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Optimize the memory usage of Tencent Vector Database (#22079)

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Co-authored-by: wlleiiwang <wlleiiwang@tencent.com>
This commit is contained in:
wlleiiwang
2025-07-09 15:53:06 +08:00
committed by GitHub
parent 3643ed1014
commit 89b52471fb
1 changed files with 2 additions and 3 deletions
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5
api/core/rag/datasource/vdb/tencent/tencent_vector.py
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@@ -122,7 +122,6 @@ class TencentVector(BaseVector):
metric_type,
params,
)
index_text = vdb_index.FilterIndex(self.field_text, enum.FieldType.String, enum.IndexType.FILTER)
index_metadate = vdb_index.FilterIndex(self.field_metadata, enum.FieldType.Json, enum.IndexType.FILTER)
index_sparse_vector = vdb_index.SparseIndex(
name="sparse_vector",
@@ -130,7 +129,7 @@ class TencentVector(BaseVector):
index_type=enum.IndexType.SPARSE_INVERTED,
metric_type=enum.MetricType.IP,
)
indexes = [index_id, index_vector, index_text, index_metadate]
indexes = [index_id, index_vector, index_metadate]
if self._enable_hybrid_search:
indexes.append(index_sparse_vector)
try:
@@ -149,7 +148,7 @@ class TencentVector(BaseVector):
index_metadate = vdb_index.FilterIndex(
self.field_metadata, enum.FieldType.String, enum.IndexType.FILTER
)
indexes = [index_id, index_vector, index_text, index_metadate]
indexes = [index_id, index_vector, index_metadate]
if self._enable_hybrid_search:
indexes.append(index_sparse_vector)
self._client.create_collection(