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IESExtension/src/main/java/cn/teammodel/service/impl/ChatMessageServiceImpl.java

270 lines
11 KiB

package cn.teammodel.service.impl;
import cn.hutool.core.lang.UUID;
import cn.teammodel.ai.SparkGptClient;
import cn.teammodel.ai.SseHelper;
import cn.teammodel.ai.cache.HistoryCache;
import cn.teammodel.ai.domain.SparkChatRequestParam;
import cn.teammodel.ai.listener.SparkGptStreamListener;
import cn.teammodel.common.ErrorCode;
import cn.teammodel.common.PK;
import cn.teammodel.config.exception.ServiceException;
import cn.teammodel.model.entity.ai.ChatApp;
import cn.teammodel.repository.ChatAppRepository;
import cn.teammodel.repository.ChatSessionRepository;
import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
import cn.teammodel.model.entity.User;
import cn.teammodel.model.entity.ai.ChatSession;
import cn.teammodel.security.utils.SecurityUtil;
import cn.teammodel.service.ChatMessageService;
import cn.teammodel.utils.RepositoryUtil;
import com.azure.cosmos.models.CosmosPatchOperations;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.ObjectUtils;
import org.apache.commons.lang3.StringUtils;
import org.springframework.stereotype.Service;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;
import javax.annotation.Resource;
import java.time.Instant;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
/**
* @author winter
* @create 2023-12-18 15:20
*/
@Service
@Slf4j
public class ChatMessageServiceImpl implements ChatMessageService {
@Resource
private SparkGptClient sparkGptClient;
@Resource
private ChatSessionRepository chatSessionRepository;
@Resource
private ChatAppRepository chatAppRepository;
@Override
public SseEmitter chatCompletion(ChatCompletionReqDto chatCompletionReqDto, String userId) {
// 目前仅使用讯飞星火大模型
String appId = chatCompletionReqDto.getAppId();
SseEmitter sseEmitter;
if (StringUtils.isEmpty(appId)) {
sseEmitter = completionBySession(chatCompletionReqDto, userId);
} else {
sseEmitter = completionByApp(chatCompletionReqDto, false);
}
return sseEmitter;
}
/**
*
* @param chatCompletionReqDto
* @param userId
* @return
*/
@Override
public SseEmitter chatComments(ChatCompletionReqDto chatCompletionReqDto, String userId,String userName) {
// 目前仅使用讯飞星火大模型
String appId = chatCompletionReqDto.getAppId();
SseEmitter sseEmitter;
if (StringUtils.isEmpty(appId)) {
sseEmitter = commentsBySession(chatCompletionReqDto, userId,userName);
} else {
sseEmitter = completionByApp(chatCompletionReqDto, false);
}
return sseEmitter;
}
/**
* ()
*/
private SseEmitter completionByApp(ChatCompletionReqDto chatCompletionReqDto, boolean justApi) {
String appId = chatCompletionReqDto.getAppId();
String userPrompt = chatCompletionReqDto.getText();
User user = SecurityUtil.getLoginUser();
String userId = user.getId();
String schoolId = user.getSchoolId();
// 查询 appId 获取 prompt
// 通过 prompt 和 userprompt 生成结果
// 直接返回
ChatApp chatApp = RepositoryUtil.findOne(chatAppRepository.findByAppId(appId), "该应用不存在");
// 检验 app 是否可以被该用户使用
if (!schoolId.equals(chatApp.getSchoolId()) && !"public".equals(chatApp.getSchoolId())) {
throw new ServiceException(ErrorCode.NO_AUTH_ERROR.getCode(), "无权使用该应用");
}
String appPrompt = chatApp.getPrompt();
SseEmitter sseEmitter = new SseEmitter(-1L);
SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
// open 回调
listener.setOnOpen((s) -> {
// 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
log.info("callback: ws open event emmit");
});
// 对话完成的回调
listener.setOnComplete((s) -> {
log.info("callback: ws complete event emmit");
SseHelper.send(sseEmitter, "[DONE]");
// 处理完成后的事件:
if (!justApi) {
// 保存消息记录, 缓存更改
}
});
// 错误的回调
listener.setOnError((s) -> {
log.error("callback: ws error, info: " + s);
// 返还积分
});
List<SparkChatRequestParam.Message> messageList = new ArrayList<>();
messageList.add(SparkChatRequestParam.Message.ofAssistant(appPrompt));
messageList.add(SparkChatRequestParam.Message.ofUser(userPrompt));
SparkChatRequestParam requestParam = SparkChatRequestParam
.builder()
.uid(userId)
.chatId(appId)
.messageList(messageList)
.build();
sparkGptClient.streamChatCompletion(requestParam, listener);
return sseEmitter;
}
/**
*
*/
private SseEmitter completionBySession(ChatCompletionReqDto chatCompletionReqDto, String userId) {
String userPrompt = chatCompletionReqDto.getText();
String sessionId = chatCompletionReqDto.getSessionId();
ChatSession session = RepositoryUtil.findOne(chatSessionRepository.findBySessionId(sessionId), "该会话不存在");
if (!session.getUserId().equals(userId)) {
throw new ServiceException(ErrorCode.NO_AUTH_ERROR.getCode(), "该会话不存在");
}
SseEmitter sseEmitter = new SseEmitter(-1L);
SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
// open 回调
listener.setOnOpen((s) -> {
// 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
log.info("callback: ws open event emmit");
});
// 对话完成的回调
listener.setOnComplete((s) -> {
log.info("callback: ws complete event emmit");
SseHelper.send(sseEmitter, "[DONE]");
// 处理完成后的事件: 保存消息记录, 缓存更改
ChatSession.Message message = ChatSession.Message.of(userPrompt, s);
HistoryCache.updateContext(sessionId, message);
CosmosPatchOperations options = CosmosPatchOperations.create()
.replace("/updateTime", Instant.now().toEpochMilli())
.add("/history/-", message);
chatSessionRepository.save(sessionId, PK.of(PK.CHAT_SESSION), ChatSession.class, options);
});
// 错误的回调
listener.setOnError((s) -> {
log.error("callback: ws error, info: " + s);
// 返还积分
});
List<SparkChatRequestParam.Message> messageList = fetchContext(sessionId, userPrompt);
SparkChatRequestParam requestParam = SparkChatRequestParam
.builder()
.uid(userId)
.chatId(sessionId)
.messageList(messageList)
.build();
sparkGptClient.streamChatCompletion(requestParam, listener);
return sseEmitter;
}
/**
*
*/
private SseEmitter commentsBySession(ChatCompletionReqDto chatCompletionReqDto, String userId,String userName) {
String userPrompt = chatCompletionReqDto.getText();
String sessionId = chatCompletionReqDto.getSessionId();
ChatSession session = null;
List<ChatSession> sessions = chatSessionRepository.findCommentsById(userId);
if (sessions.size() == 0) {
// 初始化欢迎语
ChatSession.Message message = ChatSession.Message.of("", "你好" + userName + " ,我是你的私人 AI 助手小豆,你可以问我任何包括但不仅限于教育的问题,我会尽力为您解答!");
List<ChatSession.Message> history = Collections.singletonList(message);
session = new ChatSession();
session.setId(userId);
session.setCode(PK.CHAT_SESSION);
session.setTitle("评语");
session.setUserId(userId);
session.setCreateTime(Instant.now().toEpochMilli());
session.setUpdateTime(Instant.now().toEpochMilli());
session.setHistory(history);
chatSessionRepository.save(session);
}else {
session = RepositoryUtil.findOne(chatSessionRepository.findBySessionId(userId), "该会话不存在");
}
/*
ChatSession session = RepositoryUtil.findOne(chatSessionRepository.findBySessionId(sessionId), "该会话不存在");
if (!session.getUserId().equals(userId)) {
throw new ServiceException(ErrorCode.NO_AUTH_ERROR.getCode(), "该会话不存在");
}*/
SseEmitter sseEmitter = new SseEmitter(-1L);
SparkGptStreamListener listener = new SparkGptStreamListener(sseEmitter);
// open 回调
listener.setOnOpen((s) -> {
// 敏感词检查,计费 (设计模型, reducePoints, 或者都可以在完成的回调中做?)
log.info("callback: ws open event emmit");
});
// 对话完成的回调
listener.setOnComplete((s) -> {
log.info("callback: ws complete event emmit");
SseHelper.send(sseEmitter, "[DONE]");
// 处理完成后的事件: 保存消息记录, 缓存更改
ChatSession.Message message = ChatSession.Message.of(userPrompt, s);
HistoryCache.updateContext(sessionId, message);
CosmosPatchOperations options = CosmosPatchOperations.create()
.replace("/updateTime", Instant.now().toEpochMilli())
.add("/history/-", message);
chatSessionRepository.save(sessionId, PK.of(PK.CHAT_SESSION), ChatSession.class, options);
});
// 错误的回调
listener.setOnError((s) -> {
log.error("callback: ws error, info: " + s);
// 返还积分
});
List<SparkChatRequestParam.Message> messageList = fetchContext(sessionId, userPrompt);
SparkChatRequestParam requestParam = SparkChatRequestParam
.builder()
.uid(userId)
.chatId(sessionId)
.messageList(messageList)
.build();
sparkGptClient.streamChatCompletion(requestParam, listener);
return sseEmitter;
}
List<SparkChatRequestParam.Message> fetchContext(String sessionId, String prompt) {
List<ChatSession.Message> context = HistoryCache.getContext(sessionId);
List<SparkChatRequestParam.Message> paramMessages = new ArrayList<>();
// 暂未缓存,从数据库拉取
if (ObjectUtils.isEmpty(context)) {
context = chatSessionRepository.findLatestMessage(sessionId);
if (ObjectUtils.isNotEmpty(context)) {
HistoryCache.putContext(sessionId, context);
}
}
// convert DB Message to Spark Message
context.forEach(item -> {
paramMessages.add(SparkChatRequestParam.Message.ofUser(item.getUserText()));
paramMessages.add(SparkChatRequestParam.Message.ofAssistant(item.getGptText()));
});
paramMessages.add(SparkChatRequestParam.Message.ofUser(prompt));
return paramMessages;
}
}