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fix: metric type inconsistency (#2122)

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PR fixes #2113

---------

Co-authored-by: Will Jones <willjones127@gmail.com>
This commit is contained in:
Gagan Bhullar
2025-03-12 11:28:37 -06:00
committed by GitHub
parent dd22a379b2
commit 14677d7c18
24 changed files with 104 additions and 89 deletions
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2
python/python/tests/test_query.py
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@@ -452,7 +452,7 @@ def test_query_builder_with_metric(table):
df_default = LanceVectorQueryBuilder(table, query, vector_column_name).to_pandas()
df_l2 = (
LanceVectorQueryBuilder(table, query, vector_column_name)
.distance_type("L2")
.distance_type("l2")
.to_pandas()
)
tm.assert_frame_equal(df_default, df_l2)

6
python/python/tests/test_table.py
View File

@@ -480,7 +480,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
)
table.create_index(
metric="L2",
metric="l2",
num_partitions=256,
num_sub_vectors=96,
vector_column_name="vector",
@@ -489,7 +489,7 @@ def test_create_index_method(mock_create_index, mem_db: DBConnection):
num_bits=4,
)
expected_config = IvfPq(
distance_type="L2",
distance_type="l2",
num_partitions=256,
num_sub_vectors=96,
num_bits=4,
@@ -1237,7 +1237,7 @@ def test_hybrid_search_metric_type(tmp_db: DBConnection):
# This test uses an FTS index
pytest.importorskip("lancedb.fts")
# Need to use nonnorm as the embedding function so L2 and dot results
# Need to use nonnorm as the embedding function so l2 and dot results
# are different
table, _, _ = setup_hybrid_search_table(tmp_db, "nonnorm")