Deletes _node_document_ids

This brings users without an embedding backend configured to closer
parity with those who do.  Reuse the search backend to locate similar
documents and use them to provide the LLM with the better suggestion pool
to draw from

src/documents/filters.py

@@ -12,6 +12,7 @@ from typing import TYPE_CHECKING
 from typing import Any
 
 from django.contrib.contenttypes.models import ContentType
+from django.core.exceptions import FieldError
 from django.db.models import Case
 from django.db.models import CharField
 from django.db.models import Count
@@ -52,7 +53,6 @@ from documents.models import StoragePath
 from documents.models import Tag
 from documents.permissions import permitted_document_ids
 from documents.permissions import permitted_object_ids
-from documents.versioning import annotate_effective_content
 
 if TYPE_CHECKING:
     from collections.abc import Callable
@@ -182,9 +182,14 @@ class TitleContentFilter(Filter):
             logger.warning(
                 "Deprecated document filter parameter 'title_content' used; use `text` instead.",
             )
-            return annotate_effective_content(qs).filter(
-                Q(title__icontains=value) | Q(effective_content__icontains=value),
-            )
+            try:
+                return qs.filter(
+                    Q(title__icontains=value) | Q(effective_content__icontains=value),
+                )
+            except FieldError:
+                return qs.filter(
+                    Q(title__icontains=value) | Q(content__icontains=value),
+                )
         else:
             return qs
 
@@ -195,9 +200,14 @@ class EffectiveContentFilter(Filter):
         value = value.strip() if isinstance(value, str) else value
         if not value:
             return qs
-        return annotate_effective_content(qs).filter(
-            **{f"effective_content__{self.lookup_expr}": value},
-        )
+        try:
+            return qs.filter(
+                **{f"effective_content__{self.lookup_expr}": value},
+            )
+        except FieldError:
+            return qs.filter(
+                **{f"content__{self.lookup_expr}": value},
+            )
 
 
 @extend_schema_field(serializers.BooleanField)

src/documents/tests/test_api_document_versions.py

@@ -2,12 +2,14 @@ from __future__ import annotations
 
 import datetime
 from typing import TYPE_CHECKING
+from unittest import TestCase
 from unittest import mock
 
 from auditlog.models import LogEntry  # type: ignore[import-untyped]
 from django.contrib.auth.models import Permission
 from django.contrib.auth.models import User
 from django.contrib.contenttypes.models import ContentType
+from django.core.exceptions import FieldError
 from django.core.files.uploadedfile import SimpleUploadedFile
 from django.test import TestCase as DjangoTestCase
 from django.utils import timezone
@@ -20,7 +22,6 @@ from documents.filters import TitleContentFilter
 from documents.models import Document
 from documents.tests.utils import DirectoriesMixin
 from documents.tests.utils import read_streaming_response
-from documents.versioning import annotate_effective_content
 from documents.views import DocumentSelectionMixin
 
 if TYPE_CHECKING:
@@ -891,104 +892,32 @@ class TestDocumentVersioningApi(DirectoriesMixin, APITestCase):
         )
 
 
-class TestVersionAwareFilters(DjangoTestCase):
-    """
-    The filters annotate effective_content themselves rather than relying on
-    the caller's queryset carrying it, so they stay version-aware on a plain
-    Document queryset (e.g. the bulk-edit "select all matching" path).
-    """
+class TestVersionAwareFilters(TestCase):
+    def test_title_content_filter_falls_back_to_content(self) -> None:
+        queryset = mock.Mock()
+        fallback_queryset = mock.Mock()
+        queryset.filter.side_effect = [FieldError("missing field"), fallback_queryset]
 
-    def setUp(self) -> None:
-        super().setUp()
-        self.root = Document.objects.create(
-            title="root",
-            checksum="root",
-            mime_type="application/pdf",
-            content="superseded-content",
-        )
-        Document.objects.create(
-            title="version",
-            checksum="version",
-            mime_type="application/pdf",
-            root_document=self.root,
-            version_index=1,
-            content="latest-content",
-        )
-        self.unversioned = Document.objects.create(
-            title="unversioned",
-            checksum="unversioned",
-            mime_type="application/pdf",
-            content="latest-content",
-        )
+        result = TitleContentFilter().filter(queryset, " latest ")
 
-    def test_title_content_filter_matches_latest_version_content(self) -> None:
-        result = TitleContentFilter().filter(
-            Document.objects.filter(root_document__isnull=True),
+        self.assertIs(result, fallback_queryset)
+        self.assertEqual(queryset.filter.call_count, 2)
+
+    def test_effective_content_filter_falls_back_to_content_lookup(self) -> None:
+        queryset = mock.Mock()
+        fallback_queryset = mock.Mock()
+        queryset.filter.side_effect = [FieldError("missing field"), fallback_queryset]
+
+        result = EffectiveContentFilter(lookup_expr="icontains").filter(
+            queryset,
             " latest ",
         )
 
-        self.assertCountEqual(
-            [doc.id for doc in result],
-            [self.root.id, self.unversioned.id],
-        )
-
-    def test_effective_content_filter_matches_latest_version_content(self) -> None:
-        result = EffectiveContentFilter(lookup_expr="icontains").filter(
-            Document.objects.filter(root_document__isnull=True),
-            " latest ",
-        )
-
-        self.assertCountEqual(
-            [doc.id for doc in result],
-            [self.root.id, self.unversioned.id],
-        )
-
-    def test_effective_content_filter_ignores_superseded_content(self) -> None:
-        result = EffectiveContentFilter(lookup_expr="icontains").filter(
-            Document.objects.filter(root_document__isnull=True),
-            "superseded",
-        )
-
-        self.assertEqual(list(result), [])
-
-    def test_filters_reuse_an_existing_annotation(self) -> None:
-        """
-        Annotating twice under the same alias is an error, so an already
-        annotated queryset (the search path) has to be left alone.
-        """
-        annotated = annotate_effective_content(
-            Document.objects.filter(root_document__isnull=True),
-        )
-        self.assertIs(annotate_effective_content(annotated), annotated)
-
-        result = EffectiveContentFilter(lookup_expr="icontains").filter(
-            annotated,
-            "latest",
-        )
-
-        self.assertCountEqual(
-            [doc.id for doc in result],
-            [self.root.id, self.unversioned.id],
-        )
-
-    def test_bulk_selection_does_not_match_superseded_content(self) -> None:
-        """
-        Bulk edit's "select all matching" builds its own queryset, so before
-        the filters annotated for themselves it matched the root document's
-        superseded content -- selecting documents the list view, filtered by
-        the same term, does not show.
-        """
-        user = User.objects.create_superuser(username="bulk_selection")
-
-        selected = DocumentSelectionMixin()._resolve_document_ids(
-            user=user,
-            validated_data={
-                "all": True,
-                "filters": {"content__icontains": "superseded"},
-            },
-        )
-
-        self.assertEqual(selected, [])
+        self.assertIs(result, fallback_queryset)
+        first_kwargs = queryset.filter.call_args_list[0].kwargs
+        second_kwargs = queryset.filter.call_args_list[1].kwargs
+        self.assertEqual(first_kwargs, {"effective_content__icontains": "latest"})
+        self.assertEqual(second_kwargs, {"content__icontains": "latest"})
 
     def test_effective_content_filter_returns_input_for_empty_values(self) -> None:
         queryset = mock.Mock()

src/documents/tests/test_api_search.py

@@ -1947,29 +1947,6 @@ class TestDocumentSearchApi(DirectoriesMixin, APITestCase):
         self.assertEqual(len(response.data["documents"]), 1)
         self.assertEqual(response.data["documents"][0]["id"], title_match.id)
 
-    def test_global_search_returns_latest_version_content(self) -> None:
-        root = Document.objects.create(
-            title="bank statement",
-            content="superseded content",
-            checksum="GSV1",
-            pk=23,
-        )
-        Document.objects.create(
-            title="bank statement v2",
-            content="latest content",
-            checksum="GSV2",
-            pk=24,
-            root_document=root,
-            version_index=1,
-        )
-
-        self.client.force_authenticate(self.user)
-
-        response = self.client.get("/api/search/?query=bank&db_only=true")
-        self.assertEqual(response.status_code, status.HTTP_200_OK)
-        returned = {doc["id"]: doc["content"] for doc in response.data["documents"]}
-        self.assertEqual(returned.get(root.id), "latest content")
-
     def test_global_search_filters_owned_mail_objects(self) -> None:
         user1 = User.objects.create_user("mail-search-user")
         user2 = User.objects.create_user("other-mail-search-user")

src/documents/versioning.py

@@ -27,13 +27,10 @@ def versions_newest_first(documents: QuerySet[Document]) -> QuerySet[Document]:
 
 def annotate_effective_content(documents: QuerySet[Document]) -> QuerySet[Document]:
     """
-    Annotates documents with the content of their newest version unless the
-    queryset already carries the annotation, falling back to their own, so
-    get_effective_content() can answer from the row rather than querying for
-    the versions of each document.
+    Annotates documents with the content of their newest version, falling back
+    to their own, so get_effective_content() can answer from the row rather
+    than querying for the versions of each document
     """
-    if "effective_content" in documents.query.annotations:
-        return documents
     return documents.annotate(
         effective_content=Coalesce(
             Subquery(

src/documents/views.py

@@ -232,7 +232,6 @@ from documents.tasks import train_classifier
 from documents.tasks import update_document_parent_tags
 from documents.utils import get_boolean
 from documents.versioning import VersionResolutionError
-from documents.versioning import annotate_effective_content
 from documents.versioning import get_latest_version_for_root
 from documents.versioning import get_request_version_param
 from documents.versioning import get_root_document
@@ -3633,13 +3632,8 @@ class GlobalSearchView(PassUserMixin):
         OBJECT_LIMIT = 3
         docs = []
         if request.user.has_perm("documents.view_document"):
-            # Never more than OBJECT_LIMIT rows come back here, so annotating
-            # is cheap -- and without it these results show the root
-            # document's superseded content.
-            all_docs = annotate_effective_content(
-                Document.objects.filter(
-                    id__in=permitted_document_ids(request.user),
-                ),
+            all_docs = Document.objects.filter(
+                id__in=permitted_document_ids(request.user),
             )
             if db_only:
                 docs = all_docs.filter(title__icontains=query)[:OBJECT_LIMIT]

src/locale/en_US/LC_MESSAGES/django.po

@@ -2,7 +2,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: paperless-ngx\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2026-09-08 15:56+0000\n"
+"POT-Creation-Date: 2026-09-08 15:31+0000\n"
 "PO-Revision-Date: 2022-02-17 04:17\n"
 "Last-Translator: \n"
 "Language-Team: English\n"
@@ -21,39 +21,39 @@ msgstr ""
 msgid "Documents"
 msgstr ""
 
-#: documents/filters.py:463
+#: documents/filters.py:473
 msgid "Value must be valid JSON."
 msgstr ""
 
-#: documents/filters.py:482
+#: documents/filters.py:492
 msgid "Invalid custom field query expression"
 msgstr ""
 
-#: documents/filters.py:492
+#: documents/filters.py:502
 msgid "Invalid expression list. Must be nonempty."
 msgstr ""
 
-#: documents/filters.py:513
+#: documents/filters.py:523
 msgid "Invalid logical operator {op!r}"
 msgstr ""
 
-#: documents/filters.py:527
+#: documents/filters.py:537
 msgid "Maximum number of query conditions exceeded."
 msgstr ""
 
-#: documents/filters.py:591
+#: documents/filters.py:601
 msgid "{name!r} is not a valid custom field."
 msgstr ""
 
-#: documents/filters.py:628
+#: documents/filters.py:638
 msgid "{data_type} does not support query expr {expr!r}."
 msgstr ""
 
-#: documents/filters.py:747 documents/models.py:136
+#: documents/filters.py:757 documents/models.py:136
 msgid "Maximum nesting depth exceeded."
 msgstr ""
 
-#: documents/filters.py:1109
+#: documents/filters.py:1119
 msgid "Custom field not found"
 msgstr ""
 
@@ -1632,7 +1632,7 @@ msgid "workflow runs"
 msgstr ""
 
 #: documents/serialisers.py:524 documents/serialisers.py:881
-#: documents/serialisers.py:2841 documents/views.py:315 documents/views.py:2625
+#: documents/serialisers.py:2841 documents/views.py:314 documents/views.py:2624
 #: paperless_mail/serialisers.py:156
 msgid "Insufficient permissions."
 msgstr ""
@@ -1673,7 +1673,7 @@ msgstr ""
 msgid "Duplicate document identifiers are not allowed."
 msgstr ""
 
-#: documents/serialisers.py:2927 documents/views.py:4632
+#: documents/serialisers.py:2927 documents/views.py:4626
 #, python-format
 msgid "Documents not found: %(ids)s"
 msgstr ""
@@ -1941,36 +1941,36 @@ msgstr ""
 msgid "Unable to parse URI {value}"
 msgstr ""
 
-#: documents/views.py:308 documents/views.py:2622
+#: documents/views.py:307 documents/views.py:2621
 msgid "Invalid more_like_id"
 msgstr ""
 
-#: documents/views.py:1592
+#: documents/views.py:1591
 msgid "Invalid AI configuration."
 msgstr ""
 
-#: documents/views.py:1603
+#: documents/views.py:1602
 msgid "AI backend request timed out."
 msgstr ""
 
-#: documents/views.py:2447 documents/views.py:2768
+#: documents/views.py:2446 documents/views.py:2767
 msgid "Specify only one of text, title_search, query, or more_like_id."
 msgstr ""
 
-#: documents/views.py:4645
+#: documents/views.py:4639
 #, python-format
 msgid "Insufficient permissions to share document %(id)s."
 msgstr ""
 
-#: documents/views.py:4691
+#: documents/views.py:4685
 msgid "Bundle is already being processed."
 msgstr ""
 
-#: documents/views.py:4755
+#: documents/views.py:4749
 msgid "The share link bundle is still being prepared. Please try again later."
 msgstr ""
 
-#: documents/views.py:4769
+#: documents/views.py:4763
 msgid "The share link bundle is unavailable."
 msgstr ""
 

src/paperless_ai/ai_classifier.py

@@ -4,21 +4,24 @@ from django.conf import settings
 from django.contrib.auth.models import User
 
 from documents.models import Document
-from documents.permissions import get_objects_for_user_owner_aware
+from documents.permissions import permitted_object_ids
+from documents.permissions import restrict_queryset_to_visible
+from documents.permissions import user_is_unrestricted
 from paperless.config import AIConfig
 from paperless_ai.base_model import ClassificationSuggestions
 from paperless_ai.base_model import TaxonomyChoiceDict
 from paperless_ai.base_model import classification_suggestions_to_model
 from paperless_ai.client import AIClient
 from paperless_ai.db import db_connection_released
-from paperless_ai.indexing import _node_document_ids
 from paperless_ai.indexing import retrieve_similar_nodes
 from paperless_ai.indexing import truncate_content
 from paperless_ai.prompts.context import ClassificationPromptContext
 from paperless_ai.prompts.context import LocalizationPromptContext
 from paperless_ai.prompts.context import RagContextPromptContext
 from paperless_ai.prompts.render import render_prompt
+from paperless_ai.taxonomy import SimilarDocument
 from paperless_ai.taxonomy import TaxonomyCandidates
+from paperless_ai.taxonomy import _node_document_weights
 from paperless_ai.taxonomy import build_taxonomy_candidates
 from paperless_ai.taxonomy import empty_taxonomy_candidates
 from paperless_ai.taxonomy import format_taxonomy_for_prompt
@@ -37,6 +40,48 @@ logger = logging.getLogger("paperless_ai.rag_classifier")
 TAXONOMY_CANDIDATE_TOP_K = 15
 
 
+def _fulltext_similar_documents(
+    document: Document,
+    user: User | None,
+    top_k: int,
+) -> list[SimilarDocument]:
+    """Rank-based fallback when no embedding backend is configured. Uses
+    Tantivy's "More Like This" (term-overlap similarity) instead of vector
+    similarity - cruder, but far better than no candidates at all.
+    more_like_this_ids returns only a ranked ID list, no scores, so weight is
+    synthesized from rank (descending from top_k) rather than claiming a
+    similarity magnitude that doesn't exist. An unrestricted user (none, or an
+    active superuser - see user_is_unrestricted) is normalized to ``None``
+    before calling, since the backend's permission filter has no superuser
+    short-circuit of its own. Results are re-checked with
+    restrict_queryset_to_visible() since Tantivy's indexed permission fields
+    lag the DB via async reindexing.
+    """
+    from documents.search import get_backend
+
+    unrestricted = user_is_unrestricted(user)
+    search_user = None if unrestricted else user
+    backend = get_backend()
+    similar_ids = backend.more_like_this_ids(
+        document.pk,
+        user=search_user,
+        limit=top_k,
+    )
+    if not unrestricted:
+        allowed_ids = set(
+            restrict_queryset_to_visible(
+                Document.objects.filter(pk__in=similar_ids),
+                user,
+                "view_document",
+            ).values_list("pk", flat=True),
+        )
+        similar_ids = [doc_id for doc_id in similar_ids if doc_id in allowed_ids]
+    return [
+        SimilarDocument(document_id=doc_id, weight=float(top_k - rank))
+        for rank, doc_id in enumerate(similar_ids)
+    ]
+
+
 def get_language_name(language_code: str) -> str:
     normalized_language_code = language_code.lower()
     for code, name in settings.LANGUAGES:
@@ -136,43 +181,52 @@ def get_taxonomy_context(
     user: User | None = None,
     max_docs: int = 5,
 ) -> tuple[TaxonomyCandidates, str]:
-    """One retrieval feeds both taxonomy candidates and RAG text context.
-    On any retrieval failure, degrades to empty candidates/context rather than
-    propagating the exception - a vector-store outage should not block
-    classification, only its RAG-assisted enrichment.
+    """One retrieval feeds both taxonomy candidates and RAG text context. Uses
+    vector similarity when an embedding backend is configured, otherwise
+    falls back to Tantivy full-text "More Like This" similarity - see
+    _fulltext_similar_documents. On any retrieval failure, degrades to empty
+    candidates/context rather than propagating the exception - neither a
+    vector-store outage nor a search-index issue should block classification,
+    only its context-assisted enrichment.
     """
+    ai_config = AIConfig()
     try:
-        # None means "no restriction" to retrieve_similar_nodes. A superuser
-        # (like no user at all) can see every document, so skip materializing
-        # every visible pk into a Python list and passing it through as an IN
-        # filter: for a large library that is a wasted quadratic scan in the
-        # vector store at best, and past ~32,763 documents a hard
-        # sqlite3.OperationalError (SQLite's bound-parameter limit) at worst.
-        # get_objects_for_user_owner_aware() would return every Document for a
-        # superuser anyway (guardian's own with_superuser shortcut), so this
-        # changes nothing about which documents are considered -- only how we
-        # get there.
-        visible_document_ids = (
-            None
-            if user is None or user.is_superuser
-            else list(
-                get_objects_for_user_owner_aware(
-                    user,
-                    "view_document",
-                    Document,
-                ).values_list("pk", flat=True),
+        if ai_config.llm_embedding_backend:
+            # None means "no restriction" to retrieve_similar_nodes. An
+            # unrestricted user (no user at all, or an active superuser -- see
+            # user_is_unrestricted) can see every document, so skip
+            # materializing every visible pk into a Python list and passing it
+            # through as an IN filter: for a large library that is a wasted
+            # quadratic scan in the vector store at best, and past ~32,763
+            # documents a hard sqlite3.OperationalError (SQLite's
+            # bound-parameter limit) at worst.
+            # permitted_object_ids() has its own superuser shortcut that would
+            # return every Document's id anyway, so this changes nothing about
+            # which documents are considered -- only how we get there.
+            visible_document_ids = (
+                None
+                if user_is_unrestricted(user)
+                else list(permitted_object_ids(user, Document, "view_document"))
+            )
+            nodes = retrieve_similar_nodes(
+                document,
+                top_k=TAXONOMY_CANDIDATE_TOP_K,
+                document_ids=visible_document_ids,
+            )
+            similar_documents = _node_document_weights(nodes)
+        else:
+            # See _fulltext_similar_documents: it applies its own permission
+            # filter via `user`, so no visible-document-id list is needed here.
+            similar_documents = _fulltext_similar_documents(
+                document,
+                user,
+                top_k=TAXONOMY_CANDIDATE_TOP_K,
             )
-        )
-        nodes = retrieve_similar_nodes(
-            document,
-            top_k=TAXONOMY_CANDIDATE_TOP_K,
-            document_ids=visible_document_ids,
-        )
 
-        candidates = build_taxonomy_candidates(nodes, user)
+        candidates = build_taxonomy_candidates(similar_documents, user)
 
-        # ``nodes`` are already ordered by descending vector similarity; don't lose it.
-        similar_document_ids = list(dict.fromkeys(_node_document_ids(nodes)))
+        # similar_documents is already ordered by descending weight; don't lose it.
+        similar_document_ids = [s["document_id"] for s in similar_documents]
         similar_documents_by_id = Document.objects.in_bulk(similar_document_ids)
         similar_docs = [
             similar_documents_by_id[document_id]
@@ -186,8 +240,8 @@ def get_taxonomy_context(
             context_blocks.append(f"TITLE: {title}\n{text}")
     except Exception:
         logger.exception(
-            "Failed to retrieve RAG neighbours for document %s; continuing "
-            "without taxonomy candidates or similar-document context.",
+            "Failed to retrieve similar-document context for document %s; "
+            "continuing without taxonomy candidates or similar-document context.",
             document.pk,
         )
         return empty_taxonomy_candidates(), ""
@@ -241,17 +295,13 @@ def get_ai_document_classification(
 ) -> ClassificationSuggestions:
     ai_config = AIConfig()
 
-    if ai_config.llm_embedding_backend:
-        candidates, context = get_taxonomy_context(document, user)
-        prompt = build_prompt_with_rag(
-            document,
-            ai_config,
-            candidates=candidates,
-            context=context,
-        )
-    else:
-        candidates = empty_taxonomy_candidates()
-        prompt = build_prompt_without_rag(document, ai_config, candidates=candidates)
+    candidates, context = get_taxonomy_context(document, user)
+    prompt = build_prompt_with_rag(
+        document,
+        ai_config,
+        candidates=candidates,
+        context=context,
+    )
 
     client = AIClient()
     # Hand the pooled DB connection back while the (slow) LLM query runs so it

src/paperless_ai/indexing.py

@@ -721,20 +721,3 @@ def retrieve_similar_nodes(
             continue
         filtered.append(node)
     return filtered
-
-
-def _node_document_ids(nodes: list["NodeWithScore"]) -> list[int]:
-    document_ids: list[int] = []
-    for node in nodes:
-        document_id = node.metadata.get("document_id")
-        if document_id is None:  # pragma: no cover
-            # See the matching guard in retrieve_similar_nodes() above.
-            continue
-        try:
-            document_ids.append(int(document_id))
-        except ValueError:  # pragma: no cover
-            logger.warning(
-                "Skipping LLM index result with invalid document_id %r.",
-                document_id,
-            )
-    return document_ids

src/paperless_ai/taxonomy.py

@@ -31,6 +31,11 @@ class TaxonomyCandidate(TypedDict):
     weight: float
 
 
+class SimilarDocument(TypedDict):
+    document_id: int
+    weight: float
+
+
 class TaxonomyCandidates(TypedDict):
     tags: list[TaxonomyCandidate]
     document_types: list[TaxonomyCandidate]
@@ -49,10 +54,10 @@ def empty_taxonomy_candidates() -> TaxonomyCandidates:
     )
 
 
-def _node_document_weights(nodes: list["NodeWithScore"]) -> dict[int, float]:
-    """document_id -> that node's similarity score, summed if a document_id
-    appears more than once across the retrieved nodes (e.g. multiple chunks
-    of the same source document)."""
+def _node_document_weights(nodes: list["NodeWithScore"]) -> list[SimilarDocument]:
+    """Sum each node's similarity score into its document_id (a document can
+    appear via multiple chunks/nodes) and return one SimilarDocument per
+    distinct document_id."""
     weights: dict[int, float] = defaultdict(float)
     for node in nodes:
         document_id = node.metadata.get("document_id")
@@ -65,7 +70,14 @@ def _node_document_weights(nodes: list["NodeWithScore"]) -> dict[int, float]:
             weights[int(document_id)] += float(node.score or 0.0)
         except (TypeError, ValueError):  # pragma: no cover
             continue
-    return weights
+    return sorted(
+        (
+            SimilarDocument(document_id=document_id, weight=weight)
+            for document_id, weight in weights.items()
+        ),
+        key=lambda similar: similar["weight"],
+        reverse=True,
+    )
 
 
 def _visible_ranked_candidates(
@@ -101,21 +113,26 @@ def _visible_ranked_candidates(
 
 
 def build_taxonomy_candidates(
-    nodes: list["NodeWithScore"],
+    similar_documents: list[SimilarDocument],
     user: User | None,
 ) -> TaxonomyCandidates:
-    """Resolve each neighbour node's document_id to a live Document, read its
-    *current* tags/type/correspondent/storage_path via the ORM (never the
-    possibly-stale names cached in vector-index node metadata), weight each
-    distinct taxonomy object by aggregate neighbour similarity, permission-filter
+    """Resolve each similar document's id to a live Document, read its
+    *current* tags/type/correspondent/storage_path via the ORM (never any
+    possibly-stale names an adapter's source might have cached), weight each
+    distinct taxonomy object by aggregate similarity weight, permission-filter
     against what ``user`` can see, and return each category ranked by weight
-    and capped.
+    and capped. ``similar_documents`` may come from either the vector-RAG
+    adapter or the full-text fallback adapter - both produce this same shape.
     """
-
-    document_weights = _node_document_weights(nodes)
-    if not document_weights:
+    if not similar_documents:
         return empty_taxonomy_candidates()
 
+    # Both adapters guarantee at most one SimilarDocument per document_id, so
+    # this never silently drops a duplicate's weight.
+    document_weights: dict[int, float] = {
+        s["document_id"]: s["weight"] for s in similar_documents
+    }
+
     # Only .tags.all() needs prefetching (a reverse M2M, one extra query for
     # the whole batch). document_type/correspondent/storage_path are read
     # below via their *_id columns (neighbour.document_type_id, etc.), which

src/paperless_ai/tests/test_ai_classifier.py

@@ -1,4 +1,5 @@
 import datetime
+from collections.abc import Generator
 from types import SimpleNamespace
 from unittest.mock import MagicMock
 from unittest.mock import patch
@@ -6,18 +7,24 @@ from unittest.mock import patch
 import pytest
 import pytest_mock
 from django.test import override_settings
+from guardian.shortcuts import assign_perm
+from guardian.shortcuts import remove_perm
 
 from documents.models import Document
+from documents.search import TantivyBackend
 from documents.tests.factories import DocumentFactory
 from documents.tests.factories import TagFactory
 from documents.tests.factories import UserFactory
 from paperless.config import AIConfig
+from paperless_ai.ai_classifier import TAXONOMY_CANDIDATE_TOP_K
+from paperless_ai.ai_classifier import _fulltext_similar_documents
 from paperless_ai.ai_classifier import build_localization_prompt
 from paperless_ai.ai_classifier import build_prompt_with_rag
 from paperless_ai.ai_classifier import build_prompt_without_rag
 from paperless_ai.ai_classifier import get_ai_document_classification
 from paperless_ai.ai_classifier import get_language_name
 from paperless_ai.ai_classifier import get_taxonomy_context
+from paperless_ai.taxonomy import SimilarDocument
 from paperless_ai.taxonomy import TaxonomyCandidate
 from paperless_ai.taxonomy import TaxonomyCandidates
 
@@ -220,12 +227,10 @@ def test_use_rag_if_configured(
 
 @pytest.mark.django_db
 @patch("paperless_ai.client.AIClient.run_llm_query")
-@patch("paperless_ai.ai_classifier.build_prompt_without_rag")
-@patch("paperless_ai.ai_classifier.AIConfig")
+@patch("paperless_ai.ai_classifier.build_prompt_with_rag")
 @override_settings(LLM_BACKEND="ollama", LLM_MODEL="some_model")
-def test_use_without_rag_if_not_configured(
-    mock_ai_config,
-    mock_build_prompt_without_rag,
+def test_use_rag_prompt_even_without_embedding_backend(
+    mock_build_prompt_with_rag,
     mock_run_llm_query,
     mock_document,
 ):
@@ -235,13 +240,13 @@ def test_use_without_rag_if_not_configured(
     WHEN:
         - get_ai_document_classification() is called
     THEN:
-        - The non-RAG prompt builder is used
+        - The RAG-context prompt builder is still used (fed by the full-text
+          fallback's context/candidates instead of the vector store's)
     """
-    mock_ai_config.return_value.llm_embedding_backend = None
-    mock_build_prompt_without_rag.return_value = "Prompt without RAG"
+    mock_build_prompt_with_rag.return_value = "Prompt with RAG"
     mock_run_llm_query.return_value = NESTED_SUGGESTIONS
     get_ai_document_classification(mock_document)
-    mock_build_prompt_without_rag.assert_called_once()
+    mock_build_prompt_with_rag.assert_called_once()
 
 
 @pytest.mark.django_db
@@ -320,6 +325,7 @@ def test_build_localization_prompt_preserves_unicode_characters():
 
 
 @pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
 def test_get_taxonomy_context_assembles_rag_text_and_candidates():
     """
     GIVEN:
@@ -354,6 +360,7 @@ def test_get_taxonomy_context_assembles_rag_text_and_candidates():
 
 
 @pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
 def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents():
     """
     GIVEN:
@@ -424,6 +431,7 @@ def test_get_taxonomy_context_preserves_similarity_order_and_distinct_documents(
 
 
 @pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
 def test_get_taxonomy_context_no_similar_docs():
     """
     GIVEN:
@@ -447,6 +455,67 @@ def test_get_taxonomy_context_no_similar_docs():
     }
 
 
+@pytest.mark.django_db
+def test_get_taxonomy_context_uses_fulltext_fallback_when_no_embedding_backend(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    """
+    GIVEN:
+        - No LLM embedding backend is configured (the default test settings)
+    WHEN:
+        - get_taxonomy_context() is called
+    THEN:
+        - _fulltext_similar_documents() is called with the document, the user
+          and TAXONOMY_CANDIDATE_TOP_K
+        - retrieve_similar_nodes() (the vector path) is never called
+    """
+    document = DocumentFactory.create(content="Some content")
+    mock_fulltext = mocker.patch(
+        "paperless_ai.ai_classifier._fulltext_similar_documents",
+        return_value=[],
+    )
+    mock_retrieve = mocker.patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
+
+    get_taxonomy_context(document, user=None)
+
+    mock_fulltext.assert_called_once_with(
+        document,
+        None,
+        top_k=TAXONOMY_CANDIDATE_TOP_K,
+    )
+    mock_retrieve.assert_not_called()
+
+
+@pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
+def test_get_taxonomy_context_uses_vector_path_when_embedding_backend_configured(
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    """
+    GIVEN:
+        - An LLM embedding backend is configured
+    WHEN:
+        - get_taxonomy_context() is called
+    THEN:
+        - retrieve_similar_nodes() (the vector path) is called
+        - _fulltext_similar_documents() (the no-embedding-backend fallback)
+          is never called
+    """
+    document = DocumentFactory.create(content="Some content")
+    mock_retrieve = mocker.patch(
+        "paperless_ai.ai_classifier.retrieve_similar_nodes",
+        return_value=[],
+    )
+    mock_fulltext = mocker.patch(
+        "paperless_ai.ai_classifier._fulltext_similar_documents",
+    )
+
+    get_taxonomy_context(document, user=None)
+
+    mock_retrieve.assert_called_once()
+    mock_fulltext.assert_not_called()
+
+
 class TestGetTaxonomyContextVisibility:
     """get_taxonomy_context must not materialize every visible document id
     for a user who can already see the whole library: a superuser (like no
@@ -459,6 +528,7 @@ class TestGetTaxonomyContextVisibility:
     """
 
     @pytest.mark.django_db
+    @override_settings(LLM_EMBEDDING_BACKEND="huggingface")
     def test_skips_permission_lookup_for_superuser(
         self,
         mocker: pytest_mock.MockerFixture,
@@ -477,17 +547,18 @@ class TestGetTaxonomyContextVisibility:
             "paperless_ai.ai_classifier.retrieve_similar_nodes",
             return_value=[],
         )
-        mock_get_objects = mocker.patch(
-            "paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
+        mock_permitted = mocker.patch(
+            "paperless_ai.ai_classifier.permitted_object_ids",
         )
         user = UserFactory.create(is_superuser=True)
 
         get_taxonomy_context(document, user)
 
-        mock_get_objects.assert_not_called()
+        mock_permitted.assert_not_called()
         assert mock_retrieve.call_args.kwargs["document_ids"] is None
 
     @pytest.mark.django_db
+    @override_settings(LLM_EMBEDDING_BACKEND="huggingface")
     def test_skips_permission_lookup_when_no_user(
         self,
         mocker: pytest_mock.MockerFixture,
@@ -506,16 +577,17 @@ class TestGetTaxonomyContextVisibility:
             "paperless_ai.ai_classifier.retrieve_similar_nodes",
             return_value=[],
         )
-        mock_get_objects = mocker.patch(
-            "paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
+        mock_permitted = mocker.patch(
+            "paperless_ai.ai_classifier.permitted_object_ids",
         )
 
         get_taxonomy_context(document, None)
 
-        mock_get_objects.assert_not_called()
+        mock_permitted.assert_not_called()
         assert mock_retrieve.call_args.kwargs["document_ids"] is None
 
     @pytest.mark.django_db
+    @override_settings(LLM_EMBEDDING_BACKEND="huggingface")
     def test_restricts_to_visible_documents_for_non_superuser(
         self,
         mocker: pytest_mock.MockerFixture,
@@ -526,7 +598,7 @@ class TestGetTaxonomyContextVisibility:
         WHEN:
             - get_taxonomy_context() is called
         THEN:
-            - The user's visible document ids are looked up and passed to
+            - The user's permitted document ids are looked up and passed to
               retrieve_similar_nodes() as a restriction
         """
         document = DocumentFactory.create(content="Some content")
@@ -534,21 +606,232 @@ class TestGetTaxonomyContextVisibility:
             "paperless_ai.ai_classifier.retrieve_similar_nodes",
             return_value=[],
         )
-        mock_queryset = mocker.MagicMock()
-        mock_queryset.values_list.return_value = [1, 2, 3]
-        mock_get_objects = mocker.patch(
-            "paperless_ai.ai_classifier.get_objects_for_user_owner_aware",
-            return_value=mock_queryset,
+        mock_permitted = mocker.patch(
+            "paperless_ai.ai_classifier.permitted_object_ids",
+            return_value=[1, 2, 3],
         )
         user = UserFactory.create(is_superuser=False)
 
         get_taxonomy_context(document, user)
 
-        mock_get_objects.assert_called_once_with(user, "view_document", Document)
+        mock_permitted.assert_called_once_with(user, Document, "view_document")
         assert mock_retrieve.call_args.kwargs["document_ids"] == [1, 2, 3]
 
 
 @pytest.mark.django_db
+class TestFulltextSimilarDocuments:
+    """_fulltext_similar_documents is the no-embedding-backend fallback: it
+    asks the Tantivy full-text index for "More Like This" neighbours instead
+    of the vector store, and synthesizes a rank-based weight since Tantivy's
+    more_like_this_ids returns only an ordered id list, no scores.
+    """
+
+    @pytest.fixture
+    def fulltext_backend(
+        self,
+        mocker: pytest_mock.MockerFixture,
+    ) -> Generator[TantivyBackend, None, None]:
+        """An in-memory Tantivy backend, wired up as the module-level
+        singleton _fulltext_similar_documents resolves via get_backend()."""
+        backend = TantivyBackend(path=None)
+        backend.open()
+        mocker.patch("documents.search.get_backend", return_value=backend)
+        try:
+            yield backend
+        finally:
+            backend.close()
+
+    def test_ranks_by_rank_based_weight_descending(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A source document and two similar documents indexed in Tantivy
+        WHEN:
+            - _fulltext_similar_documents() is called
+        THEN:
+            - Each result's weight reflects its rank (first result weighted
+              higher than the second), not a raw similarity score
+        """
+        source = DocumentFactory.create(content="quarterly financial report details")
+        first = DocumentFactory.create(content="quarterly financial report details")
+        second = DocumentFactory.create(content="financial report")
+        for doc in (source, first, second):
+            fulltext_backend.add_or_update(doc)
+
+        result = _fulltext_similar_documents(source, user=None, top_k=5)
+
+        assert len(result) == 2
+        weight_by_id = {s["document_id"]: s["weight"] for s in result}
+        assert weight_by_id[first.pk] > weight_by_id[second.pk]
+
+    def test_excludes_source_document(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A source document indexed in Tantivy with no other documents
+        WHEN:
+            - _fulltext_similar_documents() is called
+        THEN:
+            - An empty list is returned - the source document is never its
+              own similar document
+        """
+        source = DocumentFactory.create(content="unique unrelated content")
+        fulltext_backend.add_or_update(source)
+
+        result = _fulltext_similar_documents(source, user=None, top_k=5)
+
+        assert result == []
+
+    def test_empty_index_returns_empty_list(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A document that has never been indexed (fresh/empty Tantivy index)
+        WHEN:
+            - _fulltext_similar_documents() is called
+        THEN:
+            - An empty list is returned rather than raising
+        """
+        source = DocumentFactory.create(content="never indexed")
+
+        result = _fulltext_similar_documents(source, user=None, top_k=5)
+
+        assert result == []
+
+    def test_respects_top_k_limit(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A source document and four similar documents indexed
+        WHEN:
+            - _fulltext_similar_documents() is called with top_k=2
+        THEN:
+            - At most 2 results are returned
+        """
+        source = DocumentFactory.create(content="shared overlapping keyword text")
+        fulltext_backend.add_or_update(source)
+        for _ in range(4):
+            fulltext_backend.add_or_update(
+                DocumentFactory.create(content="shared overlapping keyword text"),
+            )
+
+        result = _fulltext_similar_documents(source, user=None, top_k=2)
+
+        assert len(result) == 2
+
+    def test_result_shape_is_similar_document(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A source document and one similar document indexed
+        WHEN:
+            - _fulltext_similar_documents() is called
+        THEN:
+            - Each result is a SimilarDocument (document_id + weight only)
+        """
+        source = DocumentFactory.create(content="shared content phrase")
+        other = DocumentFactory.create(content="shared content phrase")
+        fulltext_backend.add_or_update(source)
+        fulltext_backend.add_or_update(other)
+
+        result = _fulltext_similar_documents(source, user=None, top_k=5)
+
+        # rank 0 (the only/best result) with top_k=5 -> weight = top_k - rank = 5.0,
+        # per the "first result gets top_k, the last gets 1" formula.
+        assert result == [SimilarDocument(document_id=other.pk, weight=5.0)]
+
+    def test_superuser_sees_other_users_documents(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A source document owned by one user and a similar document
+              owned by a different user, with no sharing between them
+        WHEN:
+            - _fulltext_similar_documents() is called with a superuser
+        THEN:
+            - The other user's document is still returned as a similar
+              document - a superuser must not be narrowed by the backend's
+              owner-based permission filter
+        """
+        owner = UserFactory.create()
+        other_owner = UserFactory.create()
+        superuser = UserFactory.create(is_superuser=True)
+        source = DocumentFactory.create(
+            content="shared content phrase",
+            owner=owner,
+        )
+        other = DocumentFactory.create(
+            content="shared content phrase",
+            owner=other_owner,
+        )
+        fulltext_backend.add_or_update(source)
+        fulltext_backend.add_or_update(other)
+
+        result = _fulltext_similar_documents(source, user=superuser, top_k=5)
+
+        assert [s["document_id"] for s in result] == [other.pk]
+
+    def test_excludes_stale_permitted_document_for_regular_user(
+        self,
+        fulltext_backend: TantivyBackend,
+    ) -> None:
+        """
+        GIVEN:
+            - A regular (non-superuser) user
+            - A similar document the user is permitted to view, and another
+              similar document indexed while the user still had view
+              permission but which has since had that permission revoked in
+              the database, i.e. the Tantivy index has stale permission data
+        WHEN:
+            - _fulltext_similar_documents() is called with that user
+        THEN:
+            - Only the still-permitted document is returned - the DB
+              re-check via restrict_queryset_to_visible() must catch the
+              document Tantivy's stale index still thinks is visible
+        """
+        owner = UserFactory.create()
+        viewer = UserFactory.create(is_superuser=False)
+        source = DocumentFactory.create(
+            content="shared content phrase",
+            owner=owner,
+        )
+        permitted = DocumentFactory.create(
+            content="shared content phrase",
+            owner=owner,
+        )
+        now_private = DocumentFactory.create(
+            content="shared content phrase",
+            owner=owner,
+        )
+        assign_perm("view_document", viewer, permitted)
+        assign_perm("view_document", viewer, now_private)
+        fulltext_backend.add_or_update(source)
+        fulltext_backend.add_or_update(permitted)
+        fulltext_backend.add_or_update(now_private)
+
+        # Revoke access after indexing, without reindexing: the index still
+        # carries viewer as a permitted viewer for `now_private`.
+        remove_perm("view_document", viewer, now_private)
+
+        result = _fulltext_similar_documents(source, user=viewer, top_k=5)
+
+        assert [s["document_id"] for s in result] == [permitted.pk]
+
+
+@pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
 @patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
 def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrieve):
     """
@@ -575,6 +858,7 @@ def test_get_taxonomy_context_retrieval_failure_degrades_to_no_hints(mock_retrie
 
 
 @pytest.mark.django_db
+@override_settings(LLM_EMBEDDING_BACKEND="huggingface")
 @patch("paperless_ai.ai_classifier.build_taxonomy_candidates")
 @patch("paperless_ai.ai_classifier.retrieve_similar_nodes")
 def test_get_taxonomy_context_candidate_building_failure_degrades_to_no_hints(

src/paperless_ai/tests/test_ai_indexing.py

@@ -1188,9 +1188,7 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
 
         nodes = indexing.retrieve_similar_nodes(a, document_ids=[b.id])
 
-        assert all(
-            document_id == b.id for document_id in indexing._node_document_ids(nodes)
-        )
+        assert all(int(node.metadata["document_id"]) == b.id for node in nodes)
 
     def test_excludes_self(
         self,
@@ -1212,7 +1210,7 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
 
         nodes = indexing.retrieve_similar_nodes(a, top_k=5)
 
-        assert set(indexing._node_document_ids(nodes)) == {b.id}
+        assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}
 
     def test_excludes_self_with_multiple_chunks(
         self,
@@ -1235,4 +1233,4 @@ class TestRetrieveSimilarNodesAgainstRealIndex:
 
         nodes = indexing.retrieve_similar_nodes(a, top_k=3)
 
-        assert set(indexing._node_document_ids(nodes)) == {b.id}
+        assert {int(node.metadata["document_id"]) for node in nodes} == {b.id}

src/paperless_ai/tests/test_taxonomy.py

@@ -1,5 +1,4 @@
 import json
-from types import SimpleNamespace
 
 import pytest
 import pytest_mock
@@ -10,14 +9,14 @@ from documents.tests.factories import DocumentTypeFactory
 from documents.tests.factories import StoragePathFactory
 from documents.tests.factories import TagFactory
 from documents.tests.factories import UserFactory
+from paperless_ai.taxonomy import SimilarDocument
 from paperless_ai.taxonomy import TaxonomyCandidates
 from paperless_ai.taxonomy import build_taxonomy_candidates
 from paperless_ai.taxonomy import format_taxonomy_for_prompt
 
 
-def make_node(document_id: int, score: float) -> SimpleNamespace:
-    """A stand-in for NodeWithScore: only ``.metadata``/``.score`` are read."""
-    return SimpleNamespace(metadata={"document_id": str(document_id)}, score=score)
+def make_similar(document_id: int, weight: float) -> SimilarDocument:
+    return SimilarDocument(document_id=document_id, weight=weight)
 
 
 @pytest.mark.django_db
@@ -53,9 +52,9 @@ class TestBuildTaxonomyCandidates:
         doc_a.tags.add(tag)
         doc_b = DocumentFactory.create()
         doc_b.tags.add(tag)
-        nodes = [make_node(doc_a.pk, 0.9), make_node(doc_b.pk, 0.4)]
+        similar_documents = [make_similar(doc_a.pk, 0.9), make_similar(doc_b.pk, 0.4)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["tags"]) == 1
         assert result["tags"][0]["id"] == tag.pk
@@ -80,9 +79,9 @@ class TestBuildTaxonomyCandidates:
         document.tags.add(tag)
         tag.name = "New Name"
         tag.save()
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert result["tags"][0]["name"] == "New Name"
 
@@ -102,9 +101,9 @@ class TestBuildTaxonomyCandidates:
         document = DocumentFactory.create()
         document.tags.add(tag)
         tag.delete()
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert result["tags"] == []
 
@@ -123,9 +122,12 @@ class TestBuildTaxonomyCandidates:
         strong_doc.tags.add(strong_tag)
         weak_doc = DocumentFactory.create()
         weak_doc.tags.add(weak_tag)
-        nodes = [make_node(strong_doc.pk, 0.9), make_node(weak_doc.pk, 0.1)]
+        similar_documents = [
+            make_similar(strong_doc.pk, 0.9),
+            make_similar(weak_doc.pk, 0.1),
+        ]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert [c["name"] for c in result["tags"]] == ["Strong", "Weak"]
 
@@ -141,9 +143,9 @@ class TestBuildTaxonomyCandidates:
         document = DocumentFactory.create()
         for i in range(15):
             document.tags.add(TagFactory.create(name=f"Tag{i}"))
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["tags"]) == 10
 
@@ -157,12 +159,12 @@ class TestBuildTaxonomyCandidates:
             - Only 5 correspondents are returned
         """
         correspondents = CorrespondentFactory.create_batch(7)
-        nodes = [
-            make_node(DocumentFactory.create(correspondent=c).pk, 0.5)
+        similar_documents = [
+            make_similar(DocumentFactory.create(correspondent=c).pk, 0.5)
             for c in correspondents
         ]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["correspondents"]) == 5
 
@@ -177,9 +179,9 @@ class TestBuildTaxonomyCandidates:
         """
         document_type = DocumentTypeFactory.create(name="Invoice")
         document = DocumentFactory.create(document_type=document_type)
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["document_types"]) == 1
         assert result["document_types"][0]["id"] == document_type.pk
@@ -195,12 +197,12 @@ class TestBuildTaxonomyCandidates:
             - Only 5 document_types are returned
         """
         document_types = DocumentTypeFactory.create_batch(7)
-        nodes = [
-            make_node(DocumentFactory.create(document_type=dt).pk, 0.5)
+        similar_documents = [
+            make_similar(DocumentFactory.create(document_type=dt).pk, 0.5)
             for dt in document_types
         ]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["document_types"]) == 5
 
@@ -215,9 +217,9 @@ class TestBuildTaxonomyCandidates:
         """
         storage_path = StoragePathFactory.create(name="Invoices")
         document = DocumentFactory.create(storage_path=storage_path)
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["storage_paths"]) == 1
         assert result["storage_paths"][0]["id"] == storage_path.pk
@@ -233,12 +235,12 @@ class TestBuildTaxonomyCandidates:
             - Only 5 storage_paths are returned
         """
         storage_paths = StoragePathFactory.create_batch(7)
-        nodes = [
-            make_node(DocumentFactory.create(storage_path=sp).pk, 0.5)
+        similar_documents = [
+            make_similar(DocumentFactory.create(storage_path=sp).pk, 0.5)
             for sp in storage_paths
         ]
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert len(result["storage_paths"]) == 5
 
@@ -258,14 +260,14 @@ class TestBuildTaxonomyCandidates:
         tag = TagFactory.create(name="Restricted")
         document = DocumentFactory.create()
         document.tags.add(tag)
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
         user = UserFactory.create()
         mocker.patch(
             "documents.permissions.permitted_object_ids",
             return_value=[],  # user cannot see this tag
         )
 
-        result = build_taxonomy_candidates(nodes, user=user)
+        result = build_taxonomy_candidates(similar_documents, user=user)
 
         assert result["tags"] == []
 
@@ -295,10 +297,10 @@ class TestBuildTaxonomyCandidates:
         tag.save()
         document = DocumentFactory.create()
         document.tags.add(tag)
-        nodes = [make_node(document.pk, 0.5)]
+        similar_documents = [make_similar(document.pk, 0.5)]
         spy = mocker.patch("documents.permissions.permitted_object_ids")
 
-        result = build_taxonomy_candidates(nodes, user=None)
+        result = build_taxonomy_candidates(similar_documents, user=None)
 
         assert result["tags"][0]["name"] == "Owned"
         spy.assert_not_called()

src/paperless_mail/tasks.py

@@ -1,9 +1,7 @@
 import logging
 
-from celery import Task
 from celery import shared_task
 
-from documents.models import PaperlessTask
 from paperless_mail.mail import MailAccountHandler
 from paperless_mail.mail import MailError
 from paperless_mail.models import MailAccount
@@ -12,27 +10,8 @@ from paperless_mail.models import MailRule
 logger = logging.getLogger("paperless.mail.tasks")
 
 
-@shared_task(bind=True)
-def process_mail_accounts(self: Task, account_ids: list[int] | None = None) -> str:
-    # A scheduled check can still be running (or queued) when the next one
-    # fires, e.g. a large attachment batch that takes longer to process than
-    # the check interval. ProcessedMail dedup only records a message once its
-    # handling has finished, so an overlapping run can still pick up the same
-    # not-yet-recorded message. Skip outright rather than race it.
-    other_mail_fetch_running = (
-        PaperlessTask.objects.filter(
-            task_type=PaperlessTask.TaskType.MAIL_FETCH,
-            status__in=[PaperlessTask.Status.PENDING, PaperlessTask.Status.STARTED],
-        )
-        .exclude(task_id=self.request.id)
-        .exists()
-    )
-    if other_mail_fetch_running:
-        logger.info(
-            "Mail account processing is already running; skipping this run.",
-        )
-        return "Skipped: mail account processing already in progress."
-
+@shared_task
+def process_mail_accounts(account_ids: list[int] | None = None) -> str:
     total_new_documents = 0
     accounts = (
         MailAccount.objects.filter(pk__in=account_ids)

src/paperless_mail/tests/test_process_mail_accounts_overlap.py

@@ -1,89 +0,0 @@
-from unittest import mock
-
-import pytest
-
-from documents.models import PaperlessTask
-from paperless_mail import tasks
-from paperless_mail.tests.factories import MailAccountFactory
-from paperless_mail.tests.factories import MailRuleFactory
-
-
-@pytest.mark.django_db
-class TestProcessMailAccountsOverlap:
-    def test_skips_when_another_mail_fetch_task_is_running(self) -> None:
-        account = MailAccountFactory.create()
-        MailRuleFactory.create(account=account, enabled=True)
-
-        PaperlessTask.objects.create(
-            task_id="other-running-task",
-            task_type=PaperlessTask.TaskType.MAIL_FETCH,
-            trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
-            status=PaperlessTask.Status.STARTED,
-        )
-
-        with mock.patch.object(
-            tasks.MailAccountHandler,
-            "handle_mail_account",
-        ) as mocked_handle:
-            result = tasks.process_mail_accounts()
-
-        mocked_handle.assert_not_called()
-        assert result == "Skipped: mail account processing already in progress."
-
-    def test_runs_when_no_other_mail_fetch_task_is_running(self) -> None:
-        account = MailAccountFactory.create()
-        MailRuleFactory.create(account=account, enabled=True)
-
-        with mock.patch.object(
-            tasks.MailAccountHandler,
-            "handle_mail_account",
-            return_value=0,
-        ) as mocked_handle:
-            result = tasks.process_mail_accounts()
-
-        mocked_handle.assert_called_once()
-        assert result == "No new documents were added."
-
-    def test_ignores_completed_mail_fetch_tasks(self) -> None:
-        account = MailAccountFactory.create()
-        MailRuleFactory.create(account=account, enabled=True)
-
-        PaperlessTask.objects.create(
-            task_id="finished-task",
-            task_type=PaperlessTask.TaskType.MAIL_FETCH,
-            trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
-            status=PaperlessTask.Status.SUCCESS,
-        )
-
-        with mock.patch.object(
-            tasks.MailAccountHandler,
-            "handle_mail_account",
-            return_value=0,
-        ) as mocked_handle:
-            result = tasks.process_mail_accounts()
-
-        mocked_handle.assert_called_once()
-        assert result == "No new documents were added."
-
-    def test_does_not_skip_due_to_its_own_task_row(self) -> None:
-        account = MailAccountFactory.create()
-        MailRuleFactory.create(account=account, enabled=True)
-
-        PaperlessTask.objects.create(
-            task_id="self-task-id",
-            task_type=PaperlessTask.TaskType.MAIL_FETCH,
-            trigger_source=PaperlessTask.TriggerSource.SCHEDULED,
-            status=PaperlessTask.Status.STARTED,
-        )
-
-        with mock.patch.object(
-            tasks.MailAccountHandler,
-            "handle_mail_account",
-            return_value=0,
-        ) as mocked_handle:
-            result = tasks.process_mail_accounts.apply(
-                task_id="self-task-id",
-            ).result
-
-        mocked_handle.assert_called_once()
-        assert result == "No new documents were added."