知识库检索 API更新

go/appbuilder/knowledge_base.go

@@ -848,6 +848,12 @@ func (t *KnowledgeBase) DescribeChunks(req DescribeChunksRequest) (DescribeChunk
 }
 
 func (t *KnowledgeBase) QueryKnowledgeBase(req QueryKnowledgeBaseRequest) (QueryKnowledgeBaseResponse, error) {
+    // 检查 RankScoreThreshold 是否为 nil，如果是，则设置默认值
+    if req.RankScoreThreshold == nil {
+        defaultThreshold := 0.4
+        req.RankScoreThreshold = &defaultThreshold
+    }
+
 	request := http.Request{}
 	header := t.sdkConfig.AuthHeaderV2()
 	serviceURL, err := t.sdkConfig.ServiceURLV2("/knowledgebases/query")

go/appbuilder/knowledge_base_data.go

@@ -14,6 +14,14 @@
 
 package appbuilder
 
+type QueryType string
+
+const (
+    Fulltext QueryType = "fulltext"
+    Semantic QueryType = "semantic"
+    Hybrid   QueryType = "hybrid"
+)
+
 const (
 	ContentTypeRawText = "raw_text"
 	ContentTypeQA      = "qa"
@@ -277,6 +285,18 @@ type ElasticSearchRetrieveConfig struct {
 	Top       int     `json:"top"`
 }
 
+type VectorDBRetrieveConfig struct {
+	Name      string  `json:"name"`
+	Type      string  `json:"type"`
+	Threshold float64 `json:"threshold"`
+	Top       int     `json:"top"`
+}
+
+type SmallToBigConfig struct {
+	Name      string   `json:"name"`
+	Type      string   `json:"type"`
+}
+
 type RankingConfig struct {
 	Name      string   `json:"name"`
 	Type      string   `json:"type"`
@@ -291,13 +311,14 @@ type QueryPipelineConfig struct {
 }
 
 type QueryKnowledgeBaseRequest struct {
-	Query            string              `json:"query"`
-	KnowledgebaseIDs []string            `json:"knowledgebase_ids"`
-	Type             *string             `json:"type,omitempty"`
-	Top              int                 `json:"top,omitempty"`
-	Skip             int                 `json:"skip,omitempty"`
-	MetadataFileters MetadataFilters     `json:"metadata_fileters,omitempty"`
-	PipelineConfig   QueryPipelineConfig `json:"pipeline_config,omitempty"`
+	Query            		string              `json:"query"`
+	KnowledgebaseIDs 		[]string            `json:"knowledgebase_ids"`
+	Type             		*QueryType          `json:"type,omitempty"`
+	Top              		int                 `json:"top,omitempty"`
+	Skip             		int                 `json:"skip,omitempty"`
+	RankScoreThreshold 		*float64         	`json:"rank_score_threshold,omitempty"`
+	MetadataFileters 		MetadataFilters     `json:"metadata_fileters,omitempty"`
+	PipelineConfig   		QueryPipelineConfig `json:"pipeline_config,omitempty"`
 }
 
 type RowLine struct {
@@ -314,19 +335,22 @@ type ChunkLocation struct {
 }
 
 type Chunk struct {
-	ChunkID         string         `json:"chunk_id"`
-	KnowledgebaseID string         `json:"knowledgebase_id"`
-	DocumentID      string         `json:"document_id"`
-	DocumentName    string         `json:"document_name"`
-	Meta            map[string]any `json:"meta"`
-	Type            string         `json:"type"`
-	Content         string         `json:"content"`
-	CreateTime      string         `json:"create_time"`
-	UpdateTime      string         `json:"update_time"`
-	RetrievalScore  float64        `json:"retrieval_score"`
-	RankScore       float64        `json:"rank_score"`
-	Locations       ChunkLocation  `json:"locations"`
-	Children        []Chunk        `json:"children"`
+	ChunkID         	string         `json:"chunk_id"`
+	KnowledgebaseID 	string         `json:"knowledgebase_id"`
+	DocumentID      	string         `json:"document_id"`
+	DocumentName    	string         `json:"document_name"`
+	Meta            	map[string]any `json:"meta"`
+	Type            	string         `json:"type"`
+	Content         	string         `json:"content"`
+	CreateTime      	string         `json:"create_time"`
+	UpdateTime      	string         `json:"update_time"`
+	RetrievalScore  	float64        `json:"retrieval_score"`
+	RankScore       	float64        `json:"rank_score"`
+	Locations       	ChunkLocation  `json:"locations"`
+	Children        	[]Chunk        `json:"children"`
+	NeighbourChunks     []Chunk        `json:"neighbour_chunks"`
+	OriginalChunkId 	string         `json:"original_chunk_id"`
+	OriginalChunkOffset int        	   `json:"original_chunk_offset"`
 }
 
 type QueryKnowledgeBaseResponse struct {

java/src/main/java/com/baidubce/appbuilder/console/knowledgebase/Knowledgebase.java

@@ -722,6 +722,9 @@ public ChunksDescribeResponse describeChunks(String documentId, String marker, I
 
     public QueryKnowledgeBaseResponse queryKnowledgeBase(QueryKnowledgeBaseRequest request)
             throws IOException, AppBuilderServerException {
+        if (request.getRank_score_threshold() == null) {
+            request.setRank_score_threshold(0.4f);
+        }
         String url = AppBuilderConfig.QUERY_KNOWLEDGEBASE_URL;
 
         String jsonBody = JsonUtils.serialize(request);
@@ -734,12 +737,16 @@ public QueryKnowledgeBaseResponse queryKnowledgeBase(QueryKnowledgeBaseRequest r
         return respBody;
     }
 
-    public QueryKnowledgeBaseResponse queryKnowledgeBase(String query, String type, Integer top, Integer skip,
+    public QueryKnowledgeBaseResponse queryKnowledgeBase(String query, String type, Float rank_score_threshold, Integer top, Integer skip,
             String[] knowledgebaseIDs, QueryKnowledgeBaseRequest.MetadataFilters filters,
             QueryKnowledgeBaseRequest.QueryPipelineConfig pipelineConfig) 
             throws IOException, AppBuilderServerException {
+        if (rank_score_threshold == null) {
+            rank_score_threshold = 0.4f;
+        }
+
         String url = AppBuilderConfig.QUERY_KNOWLEDGEBASE_URL;
-        QueryKnowledgeBaseRequest request = new QueryKnowledgeBaseRequest(query, type, top, skip, knowledgebaseIDs, filters, pipelineConfig);
+        QueryKnowledgeBaseRequest request = new QueryKnowledgeBaseRequest(query, type, rank_score_threshold,top, skip, knowledgebaseIDs, filters, pipelineConfig);
         String jsonBody = JsonUtils.serialize(request);
         ClassicHttpRequest postRequest = httpClient.createPostRequestV2(url,
                 new StringEntity(jsonBody, StandardCharsets.UTF_8));

java/src/main/java/com/baidubce/appbuilder/model/knowledgebase/QueryKnowledgeBaseRequest.java

@@ -5,17 +5,19 @@
 public class QueryKnowledgeBaseRequest {
     private String query;
     private String type;
+    private Float rank_score_threshold;
     private Integer top;
     private Integer skip;
     private String[] knowledgebase_ids;
     private MetadataFilters metadata_filters;
     private QueryPipelineConfig pipeline_config;
 
-    public QueryKnowledgeBaseRequest(String query, String type, Integer top, Integer skip,
+    public QueryKnowledgeBaseRequest(String query, String type, Float rank_score_threshold, Integer top, Integer skip,
             String[] knowledgebase_ids, MetadataFilters metadata_filters,
             QueryPipelineConfig pipeline_config) {
         this.query = query;
         this.type = type;
+        this.rank_score_threshold = rank_score_threshold;
         this.top = top;
         this.skip = skip;
         this.knowledgebase_ids = knowledgebase_ids;
@@ -39,6 +41,14 @@ public void setType(String type) {
         this.type = type;
     }
 
+    public Float getRank_score_threshold() {
+        return rank_score_threshold;
+    }
+
+    public void setRank_score_threshold(Float rank_score_threshold) {
+        this.rank_score_threshold = rank_score_threshold;
+    }
+
     public Integer getTop() {
         return top;
     }
@@ -217,6 +227,46 @@ public void setTop(Integer top) {
         }
     }
 
+    public static class VectorDBRetrieveConfig {
+        private String name;
+        private String type;
+        private Double threshold;
+        private Integer top;
+
+        public String getName() {
+            return name;
+        }
+
+        public void setName(String name) {
+            this.name = name;
+        }
+
+        public String getType() {
+            return type;
+        }
+
+        public void setType(String type) {
+            this.type = type;
+        }
+
+        public Double getThreshold() {
+            return threshold;
+        }
+
+        public void setThreshold(Double threshold) {
+            this.threshold = threshold;
+        }
+
+        public Integer getTop() {
+            return top;
+        }
+
+        public void setTop(Integer top) {
+            this.top = top;
+        }
+    }
+
+
     public static class RankingConfig {
         private String name;
         private String type;
@@ -265,6 +315,28 @@ public void setTop(Integer top) {
         }
     }
 
+    public static class SmallToBigConfig {
+        private String name;
+        private String type;
+
+        public String getName() {
+            return name;
+        }
+
+        public void setName(String name) {
+            this.name = name;
+        }
+
+        public String getType() {
+            return type;
+        }
+
+        public void setType(String type) {
+            this.type = type;
+        }
+
+    }
+
     public static class QueryPipelineConfig {
         private String id;
         private List<Object> pipeline; 

java/src/main/java/com/baidubce/appbuilder/model/knowledgebase/QueryKnowledgeBaseResponse.java

@@ -44,6 +44,9 @@ public static class Chunk {
         private float rank_score;
         private ChunkLocation locations;
         private List<Chunk> children;
+        private List<Chunk> neighbour_chunks;
+        private String original_chunk_id;
+        private Integer original_chunk_offset;
 
         public String getChunk_id() { return chunk_id; }
 
@@ -96,6 +99,18 @@ public static class Chunk {
         public List<Chunk> getChildren() { return children; }
 
         public void setChildren(List<Chunk> children) { this.children = children; }
+
+        public List<Chunk> getNeighbour_chunks() { return neighbour_chunks; }
+
+        public void setNeighbour_chunks(List<Chunk> neighbour_chunks) { this.neighbour_chunks = neighbour_chunks; }
+
+        public String getOriginal_chunk_id() { return original_chunk_id; }
+
+        public void setOriginal_chunk_id(String original_chunk_id) { this.original_chunk_id = original_chunk_id; }
+
+        public Integer getOriginal_chunk_offset() { return original_chunk_offset; }
+
+        public void setOriginal_chunk_offset(Integer original_chunk_offset) { this.original_chunk_offset = original_chunk_offset; }
     }
 
     public static class ChunkLocation {

java/src/test/java/com/baidubce/appbuilder/KnowledgebaseTest.java

@@ -198,7 +198,7 @@ public void testQueryKnowledgeBaseV2() throws IOException, AppBuilderServerExcep
                 Files.readAllBytes(Paths.get("src/test/java/com/baidubce/appbuilder/files/query_knowledgebase.json")));
         QueryKnowledgeBaseRequest request = gson.fromJson(requestJson, QueryKnowledgeBaseRequest.class);
         QueryKnowledgeBaseResponse response = knowledgebase.queryKnowledgeBase(request.getQuery(),
-                request.getType(), request.getTop(), request.getSkip(),
+                request.getType(), request.getRank_score_threshold(), request.getTop(), request.getSkip(),
                 request.getKnowledgebase_ids(), request.getMetadata_filters(), request.getPipeline_config());
         assertNotNull(response.getChunks().get(0).getChunk_id());
     }

python/core/console/knowledge_base/data_class.py

@@ -14,6 +14,7 @@
 from __future__ import annotations
 from datetime import datetime
 from pydantic import BaseModel, Field
+from enum import Enum
 from typing import Union, Optional, List
 
 
@@ -323,13 +324,28 @@ class PreRankingConfig(BaseModel):
         None, description="得分归一化参数，不建议修改，默认50"
     )
 
+class QueryType(str, Enum):
+    FULLTEXT = "fulltext" # 全文检索
+    SEMANTIC = "semantic" # 语义检索
+    HYBRID = "hybrid" # 混合检索
 
-class ElasticSearchRetrieveConfig(BaseModel):
+class ElasticSearchRetrieveConfig(BaseModel): # 托管资源为共享资源 或 BES资源时使用该配置
     name: str = Field(..., description="配置名称")
     type: str = Field(None, description="elastic_search标志，该节点为es全文检索")
     threshold: float = Field(None, description="得分阈值，默认0.1")
     top: int = Field(None, description="召回数量，默认400")
 
+class VectorDBRetrieveConfig(BaseModel):
+    name: str = Field(..., description="该节点的自定义名称。")
+    type: str = Field("vector_db", description="该节点的类型，默认为vector_db。")
+    threshold: Optional[float] = Field(0.1, description="得分阈值。取值范围：[0, 1]", ge=0.0, le=1.0)
+    top: Optional[int] = Field(400, description="召回数量。取值范围：[0, 800]", ge=0, le=800)
+    pre_ranking: Optional[PreRankingConfig] = Field(None, description="粗排配置")
+
+class SmallToBigConfig(BaseModel):
+    name: str = Field(..., description="配置名称")
+    type: str = Field("small_to_big", description="small_to_big标志，该节点为small_to_big节点")
+
 
 class RankingConfig(BaseModel):
     name: str = Field(..., description="配置名称")
@@ -341,24 +357,29 @@ class RankingConfig(BaseModel):
     model_name: str = Field(None, description="ranking模型名（当前仅一种，暂不生效）")
     top: int = Field(None, description="取切片top进行排序，默认20，最大400")
 
-
 class QueryPipelineConfig(BaseModel):
     id: str = Field(
         None, description="配置唯一标识，如果用这个id，则引用已经配置好的QueryPipeline"
     )
-    pipeline: list[Union[ElasticSearchRetrieveConfig, RankingConfig]] = Field(
+    pipeline: list[Union[ElasticSearchRetrieveConfig, RankingConfig, VectorDBRetrieveConfig, SmallToBigConfig]] = Field(
         None, description="配置的Pipeline，如果没有用id，可以用这个对象指定一个新的配置"
     )
 
 
 class QueryKnowledgeBaseRequest(BaseModel):
     query: str = Field(..., description="检索query")
-    type: str = Field(None, description="检索策略的枚举, fulltext:全文检索")
+    type: Optional[QueryType] = Field(None, description="检索策略的枚举, fulltext:全文检索, semantic:语义检索, hybrid:混合检索")
     top: int = Field(None, description="返回结果数量")
     skip: int = Field(
         None,
         description="跳过多少条记录, 通过top和skip可以实现类似分页的效果，比如top 10 skip 0，取第一页的10个，top 10 skip 10，取第二页的10个",
     )
+    rank_score_threshold: float = Field(
+        0.4,
+        description="重排序匹配分阈值，只有rank_score大于等于该分值的切片重排序时才会被筛选出来。当且仅当，pipeline_config中配置了ranking节点时，该过滤条件生效。取值范围： [0, 1]。",
+        ge=0.0,
+        le=1.0,
+    )
     knowledgebase_ids: list[str] = Field(..., description="知识库ID列表")
     metadata_filters: MetadataFilters = Field(None, description="元数据过滤条件")
     pipeline_config: QueryPipelineConfig = Field(None, description="检索配置")

python/core/console/knowledge_base/knowledge_base.py

@@ -909,10 +909,11 @@ def query_knowledge_base(
         self,
         query: str,
         knowledgebase_ids: list[str],
-        type: str = None,
+        type: Optional[data_class.QueryType] = None,
         metadata_filters: data_class.MetadataFilter = None,
         pipeline_config: data_class.QueryPipelineConfig = None,
-        top: int = None,
+        rank_score_threshold: Optional[float] = 0.4,
+        top: int = 6,
         skip: int = None,
     ) -> data_class.QueryKnowledgeBaseResponse:
         """
@@ -934,6 +935,7 @@ def query_knowledge_base(
             type=type,
             metadata_filters=metadata_filters,
             pipeline_config=pipeline_config,
+            rank_score_threshold=rank_score_threshold,
             top=top,
             skip=skip,
         )