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62 lines
2.5 KiB
Java
62 lines
2.5 KiB
Java
package com.supervision.service.impl;
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import cn.hutool.core.util.StrUtil;
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import com.supervision.pojo.ai.AiTalkAnswerDTO;
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import com.supervision.service.AiService;
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import com.supervision.util.AiChatUtil;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.ai.chat.messages.AssistantMessage;
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import org.springframework.ai.chat.messages.Message;
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import org.springframework.ai.chat.messages.SystemMessage;
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import org.springframework.ai.chat.messages.UserMessage;
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import org.springframework.stereotype.Service;
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import java.util.*;
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@Slf4j
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@Service
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public class AiServiceImpl implements AiService {
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public static final String userPromptTemplate = """
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预设病例的基本情况如下：
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---
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{medicalRecord}
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---
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回复格式为json:{"answer":"扮演病人并根据病历回复的内容"}
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""";
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private static final String systemPrompt = """
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我们现在来进行一个角色扮演连续对话场景。
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你现在扮演一个病人的角色，我来扮演医生,我们进行模拟问诊。
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我会给你设定病人的病历,你根据给定病历内容进行回复。
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如果病历中信息不能回问题，则回复'我不知道/没注意/不清楚'",所有问话都必须给回复!
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如果医生说'你好'等礼貌用语,你就回复'你好,医生'!!!
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""";
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/**
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* 根据病历进行回复
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*
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* @param question 医生的问题
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* @return 大模型回答的问题
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*/
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public String talk(String question, String medicalRecord) {
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Map<String, String> paramMap = new HashMap<>();
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paramMap.put("medicalRecord", medicalRecord);
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List<Message> messageHistoryList = new ArrayList<>();
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messageHistoryList.add(new SystemMessage(systemPrompt));
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messageHistoryList.add(new UserMessage(StrUtil.format(userPromptTemplate, paramMap)));
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messageHistoryList.add(new AssistantMessage("好的,已了解我要扮演病人的病历。已准备好对话了。"));
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messageHistoryList.add(new UserMessage(question));
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Optional<AiTalkAnswerDTO> chat = AiChatUtil.chat(messageHistoryList, AiTalkAnswerDTO.class);
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if (chat.isPresent()) {
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AiTalkAnswerDTO aiTalkAnswerDTO = chat.get();
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if (StrUtil.isNotBlank(aiTalkAnswerDTO.getAnswer())) {
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return aiTalkAnswerDTO.getAnswer();
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}
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}
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return "医生,我没有听懂你说的是什么";
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}
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}
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