diff --git a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py index 6f3e15d16..aa0204ba7 100644 --- a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py +++ b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py @@ -256,7 +256,7 @@ class AnalyticdbVectorOpenAPI: response = self._client.query_collection_data(request) documents = [] for match in response.body.matches.match: - if match.score > score_threshold: + if match.score >= score_threshold: metadata = json.loads(match.metadata.get("metadata_")) metadata["score"] = match.score doc = Document( @@ -293,7 +293,7 @@ class AnalyticdbVectorOpenAPI: response = self._client.query_collection_data(request) documents = [] for match in response.body.matches.match: - if match.score > score_threshold: + if match.score >= score_threshold: metadata = json.loads(match.metadata.get("metadata_")) metadata["score"] = match.score doc = Document( diff --git a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py index df2173d1c..71472cce4 100644 --- a/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py +++ b/api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py @@ -229,7 +229,7 @@ class AnalyticdbVectorBySql: documents = [] for record in cur: id, vector, score, page_content, metadata = record - if score > score_threshold: + if score >= score_threshold: metadata["score"] = score doc = Document( page_content=page_content, diff --git a/api/core/rag/datasource/vdb/baidu/baidu_vector.py b/api/core/rag/datasource/vdb/baidu/baidu_vector.py index d63ca9f69..d30cf4260 100644 --- a/api/core/rag/datasource/vdb/baidu/baidu_vector.py +++ b/api/core/rag/datasource/vdb/baidu/baidu_vector.py @@ -157,7 +157,7 @@ class BaiduVector(BaseVector): if meta is not None: meta = json.loads(meta) score = row.get("score", 0.0) - if score > score_threshold: + if score >= score_threshold: meta["score"] = score doc = Document(page_content=row_data.get(self.field_text), metadata=meta) docs.append(doc) diff --git a/api/core/rag/datasource/vdb/chroma/chroma_vector.py b/api/core/rag/datasource/vdb/chroma/chroma_vector.py index 699a60236..88da86cf7 100644 --- a/api/core/rag/datasource/vdb/chroma/chroma_vector.py +++ b/api/core/rag/datasource/vdb/chroma/chroma_vector.py @@ -120,7 +120,7 @@ class ChromaVector(BaseVector): distance = distances[index] metadata = dict(metadatas[index]) score = 1 - distance - if score > score_threshold: + if score >= score_threshold: metadata["score"] = score doc = Document( page_content=documents[index], diff --git a/api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py b/api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py index 49c4b392f..cbad0e67d 100644 --- a/api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py +++ b/api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py @@ -216,7 +216,7 @@ class ElasticSearchVector(BaseVector): docs = [] for doc, score in docs_and_scores: score_threshold = float(kwargs.get("score_threshold") or 0.0) - if score > score_threshold: + if score >= score_threshold: if doc.metadata is not None: doc.metadata["score"] = score docs.append(doc) diff --git a/api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py b/api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py index 0a4067e39..f0d014b1e 100644 --- a/api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py +++ b/api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py @@ -127,7 +127,7 @@ class HuaweiCloudVector(BaseVector): docs = [] for doc, score in docs_and_scores: score_threshold = float(kwargs.get("score_threshold") or 0.0) - if score > score_threshold: + if score >= score_threshold: if doc.metadata is not None: doc.metadata["score"] = score docs.append(doc) diff --git a/api/core/rag/datasource/vdb/lindorm/lindorm_vector.py b/api/core/rag/datasource/vdb/lindorm/lindorm_vector.py index 3c65a41f0..cba10b5aa 100644 --- a/api/core/rag/datasource/vdb/lindorm/lindorm_vector.py +++ b/api/core/rag/datasource/vdb/lindorm/lindorm_vector.py @@ -275,7 +275,7 @@ class LindormVectorStore(BaseVector): docs = [] for doc, score in docs_and_scores: score_threshold = kwargs.get("score_threshold", 0.0) or 0.0 - if score > score_threshold: + if score >= score_threshold: if doc.metadata is not None: doc.metadata["score"] = score docs.append(doc) diff --git a/api/core/rag/datasource/vdb/opengauss/opengauss.py b/api/core/rag/datasource/vdb/opengauss/opengauss.py index 3ba9569d3..c448210d9 100644 --- a/api/core/rag/datasource/vdb/opengauss/opengauss.py +++ b/api/core/rag/datasource/vdb/opengauss/opengauss.py @@ -194,7 +194,7 @@ class OpenGauss(BaseVector): metadata, text, distance = record score = 1 - distance metadata["score"] = score - if score > score_threshold: + if score >= score_threshold: docs.append(Document(page_content=text, metadata=metadata)) return docs diff --git a/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py b/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py index 3c9302f4d..71d2ba142 100644 --- a/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py +++ b/api/core/rag/datasource/vdb/opensearch/opensearch_vector.py @@ -211,7 +211,7 @@ class OpenSearchVector(BaseVector): metadata["score"] = hit["_score"] score_threshold = float(kwargs.get("score_threshold") or 0.0) - if hit["_score"] > score_threshold: + if hit["_score"] >= score_threshold: doc = Document(page_content=hit["_source"].get(Field.CONTENT_KEY.value), metadata=metadata) docs.append(doc) diff --git a/api/core/rag/datasource/vdb/oracle/oraclevector.py b/api/core/rag/datasource/vdb/oracle/oraclevector.py index 095691407..1b99f649b 100644 --- a/api/core/rag/datasource/vdb/oracle/oraclevector.py +++ b/api/core/rag/datasource/vdb/oracle/oraclevector.py @@ -261,7 +261,7 @@ class OracleVector(BaseVector): metadata, text, distance = record score = 1 - distance metadata["score"] = score - if score > score_threshold: + if score >= score_threshold: docs.append(Document(page_content=text, metadata=metadata)) conn.close() return docs diff --git a/api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py b/api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py index e77befcda..99cd4a22c 100644 --- a/api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py +++ b/api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py @@ -202,7 +202,7 @@ class PGVectoRS(BaseVector): score = 1 - dis metadata["score"] = score score_threshold = float(kwargs.get("score_threshold") or 0.0) - if score > score_threshold: + if score >= score_threshold: doc = Document(page_content=record.text, metadata=metadata) docs.append(doc) return docs diff --git a/api/core/rag/datasource/vdb/pgvector/pgvector.py b/api/core/rag/datasource/vdb/pgvector/pgvector.py index 108167d74..13be18f92 100644 --- a/api/core/rag/datasource/vdb/pgvector/pgvector.py +++ b/api/core/rag/datasource/vdb/pgvector/pgvector.py @@ -195,7 +195,7 @@ class PGVector(BaseVector): metadata, text, distance = record score = 1 - distance metadata["score"] = score - if score > score_threshold: + if score >= score_threshold: docs.append(Document(page_content=text, metadata=metadata)) return docs diff --git a/api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py b/api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py index 580da7d62..c33e344bf 100644 --- a/api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py +++ b/api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py @@ -170,7 +170,7 @@ class VastbaseVector(BaseVector): metadata, text, distance = record score = 1 - distance metadata["score"] = score - if score > score_threshold: + if score >= score_threshold: docs.append(Document(page_content=text, metadata=metadata)) return docs diff --git a/api/core/rag/datasource/vdb/qdrant/qdrant_vector.py b/api/core/rag/datasource/vdb/qdrant/qdrant_vector.py index 41ad5e57e..fc3c2fc63 100644 --- a/api/core/rag/datasource/vdb/qdrant/qdrant_vector.py +++ b/api/core/rag/datasource/vdb/qdrant/qdrant_vector.py @@ -369,7 +369,7 @@ class QdrantVector(BaseVector): continue metadata = result.payload.get(Field.METADATA_KEY.value) or {} # duplicate check score threshold - if result.score > score_threshold: + if result.score >= score_threshold: metadata["score"] = result.score doc = Document( page_content=result.payload.get(Field.CONTENT_KEY.value, ""), diff --git a/api/core/rag/datasource/vdb/relyt/relyt_vector.py b/api/core/rag/datasource/vdb/relyt/relyt_vector.py index 7a42dd1a8..a200bacfb 100644 --- a/api/core/rag/datasource/vdb/relyt/relyt_vector.py +++ b/api/core/rag/datasource/vdb/relyt/relyt_vector.py @@ -233,7 +233,7 @@ class RelytVector(BaseVector): docs = [] for document, score in results: score_threshold = float(kwargs.get("score_threshold") or 0.0) - if 1 - score > score_threshold: + if 1 - score >= score_threshold: docs.append(document) return docs diff --git a/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py b/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py index e66959045..1c154ef36 100644 --- a/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py +++ b/api/core/rag/datasource/vdb/tablestore/tablestore_vector.py @@ -300,7 +300,7 @@ class TableStoreVector(BaseVector): ) documents = [] for search_hit in search_response.search_hits: - if search_hit.score > score_threshold: + if search_hit.score >= score_threshold: ots_column_map = {} for col in search_hit.row[1]: ots_column_map[col[0]] = col[1] diff --git a/api/core/rag/datasource/vdb/tencent/tencent_vector.py b/api/core/rag/datasource/vdb/tencent/tencent_vector.py index d41dcbc31..3df35d081 100644 --- a/api/core/rag/datasource/vdb/tencent/tencent_vector.py +++ b/api/core/rag/datasource/vdb/tencent/tencent_vector.py @@ -293,7 +293,7 @@ class TencentVector(BaseVector): score = 1 - result.get("score", 0.0) else: score = result.get("score", 0.0) - if score > score_threshold: + if score >= score_threshold: meta["score"] = score doc = Document(page_content=result.get(self.field_text), metadata=meta) docs.append(doc) diff --git a/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py b/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py index a76b5d579..feda11b7f 100644 --- a/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py +++ b/api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py @@ -351,7 +351,7 @@ class TidbOnQdrantVector(BaseVector): metadata = result.payload.get(Field.METADATA_KEY.value) or {} # duplicate check score threshold score_threshold = kwargs.get("score_threshold") or 0.0 - if result.score > score_threshold: + if result.score >= score_threshold: metadata["score"] = result.score doc = Document( page_content=result.payload.get(Field.CONTENT_KEY.value, ""), diff --git a/api/core/rag/datasource/vdb/upstash/upstash_vector.py b/api/core/rag/datasource/vdb/upstash/upstash_vector.py index e4f15be2b..9e99f14dc 100644 --- a/api/core/rag/datasource/vdb/upstash/upstash_vector.py +++ b/api/core/rag/datasource/vdb/upstash/upstash_vector.py @@ -110,7 +110,7 @@ class UpstashVector(BaseVector): score = record.score if metadata is not None and text is not None: metadata["score"] = score - if score > score_threshold: + if score >= score_threshold: docs.append(Document(page_content=text, metadata=metadata)) return docs diff --git a/api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py b/api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py index 9166d35bc..a0a2e47d1 100644 --- a/api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py +++ b/api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py @@ -192,7 +192,7 @@ class VikingDBVector(BaseVector): metadata = result.fields.get(vdb_Field.METADATA_KEY.value) if metadata is not None: metadata = json.loads(metadata) - if result.score > score_threshold: + if result.score >= score_threshold: metadata["score"] = result.score doc = Document(page_content=result.fields.get(vdb_Field.CONTENT_KEY.value), metadata=metadata) docs.append(doc) diff --git a/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py b/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py index 5525ef168..a7e0789a9 100644 --- a/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py +++ b/api/core/rag/datasource/vdb/weaviate/weaviate_vector.py @@ -220,7 +220,7 @@ class WeaviateVector(BaseVector): for doc, score in docs_and_scores: score_threshold = float(kwargs.get("score_threshold") or 0.0) # check score threshold - if score > score_threshold: + if score >= score_threshold: if doc.metadata is not None: doc.metadata["score"] = score docs.append(doc) diff --git a/api/core/rag/index_processor/processor/paragraph_index_processor.py b/api/core/rag/index_processor/processor/paragraph_index_processor.py index 9b90bd2bb..997b0b953 100644 --- a/api/core/rag/index_processor/processor/paragraph_index_processor.py +++ b/api/core/rag/index_processor/processor/paragraph_index_processor.py @@ -123,7 +123,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor): for result in results: metadata = result.metadata metadata["score"] = result.score - if result.score > score_threshold: + if result.score >= score_threshold: doc = Document(page_content=result.page_content, metadata=metadata) docs.append(doc) return docs diff --git a/api/core/rag/index_processor/processor/parent_child_index_processor.py b/api/core/rag/index_processor/processor/parent_child_index_processor.py index 52756fbac..a13d303e4 100644 --- a/api/core/rag/index_processor/processor/parent_child_index_processor.py +++ b/api/core/rag/index_processor/processor/parent_child_index_processor.py @@ -162,7 +162,7 @@ class ParentChildIndexProcessor(BaseIndexProcessor): for result in results: metadata = result.metadata metadata["score"] = result.score - if result.score > score_threshold: + if result.score >= score_threshold: doc = Document(page_content=result.page_content, metadata=metadata) docs.append(doc) return docs diff --git a/api/core/rag/index_processor/processor/qa_index_processor.py b/api/core/rag/index_processor/processor/qa_index_processor.py index 609a8aafa..8c345b7ed 100644 --- a/api/core/rag/index_processor/processor/qa_index_processor.py +++ b/api/core/rag/index_processor/processor/qa_index_processor.py @@ -158,7 +158,7 @@ class QAIndexProcessor(BaseIndexProcessor): for result in results: metadata = result.metadata metadata["score"] = result.score - if result.score > score_threshold: + if result.score >= score_threshold: doc = Document(page_content=result.page_content, metadata=metadata) docs.append(doc) return docs