactId>
+            <version>${swagger-models.version}</version>
+        </dependency>
+        <dependency>
+            <groupId>io.springfox</groupId>
+            <artifactId>springfox-swagger-ui</artifactId>
+            <version>${swagger.version}</version>
+        </dependency>
+        <!--&lt;!&ndash; https://mvnrepository.com/artifact/com.github.xiaoymin/swagger-bootstrap-ui &ndash;&gt;-->
+        <dependency>
+            <groupId>com.github.xiaoymin</groupId>
+            <artifactId>swagger-bootstrap-ui</artifactId>
+            <version>${swagger-ui.version}</version>
+        </dependency>
+
+        <dependency>
+            <groupId>com.theokanning.openai-gpt3-java</groupId>
+            <artifactId>service</artifactId>
+            <version>0.10.0</version>
+            <exclusions>
+                <exclusion>
+                    <groupId>com.squareup.okhttp3</groupId>
+                    <artifactId>okhttp</artifactId>
+                </exclusion>
+            </exclusions>
+        </dependency>
+        <dependency>
+            <groupId>com.squareup.okhttp3</groupId>
+            <artifactId>okhttp</artifactId>
+            <version>4.10.0</version>
+        </dependency>
+    </dependencies>
+
+    <build>
+        <finalName>lh-openai</finalName>
+        <plugins>
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-jar-plugin</artifactId>
+                <version>2.4</version>
+                <configuration>
+                    <archive>
+                        <!--
+                                   生成的jar中，不要包含pom.xml和pom.properties这两个文件
+                      -->
+                        <addMavenDescriptor>false</addMavenDescriptor>
+                        <manifest>
+                            <!--
+                                    是否要把第三方jar放到manifest的classpath中
+                        -->
+                            <addClasspath>true</addClasspath>
+
+                            <!--
+                                   生成的manifest中classpath的前缀，因为要把第三方jar放到lib目录下，所以classpath的前缀是lib/
+                               -->
+                            <classpathPrefix>lib/</classpathPrefix>
+                            <mainClass>com.zhonglai.luhui.alarm.AlarmApplication</mainClass>
+                        </manifest>
+                    </archive>
+                </configuration>
+            </plugin>
+
+            <!-- The configuration of maven-assembly-plugin -->
+            <plugin>
+                <groupId>org.apache.maven.plugins</groupId>
+                <artifactId>maven-assembly-plugin</artifactId>
+                <version>2.4</version>
+                <configuration>
+                    <descriptors>
+                        <descriptor>src/main/resources/package.xml</descriptor>
+                    </descriptors>
+                </configuration>
+                <executions>
+                    <execution>
+                        <id>make-assembly</id>
+                        <phase>package</phase>
+                        <goals>
+                            <goal>single</goal>
+                        </goals>
+                    </execution>
+                </executions>
+            </plugin>
+        </plugins>
+    </build>
+</project>

+package com.zhonglai.luhui.openai;
+
+import com.ruoyi.framework.aspectj.LogAspect;
+import com.ruoyi.framework.aspectj.RateLimiterAspect;
+import com.ruoyi.framework.config.FilterConfig;
+import com.ruoyi.framework.config.SecurityConfig;
+import com.ruoyi.framework.security.filter.JwtAuthenticationTokenFilter;
+import com.ruoyi.framework.security.handle.LogoutSuccessHandlerImpl;
+import com.ruoyi.system.login.service.LoginService;
+import com.ruoyi.system.login.service.TokenService;
+import com.ruoyi.system.service.impl.SysConfigServiceImpl;
+import com.ruoyi.system.service.impl.SysDictTypeServiceImpl;
+import com.ruoyi.system.service.impl.SysUserServiceImpl;
+import org.springframework.boot.SpringApplication;
+import org.springframework.boot.autoconfigure.SpringBootApplication;
+import org.springframework.boot.autoconfigure.jdbc.DataSourceAutoConfiguration;
+import org.springframework.context.annotation.ComponentScan;
+import org.springframework.context.annotation.FilterType;
+
+@ComponentScan(basePackages = {
+        "com.ruoyi.common",
+        "com.ruoyi.system",
+        "com.ruoyi.framework",
+        "com.zhonglai.luhui.openai.properties",
+        "com.zhonglai.luhui.openai.service",
+        "com.zhonglai.luhui.openai.controller"
+}
+
+)
+@SpringBootApplication(exclude = { DataSourceAutoConfiguration.class })
+public class OpenaiApplication {
+    public static void main(String[] args) {
+        SpringApplication.run(OpenaiApplication.class,args);
+        System.out.println("启动成功");
+    }
+}

+package com.zhonglai.luhui.openai.controller;
+
+import com.ruoyi.common.core.domain.Message;
+import com.ruoyi.common.core.domain.MessageCode;
+import com.theokanning.openai.completion.CompletionChoice;
+import com.zhonglai.luhui.openai.utils.OpenAiUtils;
+import io.swagger.annotations.Api;
+import io.swagger.annotations.ApiOperation;
+import org.springframework.web.bind.annotation.*;
+
+import java.util.List;
+
+@Api(tags = "chatGPT接口")
+@RestController
+@RequestMapping("/chatgpt")
+public class ChatGPTController {
+    @ApiOperation("与AI机器进行聊天")
+    @RequestMapping(value = "/aiChatbot",method = RequestMethod.POST)
+    public Message aiChatbot(@RequestBody String data)
+    {
+        List<CompletionChoice> list = OpenAiUtils.getAiChatbot(data);
+        return new Message(MessageCode.DEFAULT_SUCCESS_CODE,list);
+    }
+}

+package com.zhonglai.luhui.openai.pojos;
+
+
+/**
+ * 实体类
+ */
+public class OpenAi {
+    String id;
+    String name;
+    String desc;
+    String model;
+    // 提示模板
+    String prompt;
+    // 创新采样
+    Double temperature;
+    // 情绪采样
+    Double topP;
+    // 结果条数
+    Double n = 1d;
+    // 频率处罚系数
+    Double frequencyPenalty;
+    // 重复处罚系数
+    Double presencePenalty;
+    // 停用词
+    String stop;
+
+    public OpenAi() {
+    }
+
+    public OpenAi(String id, String name, String desc, String model, String prompt, Double temperature, Double topP, Double n, Double frequencyPenalty, Double presencePenalty, String stop) {
+        this.id = id;
+        this.name = name;
+        this.desc = desc;
+        this.model = model;
+        this.prompt = prompt;
+        this.temperature = temperature;
+        this.topP = topP;
+        this.n = n;
+        this.frequencyPenalty = frequencyPenalty;
+        this.presencePenalty = presencePenalty;
+        this.stop = stop;
+    }
+
+    public String getId() {
+        return id;
+    }
+
+    public void setId(String id) {
+        this.id = id;
+    }
+
+    public String getName() {
+        return name;
+    }
+
+    public void setName(String name) {
+        this.name = name;
+    }
+
+    public String getDesc() {
+        return desc;
+    }
+
+    public void setDesc(String desc) {
+        this.desc = desc;
+    }
+
+    public String getModel() {
+        return model;
+    }
+
+    public void setModel(String model) {
+        this.model = model;
+    }
+
+    public String getPrompt() {
+        return prompt;
+    }
+
+    public void setPrompt(String prompt) {
+        this.prompt = prompt;
+    }
+
+    public Double getTemperature() {
+        return temperature;
+    }
+
+    public void setTemperature(Double temperature) {
+        this.temperature = temperature;
+    }
+
+    public Double getTopP() {
+        return topP;
+    }
+
+    public void setTopP(Double topP) {
+        this.topP = topP;
+    }
+
+    public Double getN() {
+        return n;
+    }
+
+    public void setN(Double n) {
+        this.n = n;
+    }
+
+    public Double getFrequencyPenalty() {
+        return frequencyPenalty;
+    }
+
+    public void setFrequencyPenalty(Double frequencyPenalty) {
+        this.frequencyPenalty = frequencyPenalty;
+    }
+
+    public Double getPresencePenalty() {
+        return presencePenalty;
+    }
+
+    public void setPresencePenalty(Double presencePenalty) {
+        this.presencePenalty = presencePenalty;
+    }
+
+    public String getStop() {
+        return stop;
+    }
+
+    public void setStop(String stop) {
+        this.stop = stop;
+    }
+}

+package com.zhonglai.luhui.openai.properties;
+
+import com.zhonglai.luhui.openai.utils.OpenAiUtils;
+import org.springframework.beans.factory.InitializingBean;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Component;
+
+@Component
+public class OpenAiProperties implements InitializingBean {
+
+    @Value("${chatgpt.token}")
+    private String token; //秘钥
+    @Value("${chatgpt.timeout}")
+    private Integer timeout; //超时时间
+
+    // 设置属性时同时设置给OpenAiUtils
+    @Override
+    public void afterPropertiesSet()  {
+        OpenAiUtils.OPENAPI_TOKEN = token;
+        OpenAiUtils.TIMEOUT = timeout;
+    }
+}

+package com.zhonglai.luhui.openai.properties;
+
+import com.ruoyi.common.config.RuoYiConfig;
+import io.swagger.annotations.ApiOperation;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.context.annotation.Bean;
+import org.springframework.context.annotation.Configuration;
+import springfox.documentation.builders.ApiInfoBuilder;
+import springfox.documentation.builders.PathSelectors;
+import springfox.documentation.builders.RequestHandlerSelectors;
+import springfox.documentation.service.ApiInfo;
+import springfox.documentation.service.Contact;
+import springfox.documentation.spi.DocumentationType;
+import springfox.documentation.spring.web.plugins.Docket;
+import springfox.documentation.swagger2.annotations.EnableSwagger2;
+
+
+@Configuration
+@EnableSwagger2
+public class SwaggerConfig {
+    /** 系统基础配置 */
+    @Autowired
+    private RuoYiConfig ruoyiConfig;
+	@Bean
+    public Docket createRestApi() {
+        return new Docket(DocumentationType.SWAGGER_2)
+                .apiInfo(apiInfo())
+                .select()
+                .apis(RequestHandlerSelectors.withMethodAnnotation(ApiOperation.class))
+                .paths(PathSelectors.any())
+                .build();
+    }
+
+    /**
+     * 添加摘要信息
+     */
+    private ApiInfo apiInfo()
+    {
+        // 用ApiInfoBuilder进行定制
+        return new ApiInfoBuilder()
+                // 设置标题
+                .title("标题：chatgpt接口")
+                // 描述
+                .description("描述：用于chatgpt")
+                // 作者信息
+                .contact(new Contact(ruoyiConfig.getName(), null, null))
+                // 版本
+                .version("版本号:" + ruoyiConfig.getVersion())
+                .build();
+    }
+    
+}

+package com.zhonglai.luhui.openai.service;
+
+import com.ruoyi.common.exception.ServiceException;
+import com.ruoyi.common.utils.StringUtils;
+import com.ruoyi.system.login.dto.ApiLoginUser;
+import com.ruoyi.system.login.dto.Yu2leUserInfo;
+import com.ruoyi.system.login.dto.Yu2leUserLogin;
+import com.ruoyi.system.service.PublicService;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Autowired;
+import org.springframework.security.core.userdetails.UserDetails;
+import org.springframework.security.core.userdetails.UserDetailsService;
+import org.springframework.security.core.userdetails.UsernameNotFoundException;
+import org.springframework.stereotype.Service;
+
+@Service
+public class ChatgptDetailsServiceImpl implements UserDetailsService {
+    private static final Logger log = LoggerFactory.getLogger(ChatgptDetailsServiceImpl.class);
+    @Autowired
+    private PublicService publicService;
+    @Override
+    public UserDetails loadUserByUsername(String username) throws UsernameNotFoundException {
+        Yu2leUserLogin yu2leUserLogin = publicService.getObjectForTableName(Yu2leUserLogin.class,"loginName",username,"`liu_yu_le`.`user_login`");
+        Yu2leUserInfo yu2leUserInfo = publicService.getObjectForTableName(Yu2leUserInfo.class,"loginName",username,"`liu_yu_le`.`user_info`");;
+        if (StringUtils.isNull(yu2leUserLogin) || StringUtils.isNull(yu2leUserInfo))
+        {
+            log.info("登录用户：{} 不存在.", username);
+            throw new ServiceException("登录用户：" + username + " 不存在");
+        }
+        else if (1==yu2leUserInfo.getIsInvalid())
+        {
+            log.info("登录用户：{} 已被停用.", username);
+            throw new ServiceException("对不起，您的账号：" + username + " 已停用");
+        }
+        return new ApiLoginUser(yu2leUserInfo, yu2leUserLogin);
+    }
+}

+package com.zhonglai.luhui.openai.utils;
+
+import com.theokanning.openai.OpenAiService;
+import com.theokanning.openai.completion.CompletionChoice;
+import com.theokanning.openai.completion.CompletionRequest;
+import com.zhonglai.luhui.openai.pojos.OpenAi;
+import org.springframework.util.StringUtils;
+
+import java.util.*;
+
+/**
+ * 调用OpenAi的49中方法
+ */
+public class OpenAiUtils {
+    public static final Map<String, OpenAi> PARMS = new HashMap<>();
+
+    static {
+        PARMS.put("OpenAi01", new OpenAi("OpenAi01", "问&答", "依据现有知识库问&答", "text-davinci-003", "Q: %s\nA:", 0.0, 1.0, 1.0, 0.0, 0.0, "\n"));
+        PARMS.put("OpenAi02", new OpenAi("OpenAi02", "语法纠正", "将句子转换成标准的英语，输出结果始终是英文", "text-davinci-003", "%s", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi03", new OpenAi("OpenAi03", "内容概况", "将一段话，概况中心", "text-davinci-003", "Summarize this for a second-grade student:\n%s", 0.7, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi04", new OpenAi("OpenAi04", "生成OpenAi的代码", "一句话生成OpenAi的代码", "code-davinci-002", "\"\"\"\nUtil exposes the following:\nutil.openai() -> authenticates & returns the openai module, which has the following functions:\nopenai.Completion.create(\n    prompt=\"<my prompt>\", # The prompt to start completing from\n    max_tokens=123, # The max number of tokens to generate\n    temperature=1.0 # A measure of randomness\n    echo=True, # Whether to return the prompt in addition to the generated completion\n)\n\"\"\"\nimport util\n\"\"\"\n%s\n\"\"\"\n\n", 0.0, 1.0, 1.0, 0.0, 0.0, "\"\"\""));
+        PARMS.put("OpenAi05", new OpenAi("OpenAi05", "程序命令生成", "一句话生成程序的命令，目前支持操作系统指令比较多", "text-davinci-003", "Convert this text to a programmatic command:\n\nExample: Ask Constance if we need some bread\nOutput: send-msg `find constance` Do we need some bread?\n\n%s", 0.0, 1.0, 1.0, 0.2, 0.0, ""));
+        PARMS.put("OpenAi06", new OpenAi("OpenAi06", "语言翻译", "把一种语法翻译成其它几种语言", "text-davinci-003", "Translate this into %s:\n%s", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi07", new OpenAi("OpenAi07", "Stripe国际API生成", "一句话生成Stripe国际支付API", "code-davinci-002", "\"\"\"\nUtil exposes the following:\n\nutil.stripe() -> authenticates & returns the stripe module; usable as stripe.Charge.create etc\n\"\"\"\nimport util\n\"\"\"\n%s\n\"\"\"", 0.0, 1.0, 1.0, 0.0, 0.0, "\"\"\""));
+        PARMS.put("OpenAi08", new OpenAi("OpenAi08", "SQL语句生成", "依据上下文中的表信息，生成SQL语句", "code-davinci-002", "### %s SQL tables, 表字段信息如下:\n%s\n#\n### %s\n %s", 0.0, 1.0, 1.0, 0.0, 0.0, "# ;"));
+        PARMS.put("OpenAi09", new OpenAi("OpenAi09", "结构化生成", "对于非结构化的数据抽取其中的特征生成结构化的表格", "text-davinci-003", "A table summarizing, use Chinese:\n%s\n", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi10", new OpenAi("OpenAi10", "信息分类", "把一段信息继续分类", "text-davinci-003", "%s\n分类:", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi11", new OpenAi("OpenAi11", "Python代码解释", "把代码翻译成文字，用来解释程序的作用", "code-davinci-002", "# %s \n %s \n\n# 解释代码作用\n\n#", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi12", new OpenAi("OpenAi12", "文字转表情符号", "将文本编码成表情服务", "text-davinci-003", "转换文字为表情。\n%s：", 0.8, 1.0, 1.0, 0.0, 0.0, "\n"));
+        PARMS.put("OpenAi13", new OpenAi("OpenAi13", "时间复杂度计算", "求一段代码的时间复杂度", "text-davinci-003", "%s\n\"\"\"\n函数的时间复杂度是", 0.0, 1.0, 1.0, 0.0, 0.0, "\n"));
+        PARMS.put("OpenAi14", new OpenAi("OpenAi14", "程序代码翻译", "把一种语言的代码翻译成另外一种语言的代码", "code-davinci-002", "##### 把这段代码从%s翻译成%s\n### %s\n    \n   %s\n    \n### %s", 0.0, 1.0, 1.0, 0.0, 0.0, "###"));
+        PARMS.put("OpenAi15", new OpenAi("OpenAi15", "高级情绪评分", "支持批量列表的方式检查情绪", "text-davinci-003", "对下面内容进行情感分类:\n%s\"\n情绪评级:", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi16", new OpenAi("OpenAi16", "代码解释", "对一段代码进行解释", "code-davinci-002", "代码:\n%s\n\"\"\"\n上面的代码在做什么:\n1. ", 0.0, 1.0, 1.0, 0.0, 0.0, "\"\"\""));
+        PARMS.put("OpenAi17", new OpenAi("OpenAi17", "关键字提取", "提取一段文本中的关键字", "text-davinci-003", "抽取下面内容的关键字:\n%s", 0.5, 1.0, 1.0, 0.8, 0.0, ""));
+        PARMS.put("OpenAi18", new OpenAi("OpenAi18", "问题解答", "类似解答题", "text-davinci-003", "Q: %s\nA: ?", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi19", new OpenAi("OpenAi19", "广告设计", "给一个产品设计一个广告", "text-davinci-003", "为下面的产品创作一个创业广告，用于投放到抖音上：\n产品:%s.", 0.5, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi20", new OpenAi("OpenAi20", "产品取名", "依据产品描述和种子词语，给一个产品取一个好听的名字", "text-davinci-003", "产品描述: %s.\n种子词: %s.\n产品名称: ", 0.8, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi21", new OpenAi("OpenAi21", "句子简化", "把一个长句子简化成一个短句子", "text-davinci-003", "%s\nTl;dr: ", 0.7, 1.0, 1.0, 0.0, 1.0, ""));
+        PARMS.put("OpenAi22", new OpenAi("OpenAi22", "修复代码Bug", "自动修改代码中的bug", "code-davinci-002", "##### 修复下面代码的bug\n### %s\n %s\n###  %s\n", 0.0, 1.0, 1.0, 0.0, 0.0, "###"));
+        PARMS.put("OpenAi23", new OpenAi("OpenAi23", "表格填充数据", "自动为一个表格生成数据", "text-davinci-003", "spreadsheet ,%s rows:\n%s\n", 0.5, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi24", new OpenAi("OpenAi24", "语言聊天机器人", "各种开发语言的两天机器人", "code-davinci-002", "You: %s\n%s机器人:", 0.0, 1.0, 1.0, 0.5, 0.0, "You: "));
+        PARMS.put("OpenAi25", new OpenAi("OpenAi25", "机器学习机器人", "机器学习模型方面的机器人", "text-davinci-003", "You: %s\nML机器人:", 0.3, 1.0, 1.0, 0.5, 0.0, "You: "));
+        PARMS.put("OpenAi26", new OpenAi("OpenAi26", "清单制作", "可以列出各方面的分类列表，比如歌单", "text-davinci-003", "列出10%s:", 0.5, 1.0, 1.0, 0.52, 0.5, "11.0"));
+        PARMS.put("OpenAi27", new OpenAi("OpenAi27", "文本情绪分析", "对一段文字进行情绪分析", "text-davinci-003", "推断下面文本的情绪是积极的, 中立的, 还是消极的.\n文本: \"%s\"\n观点:", 0.0, 1.0, 1.0, 0.5, 0.0, ""));
+        PARMS.put("OpenAi28", new OpenAi("OpenAi28", "航空代码抽取", "抽取文本中的航空diam信息", "text-davinci-003", "抽取下面文本中的航空代码：\n文本：\"%s\"\n航空代码：", 0.0, 1.0, 1.0, 0.0, 0.0, "\n"));
+        PARMS.put("OpenAi29", new OpenAi("OpenAi29", "生成SQL语句", "无上下文，语句描述生成SQL", "text-davinci-003", "%s", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi30", new OpenAi("OpenAi30", "抽取联系信息", "从文本中抽取联系方式", "text-davinci-003", "从下面文本中抽取%s:\n%s", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi31", new OpenAi("OpenAi31", "程序语言转换", "把一种语言转成另外一种语言", "code-davinci-002", "#%s to %s:\n%s:%s\n\n%s:", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi32", new OpenAi("OpenAi32", "好友聊天", "模仿好友聊天", "text-davinci-003", "You: %s\n好友:", 0.5, 1.0, 1.0, 0.5, 0.0, "You:"));
+        PARMS.put("OpenAi33", new OpenAi("OpenAi33", "颜色生成", "依据描述生成对应颜色", "text-davinci-003", "%s:\nbackground-color: ", 0.0, 1.0, 1.0, 0.0, 0.0, ";"));
+        PARMS.put("OpenAi34", new OpenAi("OpenAi34", "程序文档生成", "自动为程序生成文档", "code-davinci-002", "# %s\n \n%s\n# 上述代码的详细、高质量文档字符串：\n\"\"\"", 0.0, 1.0, 1.0, 0.0, 0.0, "#\"\"\""));
+        PARMS.put("OpenAi35", new OpenAi("OpenAi35", "段落创作", "依据短语生成相关文短", "text-davinci-003", "为下面短语创建一个中文段:\n%s:\n", 0.5, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi36", new OpenAi("OpenAi36", "代码压缩", "把多行代码简单的压缩成一行", "code-davinci-002", "将下面%s代码转成一行:\n%s\n%s一行版本:", 0.0, 1.0, 1.0, 0.0, 0.0, ";"));
+        PARMS.put("OpenAi37", new OpenAi("OpenAi37", "故事创作", "依据一个主题创建一个故事", "text-davinci-003", "主题: %s\n故事创作:", 0.8, 1.0, 1.0, 0.5, 0.0, ""));
+        PARMS.put("OpenAi38", new OpenAi("OpenAi38", "人称转换", "第一人称转第3人称", "text-davinci-003", "把下面内容从第一人称转为第三人称 (性别女):\n%s\n", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi39", new OpenAi("OpenAi39", "摘要说明", "依据笔记生成摘要说明", "text-davinci-003", "将下面内容转换成将下%s摘要：\n%s", 0.0, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi40", new OpenAi("OpenAi40", "头脑风暴", "给定一个主题，让其生成一些主题相关的想法", "text-davinci-003", "头脑风暴一些关于%s的想法：", 0.6, 1.0, 1.0, 1.0, 1.0, ""));
+        PARMS.put("OpenAi41", new OpenAi("OpenAi41", "ESRB文本分类", "按照ESRB进行文本分类", "text-davinci-003", "Provide an ESRB rating for the following text:\\n\\n\\\"%s\"\\n\\nESRB rating:", 0.3, 1.0, 1.0, 0.0, 0.0, "\n"));
+        PARMS.put("OpenAi42", new OpenAi("OpenAi42", "提纲生成", "按照提示为相关内容生成提纲", "text-davinci-003", "为%s提纲:", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi43", new OpenAi("OpenAi43", "美食制作（后果自负）", "依据美食名称和材料生成美食的制作步骤", "text-davinci-003", "依据下面成分和美食，生成制作方法:\n%s\n成分:\n%s\n制作方法:", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi44", new OpenAi("OpenAi44", "AI聊天", "与AI机器进行聊天", "text-davinci-003", "Human: %s", 0.9, 1.0, 1.0, 0.0, 0.6, "Human:AI:"));
+        PARMS.put("OpenAi45", new OpenAi("OpenAi45", "摆烂聊天", "与讽刺机器进行聊天", "text-davinci-003", "Marv不情愿的回答问题.\nYou:%s\nMarv:", 0.5, 0.3, 1.0, 0.5, 0.0, ""));
+        PARMS.put("OpenAi46", new OpenAi("OpenAi46", "分解步骤", "把一段文本分解成几步来完成", "text-davinci-003", "为下面文本生成次序列表，并增加列表数子: \n%s\n", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi47", new OpenAi("OpenAi47", "点评生成", "依据文本内容自动生成点评", "text-davinci-003", "依据下面内容，进行点评:\n%s\n点评:", 0.5, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi48", new OpenAi("OpenAi48", "知识学习", "可以为学习知识自动解答", "text-davinci-003", "%s", 0.3, 1.0, 1.0, 0.0, 0.0, ""));
+        PARMS.put("OpenAi49", new OpenAi("OpenAi49", "面试", "生成面试题", "text-davinci-003", "创建10道%s相关的面试题（中文）：\n", 0.5, 1.0, 10.0, 0.0, 0.0, ""));
+    }
+
+    public static String OPENAPI_TOKEN = "";
+    public static Integer TIMEOUT = null;
+
+    /**
+     * 获取ai
+     *
+     * @param openAi
+     * @param prompt
+     * @return
+     */
+    public static List<CompletionChoice> getAiResult(OpenAi openAi, String prompt) {
+        if (TIMEOUT == null || TIMEOUT < 1000) {
+            TIMEOUT = 3000;
+        }
+        OpenAiService service = new OpenAiService(OPENAPI_TOKEN, TIMEOUT);
+        CompletionRequest.CompletionRequestBuilder builder = CompletionRequest.builder()
+                .model(openAi.getModel())
+                .prompt(prompt)
+                .temperature(openAi.getTemperature())
+                .maxTokens(1000)
+                .topP(openAi.getTopP())
+                .frequencyPenalty(openAi.getFrequencyPenalty())
+                .presencePenalty(openAi.getPresencePenalty());
+        if (!StringUtils.isEmpty(openAi.getStop())) {
+            builder.stop(Arrays.asList(openAi.getStop().split(",")));
+        }
+        CompletionRequest completionRequest = builder.build();
+        return service.createCompletion(completionRequest).getChoices();
+    }
+
+    /**
+     * 问答
+     *
+     * @param question
+     * @return
+     */
+    public static List<CompletionChoice> getQuestionAnswer(String question) {
+        OpenAi openAi = PARMS.get("OpenAi01");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question));
+    }
+
+    /**
+     * 语法纠错
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getGrammarCorrection(String text) {
+        OpenAi openAi = PARMS.get("OpenAi02");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 将一段话，概况中心
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getSummarize(String text) {
+        OpenAi openAi = PARMS.get("OpenAi03");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 一句话生成OpenAi的代码
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getOpenAiApi(String text) {
+        OpenAi openAi = PARMS.get("OpenAi04");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 一句话生成程序的命令，目前支持操作系统指令比较多
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getTextToCommand(String text) {
+        OpenAi openAi = PARMS.get("OpenAi05");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 把一种语法翻译成其它几种语言
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getTranslatesLanguages(String text, String translatesLanguages) {
+        if (StringUtils.isEmpty(translatesLanguages)) {
+            translatesLanguages = "  1. French, 2. Spanish and 3. English";
+        }
+        OpenAi openAi = PARMS.get("OpenAi06");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), translatesLanguages, text));
+    }
+
+    /**
+     * 一句话生成Stripe国际支付API
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getStripeApi(String text) {
+        OpenAi openAi = PARMS.get("OpenAi07");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+
+    /**
+     * 依据上下文中的表信息，生成SQL语句
+     *
+     * @param databaseType 数据库类型
+     * @param tables       上午依赖的表和字段 Employee(id, name, department_id)
+     * @param text         SQL描述
+     * @param sqlType      sql类型，比如SELECT
+     * @return
+     */
+    public static List<CompletionChoice> getStripeApi(String databaseType, List<String> tables, String text, String sqlType) {
+        OpenAi openAi = PARMS.get("OpenAi08");
+        StringJoiner joiner = new StringJoiner("\n");
+        for (int i = 0; i < tables.size(); i++) {
+            joiner.add("# " + tables);
+        }
+        return getAiResult(openAi, String.format(openAi.getPrompt(), databaseType, joiner.toString(), text, sqlType));
+    }
+
+    /**
+     * 对于非结构化的数据抽取其中的特征生成结构化的表格
+     *
+     * @param text 非结构化的数据
+     * @return
+     */
+    public static List<CompletionChoice> getUnstructuredData(String text) {
+        OpenAi openAi = PARMS.get("OpenAi09");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 把一段信息继续分类
+     *
+     * @param text 要分类的文本
+     * @return
+     */
+    public static List<CompletionChoice> getTextCategory(String text) {
+        OpenAi openAi = PARMS.get("OpenAi10");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 把一段信息继续分类
+     *
+     * @param codeType 代码类型，比如Python
+     * @param code     要解释的代码
+     * @return
+     */
+    public static List<CompletionChoice> getCodeExplain(String codeType, String code) {
+        OpenAi openAi = PARMS.get("OpenAi11");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), codeType, code));
+    }
+
+    /**
+     * 将文本编码成表情服务
+     *
+     * @param text 文本
+     * @return
+     */
+    public static List<CompletionChoice> getTextEmoji(String text) {
+        OpenAi openAi = PARMS.get("OpenAi12");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 求一段代码的时间复杂度
+     *
+     * @param code 代码
+     * @return
+     */
+    public static List<CompletionChoice> getTimeComplexity(String code) {
+        OpenAi openAi = PARMS.get("OpenAi13");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), code));
+    }
+
+
+    /**
+     * 把一种语言的代码翻译成另外一种语言的代码
+     *
+     * @param fromLanguage 要翻译的代码语言
+     * @param toLanguage   要翻译成的代码语言
+     * @param code         代码
+     * @return
+     */
+    public static List<CompletionChoice> getTranslateProgramming(String fromLanguage, String toLanguage, String code) {
+        OpenAi openAi = PARMS.get("OpenAi14");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), fromLanguage, toLanguage, fromLanguage, code, toLanguage));
+    }
+
+    /**
+     * 支持批量列表的方式检查情绪
+     *
+     * @param texts 文本
+     * @return
+     */
+    public static List<CompletionChoice> getBatchTweetClassifier(List<String> texts) {
+        OpenAi openAi = PARMS.get("OpenAi15");
+        StringJoiner stringJoiner = new StringJoiner("\n");
+        for (int i = 0; i < texts.size(); i++) {
+            stringJoiner.add((i + 1) + ". " + texts.get(i));
+        }
+        return getAiResult(openAi, String.format(openAi.getPrompt(), stringJoiner.toString()));
+    }
+
+    /**
+     * 对一段代码进行解释
+     *
+     * @param code 文本
+     * @return
+     */
+    public static List<CompletionChoice> getExplainCOde(String code) {
+        OpenAi openAi = PARMS.get("OpenAi16");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), code));
+    }
+
+    /**
+     * 提取一段文本中的关键字
+     *
+     * @param text 文本
+     * @return
+     */
+    public static List<CompletionChoice> getTextKeywords(String text) {
+        OpenAi openAi = PARMS.get("OpenAi17");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 事实回答答题
+     *
+     * @param text 文本
+     * @return
+     */
+    public static List<CompletionChoice> getFactualAnswering(String text) {
+        OpenAi openAi = PARMS.get("OpenAi18");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 给一个产品设计一个广告
+     *
+     * @param text 文本
+     * @return
+     */
+    public static List<CompletionChoice> getAd(String text) {
+        OpenAi openAi = PARMS.get("OpenAi19");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 依据产品描述和种子词语，给一个产品取一个好听的名字
+     *
+     * @param productDescription 产品描述
+     * @param seedWords          种子词语
+     * @return
+     */
+    public static List<CompletionChoice> getProductName(String productDescription, String seedWords) {
+        OpenAi openAi = PARMS.get("OpenAi20");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), productDescription, seedWords));
+    }
+
+    /**
+     * 把一个长句子简化成一个短句子
+     *
+     * @param text 长句子
+     * @return
+     */
+    public static List<CompletionChoice> getProductName(String text) {
+        OpenAi openAi = PARMS.get("OpenAi21");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 自动修改代码中的bug
+     *
+     * @param codeType 语言类型
+     * @param code     代码
+     * @return
+     */
+    public static List<CompletionChoice> getBugFixer(String codeType, String code) {
+        OpenAi openAi = PARMS.get("OpenAi22");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), codeType, code, codeType));
+    }
+
+    /**
+     * 自动为一个表格生成数据
+     *
+     * @param rows    生成的行数
+     * @param headers 数据表头，格式如：姓名| 年龄|性别|生日
+     * @return
+     */
+    public static List<CompletionChoice> getFillData(int rows, String headers) {
+        OpenAi openAi = PARMS.get("OpenAi23");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), rows, headers));
+    }
+
+    /**
+     * 各种开发语言的两天机器人
+     *
+     * @param question             你的问题
+     * @param programmingLanguages 语言 比如Java JavaScript
+     * @return
+     */
+    public static List<CompletionChoice> getProgrammingLanguageChatbot(String question, String programmingLanguages) {
+        OpenAi openAi = PARMS.get("OpenAi24");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question, programmingLanguages));
+    }
+
+    /**
+     * 机器学习模型方面的机器人
+     *
+     * @param question 你的问题
+     * @return
+     */
+    public static List<CompletionChoice> getMLChatbot(String question) {
+        OpenAi openAi = PARMS.get("OpenAi25");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question));
+    }
+
+    /**
+     * 可以列出各方面的分类列表，比如歌单
+     *
+     * @param text 清单描述
+     * @return
+     */
+    public static List<CompletionChoice> getListMaker(String text) {
+        OpenAi openAi = PARMS.get("OpenAi26");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 对一段文字进行情绪分析
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getTweetClassifier(String text) {
+        OpenAi openAi = PARMS.get("OpenAi27");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 抽取文本中的航空代码信息
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getAirportCodeExtractor(String text) {
+        OpenAi openAi = PARMS.get("OpenAi28");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 无上下文，语句描述生成SQL
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getSQL(String text) {
+        OpenAi openAi = PARMS.get("OpenAi29");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 从文本中抽取联系方式
+     *
+     * @param extractContent 抽取内容描述
+     * @param text
+     * @return 从下面文本中抽取邮箱和电话:\n教育行业A股IPO第一股（股票代码 003032）\n全国咨询/投诉热线：400-618-4000    举报邮箱:mc@itcast.cn
+     */
+    public static List<CompletionChoice> getExtractContactInformation(String extractContent, String text) {
+        OpenAi openAi = PARMS.get("OpenAi30");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), extractContent, text));
+    }
+
+    /**
+     * 把一种语言转成另外一种语言代码
+     *
+     * @param fromCodeType 当前代码类型
+     * @param toCodeType   转换的代码类型
+     * @param code
+     * @return
+     */
+    public static List<CompletionChoice> getTransformationCode(String fromCodeType, String toCodeType, String code) {
+        OpenAi openAi = PARMS.get("OpenAi31");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), fromCodeType, toCodeType, fromCodeType, code, toCodeType));
+    }
+
+    /**
+     * 模仿好友聊天
+     *
+     * @param question
+     * @return
+     */
+    public static List<CompletionChoice> getFriendChat(String question) {
+        OpenAi openAi = PARMS.get("OpenAi32");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question));
+    }
+
+    /**
+     * 依据描述生成对应颜色
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getMoodToColor(String text) {
+        OpenAi openAi = PARMS.get("OpenAi33");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 自动为程序生成文档
+     *
+     * @param codeType 语言
+     * @param code
+     * @return
+     */
+    public static List<CompletionChoice> getCodeDocument(String codeType, String code) {
+        OpenAi openAi = PARMS.get("OpenAi34");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), codeType, code));
+    }
+
+    /**
+     * 依据短语生成相关文短
+     *
+     * @param text 短语
+     * @return
+     */
+    public static List<CompletionChoice> getCreateAnalogies(String text) {
+        OpenAi openAi = PARMS.get("OpenAi35");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 把多行代码简单的压缩成一行
+     *
+     * @param codeType 语言
+     * @param code
+     * @return
+     */
+    public static List<CompletionChoice> getCodeLine(String codeType, String code) {
+        OpenAi openAi = PARMS.get("OpenAi36");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), codeType, code, codeType));
+    }
+
+    /**
+     * 依据一个主题创建一个故事
+     *
+     * @param topic 创作主题
+     * @return
+     */
+    public static List<CompletionChoice> getStory(String topic) {
+        OpenAi openAi = PARMS.get("OpenAi37");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), topic));
+    }
+
+    /**
+     * 第一人称转第3人称
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getStoryCreator(String text) {
+        OpenAi openAi = PARMS.get("OpenAi38");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 依据笔记生成摘要说明
+     *
+     * @param scene 生成的摘要场景
+     * @param note  记录的笔记
+     * @return
+     */
+    public static List<CompletionChoice> getNotesToSummary(String scene, String note) {
+        OpenAi openAi = PARMS.get("OpenAi39");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), note));
+    }
+
+    /**
+     * 给定一个主题，让其生成一些主题相关的想法
+     *
+     * @param topic 头脑风暴关键词
+     * @return
+     */
+    public static List<CompletionChoice> getIdeaGenerator(String topic) {
+        OpenAi openAi = PARMS.get("OpenAi40");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), topic));
+    }
+
+    /**
+     * 按照ESRB进行文本分类
+     *
+     * @param text 文本
+     * @return
+     */
+    public static List<CompletionChoice> getESRBRating(String text) {
+        OpenAi openAi = PARMS.get("OpenAi41");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 按照提示为相关内容生成提纲
+     *
+     * @param text 场景，比如 数据库软件生成大学毕业论文
+     * @return
+     */
+    public static List<CompletionChoice> getEssayOutline(String text) {
+        OpenAi openAi = PARMS.get("OpenAi42");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 依据美食名称和材料生成美食的制作步骤
+     *
+     * @param name        美食名称
+     * @param ingredients 美食食材
+     * @return
+     */
+    public static List<CompletionChoice> getRecipeCreator(String name, List<String> ingredients) {
+        OpenAi openAi = PARMS.get("OpenAi43");
+        StringJoiner joiner = new StringJoiner("\n");
+        for (String ingredient : ingredients) {
+            joiner.add(ingredient);
+        }
+        return getAiResult(openAi, String.format(openAi.getPrompt(), name, joiner.toString()));
+    }
+
+    /**
+     * 与AI机器进行聊天
+     *
+     * @param question
+     * @return
+     */
+    public static List<CompletionChoice> getAiChatbot(String question) {
+        OpenAi openAi = PARMS.get("OpenAi44");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question));
+    }
+
+    /**
+     * 与讽刺机器进行聊天，聊天的机器人是一种消极情绪
+     *
+     * @param question
+     * @return
+     */
+    public static List<CompletionChoice> getMarvChatbot(String question) {
+        OpenAi openAi = PARMS.get("OpenAi45");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), question));
+    }
+
+    /**
+     * 把一段文本分解成几步来完成
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getTurnDirection(String text) {
+        OpenAi openAi = PARMS.get("OpenAi46");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 依据文本内容自动生成点评
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getReviewCreator(String text) {
+        OpenAi openAi = PARMS.get("OpenAi47");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 可以为学习知识自动解答
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getStudyNote(String text) {
+        OpenAi openAi = PARMS.get("OpenAi48");
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+    /**
+     * 生成面试题
+     *
+     * @param text
+     * @return
+     */
+    public static List<CompletionChoice> getInterviewQuestion(String text) {
+        OpenAi openAi = PARMS.get("OpenAi49");
+        System.out.println(String.format(openAi.getPrompt(), text));
+        return getAiResult(openAi, String.format(openAi.getPrompt(), text));
+    }
+
+}

+# 数据源配置
+spring:
+    datasource:
+        type: com.alibaba.druid.pool.DruidDataSource
+        driverClassName: com.mysql.cj.jdbc.Driver
+        druid:
+            # 主库数据源
+            master:
+                url: jdbc:mysql://rm-wz9740un21f09iokuao.mysql.rds.aliyuncs.com:3306/mqtt_broker?useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&useSSL=true&serverTimezone=GMT%2B8
+                username: luhui
+                password: Luhui586
+            # 从库数据源
+            slave:
+                # 从数据源开关/默认关闭
+                enabled: false
+                url: 
+                username: 
+                password: 
+            # 初始连接数
+            initialSize: 5
+            # 最小连接池数量
+            minIdle: 10
+            # 最大连接池数量
+            maxActive: 20
+            # 配置获取连接等待超时的时间
+            maxWait: 60000
+            # 配置间隔多久才进行一次检测，检测需要关闭的空闲连接，单位是毫秒
+            timeBetweenEvictionRunsMillis: 60000
+            # 配置一个连接在池中最小生存的时间，单位是毫秒
+            minEvictableIdleTimeMillis: 300000
+            # 配置一个连接在池中最大生存的时间，单位是毫秒
+            maxEvictableIdleTimeMillis: 900000
+            # 配置检测连接是否有效
+            validationQuery: SELECT 1 FROM DUAL
+            testWhileIdle: true
+            testOnBorrow: false
+            testOnReturn: false
+            webStatFilter: 
+                enabled: true
+            statViewServlet:
+                enabled: true
+                # 设置白名单，不填则允许所有访问
+                allow:
+                url-pattern: /druid/*
+                # 控制台管理用户名和密码
+                login-username: ruoyi
+                login-password: 123456
+            filter:
+                stat:
+                    enabled: true
+                    # 慢SQL记录
+                    log-slow-sql: true
+                    slow-sql-millis: 1000
+                    merge-sql: true
+                wall:
+                    config:
+                        multi-statement-allow: true

+# 项目相关配置
jhlt:
  # 名称
  name: zhonglai
  # 版本
  version: 3.8.2
  # 版权年份
  copyrightYear: 2022
  # 获取ip地址开关
  addressEnabled: false

# 开发环境配置
server:
  # 服务器的HTTP端口，默认为8080
  port: 8082
  servlet:
    # 应用的访问路径
    context-path: /
  tomcat:
    # tomcat的URI编码
    uri-encoding: UTF-8
    # 连接数满后的排队数，默认为100
    accept-count: 1000
    threads:
      # tomcat最大线程数，默认为200
      max: 800
      # Tomcat启动初始化的线程数，默认值10
      min-spare: 100

# 日志配置
logging:
  level:
    com.ruoyi: debug
    org.springframework: warn

# Spring配置
spring:
  # 资源信息
  messages:
    # 国际化资源文件路径
    basename: i18n/messages
  profiles:
    active: druid
  # 文件上传
  servlet:
    multipart:
      # 单个文件大小
      max-file-size:  10MB
      # 设置总上传的文件大小
      max-request-size:  20MB
  # 服务模块
  devtools:
    restart:
      # 热部署开关
      enabled: true

  # redis 配置
  redis:
    # 地址
    host: 47.112.163.61
    # 端口，默认为6379
    port: 9527
    # 数据库索引
    database: 1
    # 密码
    password: Luhui586
    # 连接超时时间
    timeout: 10s
    lettuce:
      pool:
        # 连接池中的最小空闲连接
        min-idle: 0
        # 连接池中的最大空闲连接
        max-idle: 8
        # 连接池的最大数据库连接数
        max-active: 8
        # #连接池最大阻塞等待时间（使用负值表示没有限制）
        max-wait: -1ms
# token配置
token:
  # 令牌自定义标识
  header: Authorization
  # 令牌密钥
  secret: abcdefghijklmnopqrstuvwxyz
  # 令牌有效期（默认30分钟）
  expireTime: 1440
  rediskey: lh-openai

# MyBatis配置
mybatis:
  # 搜索指定包别名
  typeAliasesPackage: com.ruoyi.**.domain
  # 配置mapper的扫描，找到所有的mapper.xml映射文件
  mapperLocations: classpath*:mapper/**/*Mapper.xml
  # 加载全局的配置文件
  configLocation: classpath:mybatis/mybatis-config.xml

# PageHelper分页插件
pagehelper:
  helperDialect: mysql
  supportMethodsArguments: true
  params: count=countSql


# Swagger配置
swagger:
  # 是否开启swagger
  enabled: true
  # 请求前缀
  pathMapping: /dev-api

# 防止XSS攻击
xss:
  # 过滤开关
  enabled: true
  # 排除链接（多个用逗号分隔）
  excludes: /system/notice
  # 匹配链接
  urlPatterns: /system/*,/monitor/*,/tool/*

mqtt:
  client:
    device_life: 180

# NameServer地址
rocketmq:
  name-server: 47.115.144.179:9876
  # 默认的消息组
  producer:
    group: deviceCommand
    send-message-timeout: 30000
    send-topic: lh-chat-gpt
    send-tags: 1

sys:
  ## // 对于登录login 注册register 验证码captchaImage 允许匿名访问
  antMatchers: /login,/register,/captchaImage,/getCacheObject,/v2/api-docs,/chatgpt/aiChatbot

chatgpt:
  token: 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
  timeout: 5000

+{
+  "userAgent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/109.0.0.0 Safari/537.36",
+  "cfClearance": "TQGfn7M2Bcs8orogGzH3W.IPzJT3K_qJ9l_71ohooho-1676276962-0-1-f17cd819.14bb9dea.a67d87f9-160",
+  "session_token" : "eyJhbGciOiJkaXIiLCJlbmMiOiJBMjU2R0NNIn0..l1ZTOzatjL-w2_7B.JTf72KXAHoaYza4pYgzsWIhYNzhw24i86YEt8WQ12lDyqWybWXPVzgcOf2iYMhe7LqIqo8KoDM8HxxqSarUjxLVuJ2pL4wrri_9AincvR2phvXY_51O-QKSesBVHgGgh_rnv9Vlgpcjw2_k5a9p6jC9kf2zB7qFFArNo5b3Y19hZlfSkPgxJVT_cSfQH9pEq93HvJJjwGLzoNybF8I-zuEtSVTZ1iWvXzvH-wvLwxP8i97OSowzhhyygtU_sP6se5f54zG0_ElVGCHcXxggT2-qREqMSUyNDq0rv4chfWZengBXw2CpkzhF_uA1C-SPSrHY0Mn-KER4W279gnjMYwQgt886E31Euo9c_uG-eljD2NV9lgRJdSxzG_SREqkp9ubYq_3UYFeLwE_oUt61ii88ND-mTBRf2kVD3YCZne1Y-xDTHutdqNCNZJJPI2Zq5aNObKU1BCrp3PCCDMmjGSfhg-HdZdqeE5rXCHBXcEE2HrGbRLtylXYrYy5ttVeHZH7OKDyBaCC2lfXK1nFjvtLigVfJlXJF5lnVhIlFQe-kxjro3NUqw4RjdGoA7SJi0zpsAOB1Y7cY4Qb2WC_vjD5OBSNHceOox3WDkQt8LA-E4_PqhnBvAOYnaPBbX4eJT836OTiy12FhxnOiKxQLO9xdMnYoV3P9g2wkPqAJb5lWGYN_GqJIgiuV9Z9zN3R5N6WSryYOwzAXd3ocYODexh4U19T8JVWjxL7lurv-qBtr2wZPDNBS8U2y5sp49EgTnMswiqUnB624m7oFpgukiY9ZtEootaKEUk876-MVN5WeWOx2kQNL6ptNvhFaaqCVr6iQzrwMxYUiz_A1NhRVoO2gmYvWuC7Hxu28qwzFOubY9JRoOto-EPeqWxy9s9xmJ_19xHBpV2ZbGzPx-iwOLK_HWGiPScgAL6enWpoxWJ0XnEhEL5pghLcEuz9NAIzwVxsvLgslmkaTIFsTyP0CssyIJWv7oB75_cPGv3QqOI76Hz8A7J7C27hNKVy0f6XHoACFY6cyXx0jMYlOJW3e5GCv03Ht6SfvZPs8gNwpAuTz7JF0VliozvDLx7CM5SrBIt_iJnUZ_RM_8GBmorR1KThMtKDuvfkFNZN9dRPDVhMt7AGpZlKoJpADxH9lB7srNVSSr95PnZmsz4zwep8m_yYM9yjMTiIDn0dJifaEe_NH1Yda86yXTxhqAdD8j7ZbqvGGl75W_Ru-kvuB6hvE6PWy_6_IxwHrrDSwELjPwpgyacpJ3e2mGwAP1pkozJLWRJJkTlD-CR-PeBIhiFKk0FuKdXqnxtk4TghB7yqpUE25fLAhFu2yRNlR9jyXRPc8_mUWIyX3fcS0QDlaUY6YYGu5RlaomW5MztW80ij_h3YSObiLJbRjZe4bUWC7-p48a2YMOlDLIq6OcsXKd4ToBO3sFbnsmKUDqTt4TdU-prLwRCs1rqeRY1--vjGb8Zlju0T1-JrSJ4UimWm9CcFMz4JvuMXieVEKQ4TlVKseKM1t7jkNZmdBl4eoJth1lJvvVhlYTduxA8mumZAYjnCb-IT1pmKOxJkKtdjHwfCfEp7Jb4NcGrjfvMCOJzIyzM8GCf7gz8J-701g-BCRLPFQvER_t5pF6Re6GO8B3fHtrBQP8jxJNmM5yYl3YLFbWcYpNRBCMbuyIY88z4ALZ2Y-aXhkdTCX-_nVUDoz5PqEb20S7HJ6nkLHpNf9L95AZsZGfww9cfU5YjJs-8COD5ScOltZdEeTfUY2Q6qeM6N3p3wIREGKM6cqGFTyME1pPScNz-3ld0Fc5w3XHlU_o_DRt0TS8WMEG2chUtECsCy2M2J9Kytd2IOQLTSDIhGSCv6syiv8jVSUKThi3aQxdSk-t-cDWe9HjyIjdZ1lh9oNUa2-o7XKGg43TOgnUNUkHAEgfhD8LUPlwqUxJ6a0BDRltgVYnH7vGgPukiKXE-Li7Ks_HGgQodQowAucB9WKtkjdvU4iAtfKgcZXawci-vWM4EKLL8bpbR2MVUqDs7ie_d-Qzcxc9g_qEtWlByiil4zNUmwU3XGHp4nSHopWD1TiDZPDw5XgaXpAOukwFmrMzzvBE50uSowubbW1hbcKjVhmlZGgG6s0rwMwLugWio1tD-FJ4UgoaKxY65_j8vZhmuNZv_uIRgUHyAfJ2O3v-VBMmIHwrtfwUE-uHdCwW-RnjsGlxAI7sSKHpRV736pqukeC_XGEshq2Zv13S3Lt0MzL02P34kV3RD7n2OealEyxsuk_uexQo6DshiWw60pEgPwc12A7cYSWQODD7vJnkjXlFUPykNmqKSBTf1jhmIUWkEQBolEe7GjCb5YpZl5CZLiEN6v6WlOGOjW-o5UgT_egb7N4gu4Tj-6tv5PAZ3-lf8PUDzJ2reVhYkp_ToKdZ96aOhDQ7PFAqBYDc8A8om-zhF5A_zOeJmgAYEP3DNqE9P-PvC-1tn_kV99pfHD2ciVBXONCillWYLam1oOA3n2ABrHxvMg.0phK2SHDerfwz7VPG4rzhQ"
+}

+<?xml version="1.0" encoding="UTF-8" ?>
+<!DOCTYPE configuration
+PUBLIC "-//mybatis.org//DTD Config 3.0//EN"
+"http://mybatis.org/dtd/mybatis-3-config.dtd">
+<configuration>
+    <!-- 全局参数 -->
+    <settings>
+        <!-- 使全局的映射器启用或禁用缓存 -->
+        <setting name="cacheEnabled"             value="true"   />
+        <!-- 允许JDBC 支持自动生成主键 -->
+        <setting name="useGeneratedKeys"         value="true"   />
+        <!-- 配置默认的执行器.SIMPLE就是普通执行器;REUSE执行器会重用预处理语句(prepared statements);BATCH执行器将重用语句并执行批量更新 -->
+        <setting name="defaultExecutorType"      value="SIMPLE" />
+		<!-- 指定 MyBatis 所用日志的具体实现 -->
+        <setting name="logImpl"                  value="SLF4J"  />
+        <!-- 使用驼峰命名法转换字段 -->
+		<!-- <setting name="mapUnderscoreToCamelCase" value="true"/> -->
+	</settings>
+	
+</configuration>

+<?xml version="1.0" encoding="UTF-8"?>
+
+<assembly>  
+    <id>bin</id>  
+    <!-- 最终打包成一个用于发布的zip文件 -->
+    <formats>
+        <format>zip</format>  
+    </formats>  
+  
+    <!-- Adds dependencies to zip package under lib directory -->  
+    <dependencySets>  
+        <dependencySet>  
+            <!-- 
+               不使用项目的artifact，第三方jar不要解压，打包进zip文件的lib目录 
+           -->  
+            <useProjectArtifact>false</useProjectArtifact>  
+            <outputDirectory>lib</outputDirectory>  
+            <unpack>false</unpack>  
+        </dependencySet>
+    </dependencySets>  
+  
+    <fileSets>  
+        <!-- 把项目相关的说明文件，打包进zip文件的根目录 -->  
+        <fileSet>  
+            <directory>${project.basedir}</directory>  
+            <outputDirectory>/</outputDirectory>  
+            <includes>  
+                <include>README*</include>  
+                <include>LICENSE*</include>  
+                <include>NOTICE*</include>  
+            </includes>  
+        </fileSet>  
+
+        <!-- 把项目的配置文件，打包进zip文件的config目录 -->
+        <fileSet>
+            <directory>${project.basedir}\src\main\resources\configs</directory>
+            <outputDirectory>../configs</outputDirectory>
+            <includes>
+                <include>*.properties</include>
+            </includes>
+        </fileSet>
+
+        <!-- 把项目的配置文件，提出来 -->
+        <fileSet>
+            <directory>${project.basedir}\src\main\resources</directory>
+            <outputDirectory>/</outputDirectory>
+            <includes>
+                <include>*.properties</include>
+                <include>*.yml</include>
+            </includes>
+        </fileSet>
+
+        <!-- 把项目的脚本文件目录（ src/main/scripts ）中的启动脚本文件，打包进zip文件的跟目录 -->
+        <fileSet>  
+            <directory>${project.basedir}\bin</directory>  
+            <outputDirectory></outputDirectory>  
+            <includes>  
+                <include>start.*</include> 
+                <include>stop.*</include>  
+            </includes>  
+        </fileSet>  
+          
+        <!-- 把项目自己编译出来的jar文件，打包进zip文件的根目录 -->  
+        <fileSet>  
+            <directory>${project.build.directory}</directory>  
+            <outputDirectory></outputDirectory>  
+            <includes>  
+                <include>*.jar</include>  
+            </includes>  
+        </fileSet>  
+    </fileSets>  
+</assembly>  

@@ -19,6 +19,7 @@
         <module>lh-central-control</module>
         <module>lh-central-control</module>
         <module>lh-backups</module>
         <module>lh-backups</module>
         <module>lh-alarm</module>
         <module>lh-alarm</module>
+        <module>lh-openai</module>
     </modules>
     </modules>
 
 
     <packaging>pom</packaging>
     <packaging>pom</packaging>