增加向量化的库

virtual-patient-common/src/main/java/com/supervision/config/VectorSimilarityConfiguration.java

@@ -26,6 +26,8 @@ public class VectorSimilarityConfiguration {
                 .withMetadataFields(
                         // 问题的ID
                         RedisVectorStore.MetadataField.tag("questionId"),
+                        // 标准问ID
+                        RedisVectorStore.MetadataField.tag("standardQuestionId"),
                         // 类型 1标准问 2相似问 3自定义
                         RedisVectorStore.MetadataField.tag("type"))
                 .build();

virtual-patient-web/src/main/java/com/supervision/service/impl/AskServiceImpl.java

@@ -27,6 +27,8 @@ import com.supervision.util.UserUtil;
 import com.supervision.vo.rasa.RasaTalkVo;
 import lombok.RequiredArgsConstructor;
 import lombok.extern.slf4j.Slf4j;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.vectorstore.RedisVectorStore;
 import org.springframework.beans.factory.annotation.Value;
 import org.springframework.stereotype.Service;
 import org.springframework.web.multipart.MultipartFile;
@@ -65,7 +67,8 @@ public class AskServiceImpl implements AskService {
 
     private final DiagnosisAiRecordService diagnosisAiRecordService;
 
-    @Value("${qaSimilarityThreshold:0.4}")
+    private final RedisVectorStore redisVectorStore;
+    @Value("${qaSimilarityThreshold:0.7}")
     private String qaSimilarityThreshold;
 
     @Override
@@ -234,14 +237,21 @@ public class AskServiceImpl implements AskService {
         }
     }
 
-    public QaSimilarityQuestionAnswer talkQaSimilarityWithScore(String question, String sessionId) {
+    public QaSimilarityQuestionAnswer talkRedisVectorWithScore(String question) {
         log.info("开始调用talkQaSimilarity,问题:{}", question);
         try {
-            GlobalResult<List<QaSimilarityQuestionAnswer>> result = askQaSimilarityFeignClient.askQuestionSimilarityAnswer(new QaSimilarityQuestion(question));
+            // 走Redis进行比较
+            List<Document> documents = redisVectorStore.similaritySearch(question);
+            Optional<QaSimilarityQuestionAnswer> first = documents.stream().map(document -> {
+                QaSimilarityQuestionAnswer qaSimilarityQuestionAnswer = new QaSimilarityQuestionAnswer();
+                qaSimilarityQuestionAnswer.setMatchQuestion(document.getContent());
+                qaSimilarityQuestionAnswer.setMatchQuestionCode(String.valueOf(document.getMetadata().get("standardQuestionId")));
+                qaSimilarityQuestionAnswer.setMatchScore(Double.parseDouble(String.valueOf(document.getMetadata().get("standardQuestionId"))));
+                return qaSimilarityQuestionAnswer;
+            }).max(Comparator.comparing(QaSimilarityQuestionAnswer::getMatchScore));
             // 排序,降序,取最高的
-            result.getData().sort(Comparator.comparing(QaSimilarityQuestionAnswer::getMatchScore).reversed());
-            log.info("调用talkQaSimilarity结束,问题:{},返回结果:{}", question, JSONUtil.toJsonStr(result));
-            return CollUtil.getFirst(result.getData());
+            log.info("调用talkQaSimilarity结束,问题:{},返回结果:{}", question, JSONUtil.toJsonStr(first.orElse(null)));
+            return first.orElse(null);
         } catch (Exception e) {
             log.error("调用talkQaSimilarity error ", e);
             return null;
@@ -301,7 +311,7 @@ public class AskServiceImpl implements AskService {
         // 根据processId找到对应的病人
         Process process = Optional.ofNullable(processService.getById(talkReqVO.getProcessId())).orElseThrow(() -> new BusinessException("未找到诊疗进程"));
         MedicalRec medicalRec = medicalRecService.getById(process.getMedicalRecId());
-        QaSimilarityQuestionAnswer qaSimilarityQuestionAnswer = talkQaSimilarityWithScore(talkReqVO.getText(), UserUtil.getUser().getId());
+        QaSimilarityQuestionAnswer qaSimilarityQuestionAnswer = talkRedisVectorWithScore(talkReqVO.getText());
         TalkVideoTtsResultResVO talkVideoTtsResultResVO = new TalkVideoTtsResultResVO();
         // 如果匹配度没有匹配到任何数据,则走大模型
         if (ObjectUtil.isEmpty(qaSimilarityQuestionAnswer)) {