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1 添加依赖
<!-- 导入openai依赖 -->
<dependency>
<groupId>com.theokanning.openai-gpt3-java</groupId>
<artifactId>client</artifactId>
<version>0.8.1</version>
</dependency>2 创建相关文件
2.1 实体类:OpenAi.java
package com.wkf.workrecord.tools.openai;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
/**
* @author wuKeFan
* @date 2023-02-10 15:40:22
*/
@Data
@NoArgsConstructor
@AllArgsConstructor
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;
}2.2 配置类:OpenAiProperties.java
package com.wkf.workrecord.tools.openai;
import lombok.Data;
import org.springframework.beans.factory.InitializingBean;
import org.springframework.boot.context.properties.ConfigurationProperties;
/**
* @author wuKeFan
* @date 2023-02-10 15:25:32
*/
@Data
@ConfigurationProperties(prefix = "openai")
public class OpenAiProperties implements InitializingBean {
// 秘钥
String token;
// 超时时间
Integer timeout;
// 设置属性时同时设置给OpenAiUtils
@Override
public void afterPropertiesSet() throws Exception {
OpenAiUtils.OPENAPI_TOKEN = token;
OpenAiUtils.TIMEOUT = timeout;
}
}2.3 核心业务逻辑OpenAiUtils.java
package com.wkf.workrecord.tools.openai;
import com.theokanning.openai.OpenAiService;
import com.theokanning.openai.completion.CompletionChoice;
import com.theokanning.openai.completion.CompletionRequest;
import org.springframework.util.StringUtils;
import java.util.*;
/**
* @author wuKeFan
* @date 2023-02-10 15:32:18
*/
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
A:", 0.0, 1.0, 1.0, 0.0, 0.0, "
"));
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:
%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", """"
Util exposes the following:
util.openai() -> authenticates & returns the openai module, which has the following functions:
openai.Completion.create(
prompt="<my prompt>", # The prompt to start completing from
max_tokens=123, # The max number of tokens to generate
temperature=1.0 # A measure of randomness
echo=True, # Whether to return the prompt in addition to the generated completion
)
"""
import util
"""
%s
"""
", 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:
Example: Ask Constance if we need some bread
Output: send-msg `find constance` Do we need some bread?
%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:
%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", """"
Util exposes the following:
util.stripe() -> authenticates & returns the stripe module; usable as stripe.Charge.create etc
"""
import util
"""
%s
"""", 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:
%s
#
### %s
%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:
%s
", 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
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
%s
# 解释代码作用
#", 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。
%s：", 0.8, 1.0, 1.0, 0.0, 0.0, "
"));
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
"""
函数的时间复杂度是", 0.0, 1.0, 1.0, 0.0, 0.0, "
"));
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
### %s
%s
### %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:
%s"
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:
%s
"""
上面的代码在做什么:
1. ", 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:
%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
A: ?", 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：
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.
种子词: %s.
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
Tl;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
### %s
%s
### %s
", 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:
%s
", 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
%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
ML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.
文本: "%s"
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：
文本："%s"
航空代码：", 0.0, 1.0, 1.0, 0.0, 0.0, "
"));
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:
%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:
%s:%s
%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
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:
background-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
%s
# 上述代码的详细、高质量文档字符串：
"""", 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:
%s:
", 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:
%s
%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
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):
%s
", 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：
%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, "
"));
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:
%s
成分:
%s
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.
You:%s
Marv:", 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:
%s
", 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:
%s
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）：
", 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("
");
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("
");
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));
}
/**
&
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