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src/paperless_ai/indexing.py

@@ -24,7 +24,6 @@ from paperless_ai.embedding import get_configured_model_name
 from paperless_ai.embedding import get_embedding_model
 
 if TYPE_CHECKING:
-    from django.db.models import QuerySet
     from llama_index.core.schema import BaseNode
 
     from paperless_ai.vector_store import PaperlessSqliteVecVectorStore
@@ -253,20 +252,6 @@ def _safe_related_name(document: Document, field: str) -> str | None:
     return related.name if related else None
 
 
-def _document_index_queryset() -> "QuerySet[Document]":
-    """Document queryset with every relation build_document_node() /
-    build_llm_index_text() touches -- correspondent, document_type,
-    storage_path, tags, notes, custom_fields__field -- pre-loaded, so
-    indexing one document costs a fixed handful of queries regardless of
-    its tag or custom field count, instead of one query per related object.
-    """
-    return Document.objects.select_related(
-        "correspondent",
-        "document_type",
-        "storage_path",
-    ).prefetch_related("tags", "notes", "custom_fields__field")
-
-
 def build_document_node(
     document: Document,
     *,
@@ -440,7 +425,11 @@ def update_llm_index(
                 "Skipping LLM index update: migration check deferred; "
                 "will retry next run."
             )
-    documents = _document_index_queryset()
+    documents = Document.objects.select_related(
+        "correspondent",
+        "document_type",
+        "storage_path",
+    ).prefetch_related("tags", "notes", "custom_fields__field")
     no_documents = not documents.exists()
 
     # Fast exit before touching config: nothing to index and no existing index.
@@ -505,21 +494,6 @@ def update_llm_index(
 def llm_index_add_or_update_document(document: Document):
     """Add or atomically replace a document's chunks in the index."""
     config = AIConfig()
-    document_id = document.id
-    # Re-fetch with the same select_related/prefetch_related shape as the
-    # bulk path (update_llm_index()) uses: the caller's ``document`` instance
-    # (e.g. straight off a signal) has none of that loaded, and
-    # build_document_node()/build_llm_index_text() touch
-    # correspondent/document_type/storage_path/tags/notes/custom_fields__field
-    # -- without prefetching, that's one query per related object, including
-    # one per custom field instance.
-    document = _document_index_queryset().filter(pk=document_id).first()
-    if document is None:
-        logger.info(
-            "Skipping LLM index update for document %s: it no longer exists.",
-            document_id,
-        )
-        return
     new_nodes = build_document_node(
         document,
         chunk_size=config.llm_embedding_chunk_size,

src/paperless_ai/tests/test_ai_indexing.py

@@ -735,71 +735,8 @@ class TestLlmIndexAddOrUpdateDocumentEmptyContent:
         )
         mock_load = mocker.patch("paperless_ai.indexing.load_or_build_index")
 
-        doc = DocumentFactory.create()
-        # Must not raise
-        indexing.llm_index_add_or_update_document(doc)
-
-        mock_load.assert_not_called()
-
-
-@pytest.mark.django_db
-class TestLlmIndexAddOrUpdateDocumentPrefetch:
-    """llm_index_add_or_update_document must prefetch the relations
-    build_document_node()/build_llm_index_text() touch, not re-query per
-    tag/note/custom field.
-    """
-
-    def test_query_count_does_not_scale_with_custom_field_count(
-        self,
-        temp_llm_index_dir: Path,
-        mock_embed_model: FakeEmbedding,
-    ) -> None:
-        """
-        GIVEN a document with several custom fields, a note, and a tag
-        WHEN it is incrementally indexed via llm_index_add_or_update_document
-        THEN the query count stays flat instead of growing with the number
-             of custom fields -- a regression here would add one query per
-             custom field instance (instance.field.name unprefetched), see
-             build_llm_index_text().
-        """
-        doc = DocumentFactory.create()
-        Note.objects.create(document=doc, note="a note")
-        for i in range(5):
-            field = CustomField.objects.create(
-                name=f"Field {i}",
-                data_type=CustomField.FieldDataType.STRING,
-            )
-            CustomFieldInstance.objects.create(
-                document=doc,
-                field=field,
-                value_text="value",
-            )
-
-        with CaptureQueriesContext(connection) as ctx:
-            indexing.llm_index_add_or_update_document(doc)
-
-        # Flat regardless of custom field count -- an unprefetched
-        # custom_fields__field would add one query per instance (5 here) on
-        # top of this budget.
-        assert len(ctx.captured_queries) <= 10
-
-    def test_skips_write_when_document_no_longer_exists(
-        self,
-        temp_llm_index_dir: Path,
-        mock_embed_model: FakeEmbedding,
-        mocker: pytest_mock.MockerFixture,
-    ) -> None:
-        """
-        GIVEN a document that has been deleted since the caller looked it up
-             (e.g. a race between a signal firing and its async task running)
-        WHEN llm_index_add_or_update_document is called with that stale instance
-        THEN it skips the write instead of raising Document.DoesNotExist
-        """
-        doc = DocumentFactory.create()
-        doc_id = doc.pk
-        Document.objects.filter(pk=doc_id).delete()
-        mock_load = mocker.patch("paperless_ai.indexing.load_or_build_index")
-
+        doc = MagicMock(spec=Document)
+        doc.id = 42
         # Must not raise
         indexing.llm_index_add_or_update_document(doc)
 
@@ -856,7 +793,8 @@ class TestLlmIndexLocking:
             return_value=[mock_node],
         )
 
-        doc = DocumentFactory.create()
+        doc = MagicMock(spec=Document)
+        doc.id = 1
         indexing.llm_index_add_or_update_document(doc)
 
         mock_store.upsert_document.assert_called_once()
@@ -887,7 +825,8 @@ class TestLlmIndexLocking:
             return_value=[mock_node],
         )
 
-        doc = DocumentFactory.create()
+        doc = MagicMock(spec=Document)
+        doc.id = 1
         indexing.llm_index_add_or_update_document(doc)
 
         mock_store.upsert_document.assert_not_called()
@@ -924,7 +863,8 @@ class TestLlmIndexLocking:
             return_value=[mock_node],
         )
 
-        doc = DocumentFactory.create()
+        doc = MagicMock(spec=Document)
+        doc.id = 1
         indexing.llm_index_add_or_update_document(doc)
 
         mock_store.upsert_document.assert_not_called()