If the filter will exceed SQLite IN limits, load to a temporary table and use a subquery to filter instead

ChatStreamingView built an IN filter from every permitted document id
for the "chat over all documents" case, which exceeds the vector
store's SQLite bound-parameter safety limit on installs with more
than ~32700 documents, silently returning no context. For a user who
can see every document (an active superuser), that filter never
narrows anything, so skip it and let the retriever search the whole
index instead.

src/documents/tests/test_api_chat.py

@@ -1,11 +1,18 @@
 from __future__ import annotations
 
+from typing import TYPE_CHECKING
 from unittest import mock
 
+import pytest
+from django.contrib.auth.models import Permission
 from django.contrib.auth.models import User
 from rest_framework import status
+from rest_framework.test import APIClient
 from rest_framework.test import APITestCase
 
+if TYPE_CHECKING:
+    from pytest_mock import MockerFixture
+
 
 class TestChatStreamingViewInputValidation(APITestCase):
     def setUp(self) -> None:
@@ -42,3 +49,70 @@ class TestChatStreamingViewInputValidation(APITestCase):
                 format="json",
             )
         assert resp.status_code == status.HTTP_400_BAD_REQUEST
+
+
+@pytest.mark.django_db
+class TestChatStreamingViewUnrestrictedFlag:
+    """The document id filter may only be skipped (``unrestricted=True``) for
+    a caller who can see every document, i.e. an active superuser.
+    """
+
+    @pytest.fixture
+    def mocked_stream_chat(self, mocker: MockerFixture) -> mock.MagicMock:
+        """AI enabled, with stream_chat_with_documents patched so the view
+        never touches the real vector store; returns the patched callable so
+        tests can inspect how it was called.
+        """
+        mocker.patch("documents.views.AIConfig").return_value.ai_enabled = True
+        return mocker.patch(
+            "documents.views.stream_chat_with_documents",
+            return_value=iter(()),
+        )
+
+    @pytest.fixture
+    def viewer_client(self, user_client: APIClient, regular_user: User) -> APIClient:
+        """The conftest regular-user client, additionally granted
+        view_document -- able to see every document without being a
+        superuser.
+        """
+        regular_user.user_permissions.add(
+            *Permission.objects.filter(codename="view_document"),
+        )
+        return user_client
+
+    @pytest.mark.parametrize(
+        ("client_fixture", "expected_unrestricted"),
+        [
+            pytest.param("admin_client", True, id="superuser_is_unrestricted"),
+            pytest.param("viewer_client", False, id="regular_user_is_restricted"),
+        ],
+    )
+    def test_unrestricted_only_for_superuser(
+        self,
+        request: pytest.FixtureRequest,
+        mocked_stream_chat: mock.MagicMock,
+        client_fixture: str,
+        *,
+        expected_unrestricted: bool,
+    ) -> None:
+        """
+        GIVEN:
+            - A superuser, or a regular user holding view_document
+        WHEN:
+            - They post a chat question with no document_id
+        THEN:
+            - stream_chat_with_documents is called with unrestricted=True for
+              the superuser and unrestricted=False for the regular user, even
+              though that user can view every document
+        """
+        client: APIClient = request.getfixturevalue(client_fixture)
+
+        client.post(
+            "/api/documents/chat/",
+            data={"q": "What's in these documents?"},
+            format="json",
+        )
+
+        assert (
+            mocked_stream_chat.call_args.kwargs["unrestricted"] is expected_unrestricted
+        )

src/documents/views.py

@@ -180,6 +180,7 @@ from documents.permissions import has_system_status_permission
 from documents.permissions import permitted_document_ids
 from documents.permissions import permitted_object_ids
 from documents.permissions import set_permissions_for_object
+from documents.permissions import user_is_unrestricted
 from documents.plugins.date_parsing import get_date_parser
 from documents.schema import generate_object_with_permissions_schema
 from documents.search import SearchHit
@@ -2329,10 +2330,12 @@ class ChatStreamingView(GenericAPIView[Any]):
                 return HttpResponseForbidden("Insufficient permissions")
 
             documents = Document.objects.filter(pk=document.pk)
+            unrestricted = False
         else:
             documents = Document.objects.filter(
                 id__in=permitted_document_ids(request.user),
             )
+            unrestricted = user_is_unrestricted(request.user)
 
         output_language = get_llm_output_language(
             ai_config=ai_config,
@@ -2343,6 +2346,7 @@ class ChatStreamingView(GenericAPIView[Any]):
             stream_chat_with_documents(
                 query_str=question,
                 documents=documents,
+                unrestricted=unrestricted,
                 output_language=output_language,
             ),
             content_type="text/event-stream",

src/paperless_ai/chat.py

@@ -95,12 +95,15 @@ def _format_chat_metadata_trailer(references: list[dict[str, int | str]]) -> str
 def stream_chat_with_documents(
     query_str: str,
     documents: QuerySet[Document],
+    *,
+    unrestricted: bool = False,
     output_language: str | None = None,
 ):
     try:
         yield from _stream_chat_with_documents(
             query_str,
             documents,
+            unrestricted=unrestricted,
             output_language=output_language,
         )
     except Exception as e:
@@ -111,6 +114,8 @@ def stream_chat_with_documents(
 def _stream_chat_with_documents(
     query_str: str,
     documents: QuerySet[Document],
+    *,
+    unrestricted: bool = False,
     output_language: str | None = None,
 ):
     if not documents.exists():
@@ -123,9 +128,15 @@ def _stream_chat_with_documents(
     from llama_index.core.retrievers import VectorIndexRetriever
 
     config = AIConfig()
-    filters = _document_id_filters(
-        str(pk) for pk in documents.values_list("pk", flat=True)
-    )
+    if unrestricted:
+        # The caller can see every document, so an id filter would never narrow
+        # the search, only risk exceeding the vector store's bound parameter
+        # limit (_MAX_IN_VALUES in vector_store.py) on large installs.
+        filters = None
+    else:
+        filters = _document_id_filters(
+            str(pk) for pk in documents.values_list("pk", flat=True)
+        )
 
     # Hold the shared read lock for the whole operation: the query engine
     # retrieves from the vector store again during synthesis, so the connection

src/paperless_ai/tables.py

@@ -154,6 +154,35 @@ class DocumentMetaTable:
         }
 
 
+class PermittedIdsTable:
+    """Per-connection scratch space for an oversized IN-filter id list.
+
+    A literal ``IN (?,?,...)`` list binds one SQL parameter per id, capped by
+    SQLite's own SQLITE_MAX_VARIABLE_NUMBER (see _MAX_IN_VALUES in
+    vector_store.py). Loading the ids into a TEMP TABLE and filtering via a
+    subquery instead has no such limit. TEMP tables live in a
+    connection-private namespace -- never visible to another connection,
+    even under this identical name -- so this is safe under the vector
+    store's one-connection-per-request model without any extra locking or
+    per-call naming scheme.
+    """
+
+    TABLE_NAME = "permitted_document_ids"
+
+    @staticmethod
+    def load(conn: sqlite3.Connection, ids: Iterable[int]) -> None:
+        """Replace this connection's scratch table with ``ids``."""
+        conn.execute(f"DROP TABLE IF EXISTS temp.{PermittedIdsTable.TABLE_NAME}")
+        conn.execute(
+            f"CREATE TEMP TABLE {PermittedIdsTable.TABLE_NAME} "
+            "(id INTEGER PRIMARY KEY)",
+        )
+        conn.executemany(
+            f"INSERT INTO {PermittedIdsTable.TABLE_NAME} (id) VALUES (?)",
+            ((i,) for i in ids),
+        )
+
+
 class IndexMetaTable:
     """Typed accessors over index_meta's key/value rows -- replaces
     PaperlessSqliteVecVectorStore._meta_get_on/_meta_set_on, which returned

src/paperless_ai/tests/test_chat.py

@@ -1,4 +1,8 @@
+from __future__ import annotations
+
 import json
+from typing import TYPE_CHECKING
+from typing import Any
 from unittest.mock import MagicMock
 from unittest.mock import patch
 
@@ -18,6 +22,11 @@ from paperless_ai.chat import _build_chat_prompt
 from paperless_ai.chat import _build_refine_prompt
 from paperless_ai.chat import stream_chat_with_documents
 
+if TYPE_CHECKING:
+    from pathlib import Path
+
+    import pytest_mock
+
 
 @pytest.fixture(autouse=True)
 def patch_embed_model():
@@ -312,6 +321,30 @@ def test_stream_chat_unexpected_failure_returns_generic_error(caplog) -> None:
 
 @pytest.mark.django_db
 class TestStreamChatRetrieval:
+    @pytest.fixture
+    def captured_filters(self, mocker: pytest_mock.MockerFixture) -> list[Any]:
+        """Stub out the AI client and the retriever, capturing the ``filters``
+        kwarg of every VectorIndexRetriever construction.
+
+        VectorIndexRetriever is imported inside _stream_chat_with_documents,
+        so it is patched at the llama_index source for the lazy import to
+        pick it up.
+        """
+        captured: list[Any] = []
+        retriever = mocker.MagicMock()
+        retriever.retrieve.return_value = []
+
+        def capture_retriever(*args, **kwargs) -> pytest_mock.MockType:
+            captured.append(kwargs.get("filters"))
+            return retriever
+
+        mocker.patch("paperless_ai.chat.AIClient")
+        mocker.patch(
+            "llama_index.core.retrievers.VectorIndexRetriever",
+            side_effect=capture_retriever,
+        )
+        return captured
+
     def test_no_nodes_yields_no_content_message(
         self,
         temp_llm_index_dir,
@@ -329,9 +362,9 @@ class TestStreamChatRetrieval:
 
     def test_chat_filter_contains_only_requested_document_ids(
         self,
-        temp_llm_index_dir,
-        mock_embed_model,
-        mocker,
+        temp_llm_index_dir: Path,
+        mock_embed_model: pytest_mock.MockType,
+        captured_filters: list[Any],
     ) -> None:
         """The MetadataFilter passed to the retriever must be scoped to the
         requested documents only — content from other indexed documents must
@@ -342,22 +375,6 @@ class TestStreamChatRetrieval:
         indexing.llm_index_add_or_update_document(included)
         indexing.llm_index_add_or_update_document(excluded)
 
-        # VectorIndexRetriever is imported inside _stream_chat_with_documents;
-        # patch it at the llama_index source so the lazy import picks it up.
-        captured_filters = []
-        mock_retriever = mocker.MagicMock()
-        mock_retriever.retrieve.return_value = []
-
-        def capture_retriever(*args, **kwargs):
-            captured_filters.append(kwargs.get("filters"))
-            return mock_retriever
-
-        mocker.patch("paperless_ai.chat.AIClient")
-        mocker.patch(
-            "llama_index.core.retrievers.VectorIndexRetriever",
-            side_effect=capture_retriever,
-        )
-
         list(
             chat.stream_chat_with_documents(
                 "question?",
@@ -372,6 +389,36 @@ class TestStreamChatRetrieval:
         assert str(included.pk) in filter_values
         assert str(excluded.pk) not in filter_values
 
+    def test_unrestricted_chat_skips_document_id_filter(
+        self,
+        temp_llm_index_dir: Path,
+        mock_embed_model: pytest_mock.MockType,
+        captured_filters: list[Any],
+    ) -> None:
+        """
+        GIVEN:
+            - A document indexed in the vector store
+        WHEN:
+            - stream_chat_with_documents is called with unrestricted=True
+        THEN:
+            - The retriever receives no document id filter (filters=None), so
+              the whole index is searched instead of an IN-list that risks the
+              vector store's safety limit on large installs
+        """
+        document = DocumentFactory.create(content="indexed document content")
+        indexing.llm_index_add_or_update_document(document)
+
+        list(
+            chat.stream_chat_with_documents(
+                "question?",
+                Document.objects.filter(pk=document.pk),
+                unrestricted=True,
+            ),
+        )
+
+        assert captured_filters, "VectorIndexRetriever was never constructed"
+        assert captured_filters[0] is None
+
     @pytest.mark.django_db
     def test_get_document_references_only_queries_referenced_documents(
         self,

src/paperless_ai/tests/test_tables.py

@@ -9,6 +9,7 @@ from paperless_ai.tables import DocumentChunksTable
 from paperless_ai.tables import DocumentMetaRow
 from paperless_ai.tables import DocumentMetaTable
 from paperless_ai.tables import IndexMetaTable
+from paperless_ai.tables import PermittedIdsTable
 
 
 @pytest.fixture
@@ -338,3 +339,85 @@ class TestIndexMetaTable:
         IndexMetaTable.increment_total_inserts(conn, 100)
         IndexMetaTable.reset_total_inserts(conn, 7)
         assert IndexMetaTable.get_total_inserts(conn) == 7
+
+
+class TestPermittedIdsTable:
+    def _loaded_ids(self, conn: sqlite3.Connection) -> list[int]:
+        return [
+            row["id"]
+            for row in conn.execute(
+                f"SELECT id FROM {PermittedIdsTable.TABLE_NAME} ORDER BY id",
+            )
+        ]
+
+    def test_load_then_read_back_all_ids(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - A bare sqlite3 connection
+        WHEN:
+            - load() is called with a set of ids
+        THEN:
+            - Every id is present in the TEMP TABLE, and only those ids
+        """
+        PermittedIdsTable.load(conn, [3, 1, 2])
+        assert self._loaded_ids(conn) == [1, 2, 3]
+
+    def test_load_replaces_previous_contents(self, conn: sqlite3.Connection) -> None:
+        """
+        GIVEN:
+            - A connection whose PermittedIdsTable already holds one id set
+        WHEN:
+            - load() is called again with a different id set
+        THEN:
+            - Only the new ids are present -- a connection reused across
+              multiple queries in one request never leaks a stale filter
+        """
+        PermittedIdsTable.load(conn, [1, 2, 3])
+        PermittedIdsTable.load(conn, [4, 5])
+        assert self._loaded_ids(conn) == [4, 5]
+
+    def test_load_is_connection_private(self) -> None:
+        """
+        GIVEN:
+            - Two separate connections
+        WHEN:
+            - Each loads PermittedIdsTable with a different id set, under
+              the identical TABLE_NAME
+        THEN:
+            - Each connection sees only its own ids -- TEMP TABLE is
+              connection-private, so concurrent requests never collide or
+              cross-contaminate despite sharing the same table name (the
+              vector store opens one connection per request; see
+              PaperlessSqliteVecVectorStore)
+        """
+        conn_a = sqlite3.connect(":memory:")
+        conn_a.row_factory = sqlite3.Row
+        conn_b = sqlite3.connect(":memory:")
+        conn_b.row_factory = sqlite3.Row
+        try:
+            PermittedIdsTable.load(conn_a, [1, 2, 3])
+            PermittedIdsTable.load(conn_b, [4, 5, 6])
+            assert self._loaded_ids(conn_a) == [1, 2, 3]
+            assert self._loaded_ids(conn_b) == [4, 5, 6]
+        finally:
+            conn_a.close()
+            conn_b.close()
+
+    def test_load_handles_more_ids_than_a_bound_parameter_list_could(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        """
+        GIVEN:
+            - An id count over SQLite's own bound-parameter limit
+              (SQLITE_MAX_VARIABLE_NUMBER, 32766 by default) -- more than a
+              literal IN(?,?,...) list could ever bind in one statement
+        WHEN:
+            - load() is called with that many ids
+        THEN:
+            - Every id is loaded without error, since executemany() binds
+              one row at a time rather than one statement with N parameters
+        """
+        ids = list(range(40_000))
+        PermittedIdsTable.load(conn, ids)
+        assert self._loaded_ids(conn) == ids

src/paperless_ai/tests/test_vector_store.py

@@ -17,6 +17,7 @@ from paperless_ai.migrations import Migration
 from paperless_ai.migrations import m0001_v1_to_v2
 from paperless_ai.tables import DocumentChunksTable
 from paperless_ai.tables import DocumentMetaTable
+from paperless_ai.tables import PermittedIdsTable
 from paperless_ai.vector_store import _MAX_IN_VALUES
 from paperless_ai.vector_store import DB_FILENAME
 from paperless_ai.vector_store import DEFAULT_TABLE_NAME
@@ -267,8 +268,23 @@ class TestCrud:
 
 
 class TestBuildWhere:
-    def test_ne_filter_translates_to_not_equal_clause(self) -> None:
-        where, params = _build_where(_ne_filter(1))
+    @pytest.fixture
+    def conn(self) -> Generator[sqlite3.Connection, None, None]:
+        """A bare connection, sufficient for _build_where(): it only ever
+        touches the connection via PermittedIdsTable, which needs no vec0
+        extension loaded.
+        """
+        connection = sqlite3.connect(":memory:")
+        try:
+            yield connection
+        finally:
+            connection.close()
+
+    def test_ne_filter_translates_to_not_equal_clause(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
+        where, params = _build_where(conn, _ne_filter(1))
         assert where == "(document_id != ?)"
         assert params == [1]
 
@@ -280,7 +296,10 @@ class TestBuildWhere:
             "b1",
         ]
 
-    def test_fails_closed_when_no_filter_is_translatable(self) -> None:
+    def test_fails_closed_when_no_filter_is_translatable(
+        self,
+        conn: sqlite3.Connection,
+    ) -> None:
         # A nested MetadataFilters is not a MetadataFilter, so it is skipped.
         # With no translatable clauses, the function must fail closed rather
         # than emit "()" (invalid SQL) and never widen document access.
@@ -293,35 +312,74 @@ class TestBuildWhere:
                 ),
             ],
         )
-        where, params = _build_where(MetadataFilters(filters=[nested]))
+        where, params = _build_where(conn, MetadataFilters(filters=[nested]))
         assert where == "1 = 0"
         assert params == []
 
-    def test_fails_closed_when_in_filter_exceeds_max_values(
+    def test_in_filter_over_max_values_uses_permitted_ids_table(
         self,
-        caplog: pytest.LogCaptureFixture,
+        conn: sqlite3.Connection,
     ) -> None:
         """
         GIVEN:
             - An IN filter with more values than _MAX_IN_VALUES (SQLite's
-              own bound-parameter limit is 32766; this guard sits below
+              own bound-parameter limit is 32766; this threshold sits below
               that with headroom for the query's other bound parameters)
         WHEN:
             - _build_where() translates it to SQL
         THEN:
-            - It fails closed ("1 = 0", no params) instead of building an
-              IN clause SQLite would reject, and logs a warning -- this
-              filter scopes document access, so refusing to build it must
-              never widen the scope to "everything" by accident
+            - It builds a subquery against PermittedIdsTable's TEMP TABLE,
+              loaded with every id, instead of a literal IN(...) list that
+              SQLite would reject past its own limit -- the filter still
+              scopes document access to exactly the requested ids, never
+              widening the scope to "everything"
         """
-        oversized = _in_filter([str(i) for i in range(_MAX_IN_VALUES + 1)])
+        ids = list(range(_MAX_IN_VALUES + 1))
+        oversized = _in_filter([str(i) for i in ids])
 
-        with caplog.at_level("WARNING"):
-            where, params = _build_where(oversized)
+        where, params = _build_where(conn, oversized)
 
-        assert where == "(1 = 0)"
+        assert where == (
+            f"(document_id IN (SELECT id FROM {PermittedIdsTable.TABLE_NAME}))"
+        )
         assert params == []
-        assert "document_id" in caplog.text
+        loaded = [
+            row[0]
+            for row in conn.execute(
+                f"SELECT id FROM {PermittedIdsTable.TABLE_NAME} ORDER BY id",
+            )
+        ]
+        assert loaded == ids
+
+    def test_query_and_get_nodes_scope_correctly_when_in_filter_exceeds_max_values(
+        self,
+        store: PaperlessSqliteVecVectorStore,
+        mocker: MockerFixture,
+    ) -> None:
+        """
+        GIVEN:
+            - _MAX_IN_VALUES lowered so a small IN filter exceeds it
+        WHEN:
+            - query() and get_nodes() are called with that filter
+        THEN:
+            - Both still correctly scope results to the permitted ids -- the
+              PermittedIdsTable temp-table path behaves identically to the
+              literal IN(...) path it replaces above the threshold
+        """
+        mocker.patch("paperless_ai.vector_store._MAX_IN_VALUES", 1)
+        store.add(
+            [
+                make_node("a1", 1, seed=0.0),
+                make_node("b1", 2, seed=1.0),
+                make_node("c1", 3, seed=2.0),
+            ],
+        )
+
+        result = _query(store, [0.0] * DIM, top_k=10, filters=_in_filter([2, 3]))
+        nodes = store.get_nodes(filters=_in_filter([2, 3]))
+
+        assert sorted(result.ids) == ["b1", "c1"]
+        assert sorted(n.node_id for n in nodes) == ["b1", "c1"]
 
     def test_query_with_untranslatable_filter_returns_no_rows(
         self,

src/paperless_ai/vector_store.py

@@ -30,6 +30,7 @@ from paperless_ai.tables import DocumentChunksTable
 from paperless_ai.tables import DocumentMetaRow
 from paperless_ai.tables import DocumentMetaTable
 from paperless_ai.tables import IndexMetaTable
+from paperless_ai.tables import PermittedIdsTable
 
 logger = logging.getLogger("paperless_ai.vector_store")
 
@@ -75,14 +76,12 @@ class _Row(NamedTuple):
     embedding: bytes
 
 
-# _build_where(): the largest IN value list translated into bound SQL
-# parameters. SQLite's own hard limit (SQLITE_MAX_VARIABLE_NUMBER) is 32766
-# by default; this leaves headroom below that for the query's other bound
-# parameters (the embedding blob, k, and any NE clause) and for the limit
-# itself to move. An IN filter this large should not happen in practice --
-# callers are expected to pass None (no filter) rather than every id when
-# the filter would not actually narrow anything -- so this is a guard
-# against a future regression, not a normal code path.
+# _build_where(): the largest IN value list translated into a literal
+# IN (?,?,...) clause. SQLite's own hard limit (SQLITE_MAX_VARIABLE_NUMBER)
+# is 32766 by default; this leaves headroom below that for the query's other
+# bound parameters (the embedding blob, k, and any NE clause) and for the
+# limit itself to move. Above this threshold _build_where() switches to
+# PermittedIdsTable instead of failing closed -- see its docstring.
 _MAX_IN_VALUES = 32700
 
 
@@ -106,13 +105,20 @@ def _vec0_params(rows: list[_Row]) -> list[tuple[str, int, str, bytes]]:
     return [(r.chunk_id, r.document_id, r.node_content, r.embedding) for r in rows]
 
 
-def _build_where(filters: MetadataFilters | None) -> tuple[str, list[int]]:
+def _build_where(
+    conn: sqlite3.Connection,
+    filters: MetadataFilters | None,
+) -> tuple[str, list[int]]:
     """Translate the EQ / IN / NE filters we use into a parameterized SQL
     clause on vec0 metadata columns. Returns ("", []) when there is nothing
     to filter. document_id is vec0's only filterable column and is INTEGER;
     every value is coerced via int() here so callers (which today still pass
     strings in places, e.g. indexing.py's MetadataFilter construction) don't
     have to be individually correct -- vec0 doesn't coerce types itself.
+
+    ``conn`` is only used for an IN filter over _MAX_IN_VALUES: it loads the
+    ids into PermittedIdsTable's TEMP TABLE on that connection rather than
+    binding them as SQL parameters.
     """
     if filters is None or not filters.filters:
         return "", []
@@ -131,19 +137,14 @@ def _build_where(filters: MetadataFilters | None) -> tuple[str, list[int]]:
                 clauses.append("1 = 0")
                 continue
             if len(values) > _MAX_IN_VALUES:
-                # Fail closed (see the empty-clauses case below) rather than
-                # let SQLite raise "too many SQL variables" past its own
-                # limit: this filter scopes document access, so an IN list
-                # too large to safely bind must match no rows, never widen
-                # the scope to "everything" by accident.
-                logger.warning(
-                    "Refusing to build an IN filter on %r with %d values "
-                    "(over the %d-value safety limit); returning no rows.",
-                    f.key,
-                    len(values),
-                    _MAX_IN_VALUES,
+                # A literal IN(...) list this large would exceed SQLite's own
+                # bound-parameter limit. Load the ids into a TEMP TABLE on
+                # this connection instead and filter via subquery, which has
+                # no such limit -- see PermittedIdsTable.
+                PermittedIdsTable.load(conn, values)
+                clauses.append(
+                    f"{f.key} IN (SELECT id FROM {PermittedIdsTable.TABLE_NAME})",
                 )
-                clauses.append("1 = 0")
                 continue
             placeholders = ",".join("?" for _ in values)
             clauses.append(f"{f.key} IN ({placeholders})")
@@ -482,7 +483,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
             )
         if not self.table_exists():
             return []
-        where, params = _build_where(filters)
+        where, params = _build_where(self._conn, filters)
         sql = "SELECT node_content, embedding FROM " + DEFAULT_TABLE_NAME
         if where:
             sql += " WHERE " + where
@@ -498,7 +499,7 @@ class PaperlessSqliteVecVectorStore(BasePydanticVectorStore):
         if query.query_embedding is None:  # pragma: no cover
             return VectorStoreQueryResult(nodes=[], similarities=[], ids=[])
         top_k = query.similarity_top_k if query.similarity_top_k is not None else 10
-        where, params = _build_where(query.filters)
+        where, params = _build_where(self._conn, query.filters)
         sql = (
             "SELECT id, node_content, embedding, distance FROM "
             + DEFAULT_TABLE_NAME