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fix:score threshold (#24897)

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This commit is contained in:
Frederick2313072
2025-09-02 08:58:14 +08:00
committed by GitHub
parent 9486715929
commit 2042353526
24 changed files with 25 additions and 25 deletions
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4
api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_openapi.py
View File

@@ -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(

2
api/core/rag/datasource/vdb/analyticdb/analyticdb_vector_sql.py
View File

@@ -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,

2
api/core/rag/datasource/vdb/baidu/baidu_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/chroma/chroma_vector.py
View File

@@ -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],

2
api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/huawei/huawei_cloud_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/lindorm/lindorm_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/opengauss/opengauss.py
View File

@@ -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

2
api/core/rag/datasource/vdb/opensearch/opensearch_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/oracle/oraclevector.py
View File

@@ -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

2
api/core/rag/datasource/vdb/pgvecto_rs/pgvecto_rs.py
View File

@@ -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

2
api/core/rag/datasource/vdb/pgvector/pgvector.py
View File

@@ -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

2
api/core/rag/datasource/vdb/pyvastbase/vastbase_vector.py
View File

@@ -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

2
api/core/rag/datasource/vdb/qdrant/qdrant_vector.py
View File

@@ -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, ""),

2
api/core/rag/datasource/vdb/relyt/relyt_vector.py
View File

@@ -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

2
api/core/rag/datasource/vdb/tablestore/tablestore_vector.py
View File

@@ -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]

2
api/core/rag/datasource/vdb/tencent/tencent_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/tidb_on_qdrant/tidb_on_qdrant_vector.py
View File

@@ -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, ""),

2
api/core/rag/datasource/vdb/upstash/upstash_vector.py
View File

@@ -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

2
api/core/rag/datasource/vdb/vikingdb/vikingdb_vector.py
View File

@@ -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)

2
api/core/rag/datasource/vdb/weaviate/weaviate_vector.py
View File

@@ -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)

2
api/core/rag/index_processor/processor/paragraph_index_processor.py
View File

@@ -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

2
api/core/rag/index_processor/processor/parent_child_index_processor.py
View File

@@ -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

2
api/core/rag/index_processor/processor/qa_index_processor.py
View File

@@ -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