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(improvement)(Chat) Fixed the issue of ineffective filtering in mapper detectDataSetIds, resolved the autocomplete feature, and changed METRIC_TAG to METRIC_ID. (#819)

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lexluo09
2024-03-14 16:58:41 +08:00
committed by GitHub
parent 901770f02c
commit 30ee64efec
25 changed files with 148 additions and 168 deletions
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7
chat/server/src/main/java/com/tencent/supersonic/chat/server/processor/execute/MetricRecommendProcessor.java
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@@ -13,15 +13,15 @@ import com.tencent.supersonic.headless.api.pojo.SemanticParseInfo;
import com.tencent.supersonic.headless.api.pojo.request.ExecuteQueryReq;
import com.tencent.supersonic.headless.api.pojo.response.QueryResult;
import com.tencent.supersonic.headless.core.chat.knowledge.MetaEmbeddingService;
import org.springframework.util.CollectionUtils;
import java.util.Collections;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import org.springframework.util.CollectionUtils;
/**
* MetricRecommendProcessor fills recommended metrics based on embedding similarity.
@@ -49,7 +49,8 @@ public class MetricRecommendProcessor implements ExecuteResultProcessor {
.filterCondition(filterCondition).queryEmbeddings(null).build();
MetaEmbeddingService metaEmbeddingService = ContextUtils.getBean(MetaEmbeddingService.class);
List<RetrieveQueryResult> retrieveQueryResults =
metaEmbeddingService.retrieveQuery(retrieveQuery, METRIC_RECOMMEND_SIZE + 1, new HashMap<>());
metaEmbeddingService.retrieveQuery(retrieveQuery, METRIC_RECOMMEND_SIZE + 1, new HashMap<>(),
new HashSet<>());
if (CollectionUtils.isEmpty(retrieveQueryResults)) {
return;
}