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

package cn.teammodel.service.impl;

import cn.teammodel.ai.SparkGptClient;
import cn.teammodel.ai.SseHelper;
import cn.teammodel.ai.domain.SparkChatRequestParam;
import cn.teammodel.ai.listener.SparkGptStreamListener;
import cn.teammodel.model.dto.ai.ChatCompletionReqDto;
import cn.teammodel.model.entity.User;
import cn.teammodel.security.utils.SecurityUtil;
import cn.teammodel.service.ChatMessageService;
import com.google.common.collect.Lists;
import lombok.extern.slf4j.Slf4j;
import org.springframework.stereotype.Service;
import org.springframework.web.servlet.mvc.method.annotation.SseEmitter;

import javax.annotation.Resource;
import java.util.List;

/**
 * @author winter
 * @create 2023-12-18 15:20
 */
@Service
@Slf4j
public class ChatMessageServiceImpl implements ChatMessageService {
    @Resource
    private SparkGptClient sparkGptClient;

    @Override
    public SseEmitter chatCompletion(ChatCompletionReqDto chatCompletionReqDto) {
        // 目前仅使用讯飞星火大模型
        User user = SecurityUtil.getLoginUser();
        String userId = user.getId();
       String text = chatCompletionReqDto.getText();
        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
        });
        // 错误的回调
        listener.setOnError((s) -> {
            log.error("callback: ws error" );
            // 返还积分
        });
        // todo: 拉取对话上下文
        List<SparkChatRequestParam.Message> messageList = Lists.newArrayList();
        messageList.add(SparkChatRequestParam.Message.ofUser(text));
        // todo: sessionId
        SparkChatRequestParam requestParam = SparkChatRequestParam
                .builder()
                .uid(userId)
                .chatId("123")
                .messageList(messageList)
                .build();
        sparkGptClient.streamChatCompletion(requestParam, listener);
        return sseEmitter;
    }
}