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https://github.com/lancedb/lancedb.git
synced 2026-10-23 04:02:27 +00:00
fix: reject zero vector search probes across SDKs
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@@ -1693,13 +1693,15 @@ class LanceVectorQueryBuilder(LanceQueryBuilder):
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Parameters
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----------
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nprobes: int
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The number of probes to use.
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The number of probes to use. Must be greater than 0.
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Returns
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-------
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LanceVectorQueryBuilder
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The LanceQueryBuilder object.
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"""
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if nprobes <= 0:
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raise ValueError("Invalid input, nprobes must be greater than 0")
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self._minimum_nprobes = nprobes
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self._maximum_nprobes = nprobes
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return self
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@@ -2495,13 +2497,15 @@ class LanceHybridQueryBuilder(LanceQueryBuilder):
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Parameters
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----------
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nprobes: int
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The number of probes to use.
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The number of probes to use. Must be greater than 0.
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Returns
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-------
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LanceHybridQueryBuilder
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The LanceHybridQueryBuilder object.
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"""
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if nprobes <= 0:
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raise ValueError("Invalid input, nprobes must be greater than 0")
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self._minimum_nprobes = nprobes
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self._maximum_nprobes = nprobes
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return self
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@@ -3654,6 +3658,8 @@ class AsyncVectorQueryBase:
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"""
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Set the number of partitions to search (probe)
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The number of probes must be greater than 0.
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This argument is only used when the vector column has an IVF-based index.
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If there is no index then this value is ignored.
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@@ -974,6 +974,19 @@ def test_query_builder_with_filter(table):
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assert all(np.array(rs[0]["vector"]) == [3, 4])
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@pytest.mark.parametrize("query_type", ["vector", "hybrid"])
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@pytest.mark.parametrize("nprobes", [0, -1])
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def test_nprobes_nonpositive_sync(table, query_type, nprobes):
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if query_type == "hybrid":
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query = table.search(query_type="hybrid").vector([0, 0]).text("a")
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else:
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query = table.search([0, 0])
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with pytest.raises(
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ValueError, match="^Invalid input, nprobes must be greater than 0$"
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):
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query.nprobes(nprobes)
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def test_invalid_nprobes_sync(table):
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with pytest.raises(ValueError, match="minimum_nprobes must be greater than 0"):
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LanceVectorQueryBuilder(table, [0, 0], "vector").minimum_nprobes(0).to_list()
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@@ -1005,6 +1018,18 @@ def test_multiple_nprobes_calls_works_sync(table):
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).minimum_nprobes(20).to_list()
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@pytest.mark.asyncio
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@pytest.mark.parametrize("hybrid", [False, True])
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async def test_nprobes_zero_async(table_async: AsyncTable, hybrid):
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query = table_async.query().nearest_to([0, 0])
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if hybrid:
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query = query.nearest_to_text("dog")
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with pytest.raises(
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ValueError, match="^Invalid input, nprobes must be greater than 0$"
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):
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query.nprobes(0)
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@pytest.mark.asyncio
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async def test_invalid_nprobes_async(table_async: AsyncTable):
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with pytest.raises(ValueError, match="minimum_nprobes must be greater than 0"):
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@@ -1581,6 +1581,53 @@ def test_query_sync_maximal():
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)
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@pytest.mark.parametrize("hybrid", [False, True])
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def test_query_sync_nprobes_zero(hybrid):
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query_requests = []
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def handler(body):
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query_requests.append(body)
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return pa.table({"id": []})
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with query_test_table(handler) as table:
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if hybrid:
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query = table.search(query_type="hybrid").vector([1, 2, 3]).text("dog")
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else:
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query = table.search([1, 2, 3])
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with pytest.raises(
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ValueError, match="^Invalid input, nprobes must be greater than 0$"
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):
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query.nprobes(0)
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assert query_requests == []
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@pytest.mark.asyncio
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@pytest.mark.parametrize("hybrid", [False, True])
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async def test_query_async_nprobes_zero(hybrid):
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requests = []
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def handler(request):
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requests.append(request.path)
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if request.path == "/v1/table/test/describe/":
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send_json(request, {"version": 1, "schema": {"fields": []}})
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else:
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request.send_response(404)
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request.end_headers()
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async with mock_lancedb_connection_async(handler) as db:
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table = await db.open_table("test")
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query = table.query().nearest_to([1, 2, 3])
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if hybrid:
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query = query.nearest_to_text("dog")
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with pytest.raises(
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ValueError, match="^Invalid input, nprobes must be greater than 0$"
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):
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query.nprobes(0)
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assert requests == ["/v1/table/test/describe/"]
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def test_query_sync_nprobes():
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def handler(body):
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assert body == {
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+5
-4
@@ -995,8 +995,9 @@ impl VectorQuery {
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self.inner = self.inner.clone().refine_factor(refine_factor);
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}
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pub fn nprobes(&mut self, nprobe: u32) {
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self.inner = self.inner.clone().nprobes(nprobe as usize);
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pub fn nprobes(&mut self, nprobe: u32) -> PyResult<()> {
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self.inner = self.inner.clone().nprobes(nprobe as usize).infer_error()?;
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Ok(())
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}
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pub fn minimum_nprobes(&mut self, minimum_nprobes: u32) -> PyResult<()> {
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@@ -1188,8 +1189,8 @@ impl HybridQuery {
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self.inner_vec.refine_factor(refine_factor);
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}
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pub fn nprobes(&mut self, nprobe: u32) {
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self.inner_vec.nprobes(nprobe);
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pub fn nprobes(&mut self, nprobe: u32) -> PyResult<()> {
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self.inner_vec.nprobes(nprobe)
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}
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pub fn ef(&mut self, ef: u32) {
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