feat: allow distance type (metric) to be specified during hybrid search (#1777)

python/python/tests/test_table.py

@@ -991,13 +991,10 @@ def test_count_rows(db):
     assert table.count_rows(filter="text='bar'") == 1
 
 
-def test_hybrid_search(db, tmp_path):
-    # This test uses an FTS index
-    pytest.importorskip("lancedb.fts")
-
+def setup_hybrid_search_table(tmp_path, embedding_func):
     db = MockDB(str(tmp_path))
     # Create a LanceDB table schema with a vector and a text column
-    emb = EmbeddingFunctionRegistry.get_instance().get("test")()
+    emb = EmbeddingFunctionRegistry.get_instance().get(embedding_func)()
 
     class MyTable(LanceModel):
         text: str = emb.SourceField()
@@ -1030,6 +1027,15 @@ def test_hybrid_search(db, tmp_path):
     # Create a fts index
     table.create_fts_index("text")
 
+    return table, MyTable, emb
+
+
+def test_hybrid_search(tmp_path):
+    # This test uses an FTS index
+    pytest.importorskip("lancedb.fts")
+
+    table, MyTable, emb = setup_hybrid_search_table(tmp_path, "test")
+
     result1 = (
         table.search("Our father who art in heaven", query_type="hybrid")
         .rerank(normalize="score")
@@ -1094,6 +1100,24 @@ def test_hybrid_search(db, tmp_path):
         table.search(query_type="hybrid").text("Arrrrggghhhhhhh").to_list()
 
 
+def test_hybrid_search_metric_type(db, tmp_path):
+    # This test uses an FTS index
+    pytest.importorskip("lancedb.fts")
+
+    # Need to use nonnorm as the embedding function so L2 and dot results
+    # are different
+    table, _, _ = setup_hybrid_search_table(tmp_path, "nonnorm")
+
+    # with custom metric
+    result_dot = (
+        table.search("feeling lucky", query_type="hybrid").metric("dot").to_arrow()
+    )
+    result_l2 = table.search("feeling lucky", query_type="hybrid").to_arrow()
+    assert len(result_dot) > 0
+    assert len(result_l2) > 0
+    assert result_dot["_relevance_score"] != result_l2["_relevance_score"]
+
+
 @pytest.mark.parametrize(
     "consistency_interval", [None, timedelta(seconds=0), timedelta(seconds=0.1)]
 )