fix(python): reject empty query vectors before column inference (#4415)

Empty list and NumPy vector queries were validated too late: local
search inferred a vector column first, producing misleading schema
errors, while remote search indexed `vector[0]` and raised `IndexError`.

Add a shared empty-vector check before column inference and query
creation, and validate direct vector-builder inputs. Local and remote
sync search now raise `ValueError: Query vector must not be empty` for
these inputs.

Validation:

- All 26 new regression cases failed on the original code and pass with
the fix, covering list/NumPy inputs, automatic/explicit vector search,
inferred/explicit column names, one/two local vector columns, and remote
search before query submission.
- After merging current `main`, all 32 focused cases passed, covering
these regressions and upstream async searches without a query.
- The query, table, remote, utility, hybrid-query, and database suites
passed in the rebuilt uv environment: 541 passed, 1 skipped, 1 slow test
deselected.
- `ruff check .`, `ruff format .`, and `cargo fmt --all` passed from the
repository root.

Fixes #4389

<!-- lance-gatekeeper-fix:v1 agent=f1f4875090ef391bb1aa912dd54026dc
generation=1 -->

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>

python/python/tests/test_table.py

@@ -3777,6 +3777,24 @@ def test_empty_query(mem_db: DBConnection):
     assert df.num_rows == 42
 
 
+@pytest.mark.parametrize("query", [[], np.array([], dtype=np.float32)])
+@pytest.mark.parametrize("vector_column_name", [None, "vector"])
+@pytest.mark.parametrize("query_type", ["auto", "vector"])
+@pytest.mark.parametrize("multiple_vector_columns", [False, True])
+def test_search_empty_vector(
+    mem_db, query, vector_column_name, query_type, multiple_vector_columns
+):
+    fields = [pa.field("vector", pa.list_(pa.float32(), 8))]
+    if multiple_vector_columns:
+        fields.append(pa.field("vec2", pa.list_(pa.float32(), 4)))
+    table = mem_db.create_table("empty_vector_query", schema=pa.schema(fields))
+
+    with pytest.raises(ValueError, match="^Query vector must not be empty$"):
+        table.search(
+            query, vector_column_name=vector_column_name, query_type=query_type
+        ).limit(3).to_arrow()
+
+
 def test_search_with_schema_inf_single_vector(mem_db: DBConnection):
     class MyTable(LanceModel):
         text: str