mirror of
https://github.com/zongzibinbin/MallChat.git
synced 2025-12-26 04:47:53 +08:00
openAI
This commit is contained in:
zhaoyuhang
parent
3218b37ffc
commit
fb90e98a4e
@ -36,6 +36,11 @@ public class RedisKey {
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*/
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public static final String USER_SUMMARY_STRING = "userSummary:uid_%d";
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/**
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* 用户AI聊天次数
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*/
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public static final String USER_CHAT_NUM = "userAIChatNum:uid_%d";
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public static String getKey(String key, Object... objects) {
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return BASE_KEY + String.format(key, objects);
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}
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@ -0,0 +1,16 @@
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package com.abin.mallchat.common.common.utils;
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import java.util.Calendar;
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import java.util.Date;
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public class DateUtils extends org.apache.commons.lang3.time.DateUtils {
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public static Long getEndTimeByToday() {
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Calendar instance = Calendar.getInstance();
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Date now = new Date();
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instance.setTime(now);
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instance.set(Calendar.HOUR_OF_DAY, 23);
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instance.set(Calendar.MINUTE, 59);
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instance.set(Calendar.SECOND, 59);
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return instance.getTime().getTime() - now.getTime();
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}
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}
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@ -12,7 +12,7 @@ mybatis-plus:
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spring:
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profiles:
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#运行的环境
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active: my-prod
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active: test
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application:
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name: mallchat
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datasource:
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@ -37,8 +37,8 @@ spring:
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database: 0
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# 连接超时时间
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timeout: 1800000
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# 设置密码
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password: ${mallchat.redis.password}
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# # 设置密码
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# password: ${mallchat.redis.password}
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lettuce:
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pool:
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# 最大阻塞等待时间，负数表示没有限制
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@ -62,4 +62,9 @@ wx:
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- appId: ${mallchat.wx.appId} # 第一个公众号的appid
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secret: ${mallchat.wx.secret} # 公众号的appsecret
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token: ${mallchat.wx.token} # 接口配置里的Token值
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aesKey: ${mallchat.wx.aesKey} # 接口配置里的EncodingAESKey值
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aesKey: ${mallchat.wx.aesKey} # 接口配置里的EncodingAESKey值
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openai:
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use-openai: true
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ai-user-id: xxxxx
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key: xxxxxxx
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proxy-url: https://xxxxxxx
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@ -38,6 +38,7 @@ import com.abin.mallchat.custom.chat.service.strategy.mark.MsgMarkFactory;
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import com.abin.mallchat.custom.chat.service.strategy.msg.AbstractMsgHandler;
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import com.abin.mallchat.custom.chat.service.strategy.msg.MsgHandlerFactory;
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import com.abin.mallchat.custom.chat.service.strategy.msg.RecallMsgHandler;
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import com.abin.mallchat.custom.openai.event.OpenAIEvent;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.beans.BeanUtils;
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import org.springframework.beans.factory.annotation.Autowired;
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@ -95,6 +96,7 @@ public class ChatServiceImpl implements ChatService {
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msgHandler.saveMsg(insert, request);
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//发布消息发送事件
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applicationEventPublisher.publishEvent(new MessageSendEvent(this, insert.getId()));
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applicationEventPublisher.publishEvent(new OpenAIEvent(this, insert.getId()));
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return insert.getId();
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}
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@ -66,7 +66,7 @@ public class TextMsgHandler extends AbstractMsgHandler {
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AssertUtil.equal(replyMsg.getRoomId(), request.getRoomId(), "只能回复相同会话内的消息");
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}
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if (CollectionUtil.isNotEmpty(body.getAtUidList())) {
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AssertUtil.isTrue(body.getAtUidList().size() > 10, "一次别艾特这么多人");
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AssertUtil.isFalse(body.getAtUidList().size() > 10, "一次别艾特这么多人");
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List<Long> atUidList = body.getAtUidList();
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Map<Long, User> batch = userInfoCache.getBatch(atUidList);
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AssertUtil.equal(atUidList.size(), batch.values().size(), "@用户不存在");
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@ -0,0 +1,92 @@
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package com.abin.mallchat.custom.openai.enums;
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import lombok.AllArgsConstructor;
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import lombok.Getter;
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import java.util.Arrays;
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import java.util.Map;
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import java.util.function.Function;
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import java.util.stream.Collectors;
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@AllArgsConstructor
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@Getter
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public enum OpenAIModelEnums {
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// chat
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GPT_35_TURBO("gpt-3.5-turbo", 3, 40000),
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GPT_35_TURBO_0301("gpt-3.5-turbo-0301", 3, 40000),
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GPT_35_TURBO_0613("gpt-3.5-turbo-0613", 3, 40000),
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GPT_35_TURBO_16K("gpt-3.5-turbo-16k", 3, 40000),
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GPT_35_TURBO_16K_0613("gpt-3.5-turbo-16k-0613", 3, 40000),
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// text
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ADA("ada", 60, 150000),
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ADA_CODE_SEARCH_CODE("ada-code-search-code", 60, 150000),
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ADA_CODE_SEARCH_TEXT("ada-code-search-text", 60, 150000),
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ADA_SEARCH_DOCUMENT("ada-search-document", 60, 150000),
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ADA_SEARCH_QUERY("ada-search-query", 60, 150000),
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ADA_SIMILARITY("ada-similarity", 60, 150000),
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BABBAGE("babbage", 60, 150000),
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BABBAGE_CODE_SEARCH_CODE("babbage-code-search-code", 60, 150000),
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BABBAGE_CODE_SEARCH_TEXT("babbage-code-search-text", 60, 150000),
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BABBAGE_SEARCH_DOCUMENT("babbage-search-document", 60, 150000),
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BABBAGE_SEARCH_QUERY("babbage-search-query", 60, 150000),
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BABBAGE_SIMILARITY("babbage-similarity", 60, 150000),
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CODE_DAVINCI_EDIT_001("code-davinci-edit-001", 20, 150000),
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CODE_SEARCH_ADA_CODE_001("code-search-ada-code-001", 60, 150000),
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CODE_SEARCH_ADA_TEXT_001("code-search-ada-text-001", 60, 150000),
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CODE_SEARCH_BABBAGE_CODE_001("code-search-babbage-code-001", 60, 150000),
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CODE_SEARCH_BABBAGE_TEXT_001("code-search-babbage-text-001", 60, 150000),
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CURIE("curie", 60, 150000),
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CURIE_INSTRUCT_BETA("curie-instruct-beta", 60, 150000),
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CURIE_SEARCH_DOCUMENT("curie-search-document", 60, 150000),
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CURIE_SEARCH_QUERY("curie-search-query", 60, 150000),
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CURIE_SIMILARITY("curie-similarity", 60, 150000),
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DAVINCI("davinci", 60, 150000),
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DAVINCI_INSTRUCT_BETA("davinci-instruct-beta", 60, 150000),
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DAVINCI_SEARCH_DOCUMENT("davinci-search-document", 60, 150000),
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DAVINCI_SEARCH_QUERY("davinci-search-query", 60, 150000),
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DAVINCI_SIMILARITY("davinci-similarity", 60, 150000),
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TEXT_ADA_001("text-ada-001", 60, 150000),
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TEXT_BABBAGE_001("text-babbage-001", 60, 150000),
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TEXT_CURIE_001("text-curie-001", 60, 150000),
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TEXT_DAVINCI_001("text-davinci-001", 60, 150000),
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TEXT_DAVINCI_002("text-davinci-002", 60, 150000),
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TEXT_DAVINCI_003("text-davinci-003", 60, 150000),
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TEXT_DAVINCI_EDIT_001("text-davinci-edit-001", 20, 150000),
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TEXT_EMBEDDING_ADA_002("text-embedding-ada-002", 60, 150000),
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TEXT_SEARCH_ADA_DOC_001("text-search-ada-doc-001", 60, 150000),
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TEXT_SEARCH_ADA_QUERY_001("text-search-ada-query-001", 60, 150000),
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TEXT_SEARCH_BABBAGE_DOC_001("text-search-babbage-doc-001", 60, 150000),
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TEXT_SEARCH_BABBAGE_QUERY_001("text-search-babbage-query-001", 60, 150000),
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TEXT_SEARCH_CURIE_DOC_001("text-search-curie-doc-001", 60, 150000),
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TEXT_SEARCH_CURIE_QUERY_001("text-search-curie-query-001", 60, 150000),
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TEXT_SEARCH_DAVINCI_DOC_001("text-search-davinci-doc-001", 60, 150000),
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TEXT_SEARCH_DAVINCI_QUERY_001("text-search-davinci-query-001", 60, 150000),
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TEXT_SIMILARITY_ADA_001("text-similarity-ada-001", 60, 150000),
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TEXT_SIMILARITY_BABBAGE_001("text-similarity-babbage-001", 60, 150000),
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TEXT_SIMILARITY_CURIE_001("text-similarity-curie-001", 60, 150000),
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TEXT_SIMILARITY_DAVINCI_001("text-similarity-davinci-001", 60, 150000);
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/**
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* 名字
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*/
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private final String name;
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/**
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* 每分钟请求数
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*/
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private final Integer RPM;
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/**
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* 每分钟令牌数
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*/
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private final Integer TPM;
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private static final Map<String, OpenAIModelEnums> cache;
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static {
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cache = Arrays.stream(OpenAIModelEnums.values()).collect(Collectors.toMap(OpenAIModelEnums::getName, Function.identity()));
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}
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public static OpenAIModelEnums of(String name) {
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return cache.get(name);
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}
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}
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@ -0,0 +1,14 @@
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package com.abin.mallchat.custom.openai.event;
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import lombok.Getter;
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import org.springframework.context.ApplicationEvent;
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@Getter
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public class OpenAIEvent extends ApplicationEvent {
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private Long msgId;
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public OpenAIEvent(Object source, Long msgId) {
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super(source);
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this.msgId = msgId;
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}
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}
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@ -0,0 +1,63 @@
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package com.abin.mallchat.custom.openai.event.listener;
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import com.abin.mallchat.common.chat.dao.MessageDao;
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import com.abin.mallchat.common.chat.domain.entity.Message;
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import com.abin.mallchat.custom.openai.event.OpenAIEvent;
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import com.abin.mallchat.custom.openai.service.IOpenAIService;
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import lombok.extern.slf4j.Slf4j;
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import org.apache.commons.lang3.StringUtils;
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import org.jetbrains.annotations.NotNull;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.stereotype.Component;
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import org.springframework.transaction.event.TransactionalEventListener;
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import static com.abin.mallchat.custom.openai.service.impl.OpenAIServiceImpl.MALL_CHAT_AI_NAME;
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/**
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* 是否AI回复监听器
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*
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* @author zhaoyuhang
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* @date 2023/06/29
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*/
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@Slf4j
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@Component
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public class OpenAIListener {
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@Autowired
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private IOpenAIService openAIService;
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@Autowired
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private MessageDao messageDao;
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@TransactionalEventListener(classes = OpenAIEvent.class, fallbackExecution = true)
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public void notifyAllOnline(@NotNull OpenAIEvent event) {
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Message message = messageDao.getById(event.getMsgId());
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if (ATedAI(message)) {
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openAIService.chat(message);
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}
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}
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/**
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* @return boolean
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* @了AI
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*/
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private boolean ATedAI(Message message) {
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/* 前端传@信息后取消注释 */
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// MessageExtra extra = message.getExtra();
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// if (extra == null) {
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// return false;
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// }
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// if (CollectionUtils.isEmpty(extra.getAtUidList())) {
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// return false;
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// }
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// if (!extra.getAtUidList().contains(OpenAIServiceImpl.AI_USER_ID)) {
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// return false;
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// }
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if (StringUtils.isBlank(message.getContent())) {
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return false;
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}
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return StringUtils.contains(message.getContent(), "@" + MALL_CHAT_AI_NAME)
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&& StringUtils.isNotBlank(message.getContent().replace(MALL_CHAT_AI_NAME, "").trim());
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}
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}
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@ -0,0 +1,11 @@
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package com.abin.mallchat.custom.openai.service;
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import com.abin.mallchat.common.chat.domain.entity.Message;
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import com.abin.mallchat.custom.chat.domain.vo.request.ChatMessageReq;
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public interface IOpenAIService {
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void chat(ChatMessageReq chatMessageReq, Long uid);
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void chat(Message message);
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}
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@ -0,0 +1,171 @@
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package com.abin.mallchat.custom.openai.service.impl;
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import cn.hutool.core.bean.BeanUtil;
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import cn.hutool.core.thread.NamedThreadFactory;
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import cn.hutool.http.HttpResponse;
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import cn.hutool.http.HttpUtil;
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import com.abin.mallchat.common.chat.domain.entity.Message;
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import com.abin.mallchat.common.chat.domain.enums.MessageTypeEnum;
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import com.abin.mallchat.common.common.constant.RedisKey;
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import com.abin.mallchat.common.common.exception.BusinessException;
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import com.abin.mallchat.common.common.handler.GlobalUncaughtExceptionHandler;
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import com.abin.mallchat.common.common.utils.DateUtils;
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import com.abin.mallchat.common.common.utils.RedisUtils;
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import com.abin.mallchat.custom.chat.domain.vo.request.ChatMessageReq;
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import com.abin.mallchat.custom.chat.domain.vo.request.msg.TextMsgReq;
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import com.abin.mallchat.custom.chat.service.ChatService;
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import com.abin.mallchat.custom.openai.enums.OpenAIModelEnums;
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import com.abin.mallchat.custom.openai.service.IOpenAIService;
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import com.abin.mallchat.custom.openai.utils.OpenAIUtils;
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import com.abin.mallchat.custom.user.domain.vo.response.user.UserInfoResp;
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import com.abin.mallchat.custom.user.service.UserService;
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import lombok.extern.slf4j.Slf4j;
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import org.apache.commons.lang3.StringUtils;
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import org.springframework.beans.factory.DisposableBean;
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import org.springframework.beans.factory.InitializingBean;
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import org.springframework.beans.factory.annotation.Autowired;
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import org.springframework.beans.factory.annotation.Value;
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import org.springframework.context.annotation.Description;
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import org.springframework.context.annotation.Lazy;
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import org.springframework.stereotype.Service;
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import java.util.Collections;
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import java.util.concurrent.ExecutorService;
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import java.util.concurrent.LinkedBlockingQueue;
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import java.util.concurrent.ThreadPoolExecutor;
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import java.util.concurrent.TimeUnit;
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@Slf4j
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@Service
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public class OpenAIServiceImpl implements IOpenAIService, DisposableBean, InitializingBean {
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private static ExecutorService EXECUTOR;
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@Value("${openai.use-openai:false}")
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private boolean USE_OPENAI;
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@Value("${openai.ai-user-id}")
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public Long AI_USER_ID;
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@Value("${openai.model.name:text-davinci-003}")
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private String modelName;
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@Value("${openai.key}")
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private String key;
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@Value("${openai.proxy-url:}")
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private String proxyUrl;
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@Value("${openai.limit:5}")
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private Integer limit;
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@Autowired
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private UserService userService;
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@Lazy
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@Autowired
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private ChatService chatService;
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public static String MALL_CHAT_AI_NAME;
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/**
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* 聊天
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*
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* @param chatMessageReq 提示词
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* @param uid 用户id
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*/
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@Deprecated
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@Override
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public void chat(ChatMessageReq chatMessageReq, Long uid) {
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TextMsgReq body = BeanUtil.toBean(chatMessageReq.getBody(), TextMsgReq.class);
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String content = body.getContent().replace(MALL_CHAT_AI_NAME, "").trim();
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EXECUTOR.execute(() -> {
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Long chatNum;
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if ((chatNum = userChatNumInrc(uid)) > limit) {
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answerMsg("你今天已经和我聊了" + chatNum + "次了，我累了，明天再聊吧", chatMessageReq.getRoomId(), uid);
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} else {
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chat(content, chatMessageReq.getRoomId(), uid);
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}
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});
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}
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@Override
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public void chat(Message message) {
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String content = message.getContent().replace(MALL_CHAT_AI_NAME, "").trim();
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Long roomId = message.getRoomId();
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Long uid = message.getFromUid();
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EXECUTOR.execute(() -> {
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Long chatNum;
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if ((chatNum = userChatNumInrc(uid)) > limit) {
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answerMsg("你今天已经和我聊了" + chatNum + "次了，我累了，明天再聊吧", roomId, uid);
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} else {
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chat(content, roomId, uid);
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}
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});
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}
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private Long userChatNumInrc(Long uid) {
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//todo:白名单
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return RedisUtils.inc(RedisKey.getKey(RedisKey.USER_CHAT_NUM, uid), DateUtils.getEndTimeByToday().intValue(), TimeUnit.MILLISECONDS);
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}
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private void chat(String content, Long roomId, Long uid) {
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HttpResponse response = OpenAIUtils.create(key)
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.proxyUrl(proxyUrl)
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.model(modelName)
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.prompt(content)
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.send();
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String text = OpenAIUtils.parseText(response);
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answerMsg(text, roomId, uid);
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}
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private void answerMsg(String text, Long roomId, Long uid) {
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ChatMessageReq answerReq = new ChatMessageReq();
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answerReq.setRoomId(roomId);
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answerReq.setMsgType(MessageTypeEnum.TEXT.getType());
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UserInfoResp userInfo = userService.getUserInfo(uid);
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TextMsgReq textMsgReq = new TextMsgReq();
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textMsgReq.setContent("@" + userInfo.getName() + " " + text);
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textMsgReq.setAtUidList(Collections.singletonList(uid));
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answerReq.setBody(textMsgReq);
|
||||
chatService.sendMsg(answerReq, AI_USER_ID);
|
||||
}
|
||||
|
||||
|
||||
@Override
|
||||
public void afterPropertiesSet() {
|
||||
if (!USE_OPENAI) {
|
||||
return;
|
||||
}
|
||||
if (StringUtils.isNotBlank(proxyUrl) && !HttpUtil.isHttp(proxyUrl) && !HttpUtil.isHttps(proxyUrl)) {
|
||||
throw new BusinessException("openai.proxy-url 配置错误");
|
||||
}
|
||||
OpenAIModelEnums modelEnum = OpenAIModelEnums.of(modelName);
|
||||
if (modelEnum == null) {
|
||||
throw new BusinessException("openai.model.name 配置错误");
|
||||
}
|
||||
Integer rpm = modelEnum.getRPM();
|
||||
EXECUTOR = new ThreadPoolExecutor(10, 10,
|
||||
0L, TimeUnit.MILLISECONDS,
|
||||
new LinkedBlockingQueue<>(rpm),
|
||||
new NamedThreadFactory("openAI-chat-gpt",
|
||||
null,
|
||||
false,
|
||||
new GlobalUncaughtExceptionHandler()),
|
||||
(r, executor) -> {
|
||||
throw new BusinessException("别问的太快了，我的脑子不够用了");
|
||||
});
|
||||
UserInfoResp userInfo = userService.getUserInfo(AI_USER_ID);
|
||||
if (userInfo == null) {
|
||||
throw new BusinessException("openai.ai-user-id 配置错误");
|
||||
}
|
||||
MALL_CHAT_AI_NAME = userInfo.getName();
|
||||
}
|
||||
|
||||
@Override
|
||||
public void destroy() throws Exception {
|
||||
EXECUTOR.shutdown();
|
||||
if (!EXECUTOR.awaitTermination(30, TimeUnit.SECONDS)) { //最多等30秒，处理不完就拉倒
|
||||
if (log.isErrorEnabled()) {
|
||||
log.error("Timed out while waiting for executor [{}] to terminate", EXECUTOR);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@ -0,0 +1,158 @@
|
||||
package com.abin.mallchat.custom.openai.utils;
|
||||
|
||||
import cn.hutool.http.HttpResponse;
|
||||
import cn.hutool.http.HttpUtil;
|
||||
import cn.hutool.json.JSONArray;
|
||||
import cn.hutool.json.JSONObject;
|
||||
import com.abin.mallchat.common.common.exception.BusinessException;
|
||||
import org.apache.commons.lang3.StringUtils;
|
||||
|
||||
import java.util.HashMap;
|
||||
import java.util.Map;
|
||||
|
||||
public class OpenAIUtils {
|
||||
|
||||
private static final String URL = "https://api.openai.com/v1/completions";
|
||||
|
||||
private String model = "text-davinci-003";
|
||||
|
||||
private final Map<String, String> headers;
|
||||
/**
|
||||
* 超时30秒
|
||||
*/
|
||||
private Integer timeout = 30 * 1000;
|
||||
/**
|
||||
* 参数用于指定生成文本的最大长度。
|
||||
* 它表示生成的文本中最多包含多少个 token。一个 token 可以是一个单词、一个标点符号或一个空格。
|
||||
*/
|
||||
private int maxTokens = 2048;
|
||||
/**
|
||||
* 用于控制生成文本的多样性。
|
||||
* 较高的温度会导致更多的随机性和多样性，但可能会降低生成文本的质量。默认值为 1，建议在 0.7 到 1.3 之间调整。
|
||||
*/
|
||||
private Object temperature = 1;
|
||||
/**
|
||||
* 用于控制生成文本的多样性。
|
||||
* 它会根据概率选择最高的几个单词，而不是选择概率最高的单词。默认值为 1，建议在 0.7 到 0.9 之间调整。
|
||||
*/
|
||||
private Object topP = 0.9;
|
||||
/**
|
||||
* 用于控制生成文本中重复单词的数量。
|
||||
* 较高的惩罚值会导致更少的重复单词，但可能会降低生成文本的流畅性。默认值为 0，建议在 0 到 2 之间调整。
|
||||
*/
|
||||
private Object frequencyPenalty = 0.0;
|
||||
/**
|
||||
* 用于控制生成文本中出现特定单词的数量。
|
||||
* 较高的惩罚值会导致更少的特定单词，但可能会降低生成文本的流畅性。默认值为 0，建议在 0 到 2 之间调整。
|
||||
*/
|
||||
private Object presencePenalty = 0.6;
|
||||
|
||||
/**
|
||||
* 提示词
|
||||
*/
|
||||
private String prompt;
|
||||
|
||||
private String proxyUrl;
|
||||
|
||||
public OpenAIUtils(String key) {
|
||||
HashMap<String, String> _headers_ = new HashMap<>();
|
||||
_headers_.put("Content-Type", "application/json");
|
||||
if (StringUtils.isBlank(key)) {
|
||||
throw new BusinessException("openAi key is blank");
|
||||
}
|
||||
_headers_.put("Authorization", "Bearer " + key);
|
||||
this.headers = _headers_;
|
||||
}
|
||||
|
||||
public static OpenAIUtils create(String key) {
|
||||
return new OpenAIUtils(key);
|
||||
}
|
||||
|
||||
public static String parseText(HttpResponse response) {
|
||||
return parseText(response.body());
|
||||
}
|
||||
|
||||
public static String parseText(String body) {
|
||||
JSONObject jsonObj = new JSONObject(body);
|
||||
JSONArray choicesArr = jsonObj.getJSONArray("choices");
|
||||
JSONObject choiceObj = choicesArr.getJSONObject(0);
|
||||
return choiceObj.getStr("text");
|
||||
}
|
||||
|
||||
public OpenAIUtils model(String model) {
|
||||
this.model = model;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils timeout(int timeout) {
|
||||
this.timeout = timeout;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils maxTokens(int maxTokens) {
|
||||
this.maxTokens = maxTokens;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils temperature(int temperature) {
|
||||
this.temperature = temperature;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils topP(int topP) {
|
||||
this.topP = topP;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils frequencyPenalty(int frequencyPenalty) {
|
||||
this.frequencyPenalty = frequencyPenalty;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils presencePenalty(int presencePenalty) {
|
||||
this.presencePenalty = presencePenalty;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils prompt(String prompt) {
|
||||
this.prompt = prompt;
|
||||
return this;
|
||||
}
|
||||
|
||||
public OpenAIUtils proxyUrl(String proxyUrl) {
|
||||
this.proxyUrl = proxyUrl;
|
||||
return this;
|
||||
}
|
||||
|
||||
public HttpResponse send() {
|
||||
JSONObject param = new JSONObject();
|
||||
param.set("model", model);
|
||||
param.set("prompt", prompt);
|
||||
param.set("max_tokens", maxTokens);
|
||||
param.set("temperature", temperature);
|
||||
param.set("top_p", topP);
|
||||
param.set("frequency_penalty", frequencyPenalty);
|
||||
param.set("presence_penalty", presencePenalty);
|
||||
return HttpUtil.createPost(StringUtils.isNotBlank(proxyUrl) ? proxyUrl : URL)
|
||||
.addHeaders(headers)
|
||||
.body(param.toString())
|
||||
.timeout(timeout)
|
||||
.execute();
|
||||
}
|
||||
|
||||
public static void main(String[] args) {
|
||||
HttpResponse send = OpenAIUtils.create("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")
|
||||
.timeout(30 * 1000)
|
||||
.prompt("Spring的启动流程是什么")
|
||||
.send();
|
||||
System.out.println("send = " + send);
|
||||
// JSON 数据
|
||||
// JSON 数据
|
||||
JSONObject jsonObj = new JSONObject(send.body());
|
||||
JSONArray choicesArr = jsonObj.getJSONArray("choices");
|
||||
JSONObject choiceObj = choicesArr.getJSONObject(0);
|
||||
String text = choiceObj.getStr("text");
|
||||
System.out.println("text = " + text);
|
||||
|
||||
}
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user