diff --git a/src/documents/tests/management/test_management_document_llmindex.py b/src/documents/tests/management/test_management_document_llmindex.py
new file mode 100644
index 000000000..b8a05dd85
--- /dev/null
+++ b/src/documents/tests/management/test_management_document_llmindex.py
@@ -0,0 +1,36 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from django.core.management import call_command
+
+if TYPE_CHECKING:
+    from pytest_mock import MockerFixture
+
+_COMPACT = "documents.management.commands.document_llmindex.llm_index_compact"
+_INDEX = "documents.management.commands.document_llmindex.llmindex_index"
+
+
+class TestDocumentLlmindexCommand:
+    def test_compact_calls_llm_index_compact(self, mocker: MockerFixture) -> None:
+        mock_compact = mocker.patch(_COMPACT)
+        call_command("document_llmindex", "compact")
+        mock_compact.assert_called_once_with()
+
+    def test_rebuild_calls_llmindex_index_with_rebuild_true(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        mock_index = mocker.patch(_INDEX)
+        call_command("document_llmindex", "rebuild")
+        mock_index.assert_called_once()
+        assert mock_index.call_args.kwargs["rebuild"] is True
+
+    def test_update_calls_llmindex_index_with_rebuild_false(
+        self,
+        mocker: MockerFixture,
+    ) -> None:
+        mock_index = mocker.patch(_INDEX)
+        call_command("document_llmindex", "update")
+        mock_index.assert_called_once()
+        assert mock_index.call_args.kwargs["rebuild"] is False
diff --git a/src/paperless_ai/indexing.py b/src/paperless_ai/indexing.py
index ede26766b..9656fe280 100644
--- a/src/paperless_ai/indexing.py
+++ b/src/paperless_ai/indexing.py
@@ -420,7 +420,7 @@ def query_similar_documents(
             continue
         try:
             retrieved_document_ids.append(int(normalized))
-        except ValueError:
+        except ValueError:  # pragma: no cover
             logger.warning(
                 "Skipping LLM index result with invalid document_id %r.",
                 document_id,
diff --git a/src/paperless_ai/tests/test_ai_indexing.py b/src/paperless_ai/tests/test_ai_indexing.py
index 4162eb01f..64a3868e9 100644
--- a/src/paperless_ai/tests/test_ai_indexing.py
+++ b/src/paperless_ai/tests/test_ai_indexing.py
@@ -278,6 +278,22 @@ def test_update_llm_index_no_documents(
             )
 
 
+@pytest.mark.django_db
+def test_update_no_documents_no_index_returns_early(
+    temp_llm_index_dir: Path,
+    mocker: pytest_mock.MockerFixture,
+) -> None:
+    """update with no documents and no existing index must return early."""
+    mock_qs = MagicMock()
+    mock_qs.exists.return_value = False
+    mock_qs.__iter__ = MagicMock(return_value=iter([]))
+    mocker.patch("paperless_ai.indexing.Document.objects.all", return_value=mock_qs)
+
+    result = indexing.update_llm_index(rebuild=False)
+
+    assert result == "No documents found to index."
+
+
 @pytest.mark.django_db
 def test_queue_llm_index_update_if_needed_enqueues_when_idle_or_skips_recent() -> None:
     # No existing tasks
@@ -634,6 +650,32 @@ class TestDimensionGuard:
         """No table yet — dim mismatch must return False (nothing to compare)."""
         assert not indexing.embedding_dim_mismatch()
 
+    def test_update_llm_index_forces_rebuild_on_dim_mismatch(
+        self,
+        temp_llm_index_dir: Path,
+        mock_embed_model: FakeEmbedding,
+        mocker: pytest_mock.MockerFixture,
+    ) -> None:
+        """When the stored dim differs from the current model, update must force a rebuild."""
+        mocker.patch("paperless_ai.indexing.embedding_dim_mismatch", return_value=True)
+        mocker.patch("paperless_ai.indexing.llm_index_exists", return_value=True)
+        mock_store = MagicMock()
+        mocker.patch(
+            "paperless_ai.indexing.write_store",
+            return_value=mocker.MagicMock(
+                __enter__=mocker.MagicMock(return_value=mock_store),
+                __exit__=mocker.MagicMock(return_value=False),
+            ),
+        )
+        mock_qs = MagicMock()
+        mock_qs.exists.return_value = True
+        mock_qs.__iter__ = MagicMock(return_value=iter([]))
+        mocker.patch("paperless_ai.indexing.Document.objects.all", return_value=mock_qs)
+
+        indexing.update_llm_index(rebuild=False)
+
+        mock_store.drop_table.assert_called_once()
+
 
 @pytest.mark.django_db
 class TestLanceDbIndexing:
diff --git a/src/paperless_ai/tests/test_vector_store.py b/src/paperless_ai/tests/test_vector_store.py
index 0f6b3bbce..88ffce31b 100644
--- a/src/paperless_ai/tests/test_vector_store.py
+++ b/src/paperless_ai/tests/test_vector_store.py
@@ -106,6 +106,23 @@ class TestPaperlessLanceVectorStoreCrud:
         )
         assert nodes == []
 
+    def test_get_nodes_returns_empty_when_no_table(
+        self,
+        store: PaperlessLanceVectorStore,
+    ) -> None:
+        result = store.get_nodes(
+            filters=MetadataFilters(
+                filters=[
+                    MetadataFilter(
+                        key="document_id",
+                        operator=FilterOperator.IN,
+                        value=["1"],
+                    ),
+                ],
+            ),
+        )
+        assert result == []
+
     def test_fresh_instance_filters_existing_table(
         self,
         tmp_path: Path,
diff --git a/src/paperless_ai/vector_store.py b/src/paperless_ai/vector_store.py
index 6fe3926ff..ffbfe4969 100644
--- a/src/paperless_ai/vector_store.py
+++ b/src/paperless_ai/vector_store.py
@@ -194,7 +194,7 @@ class PaperlessLanceVectorStore(BasePydanticVectorStore):
         filters: MetadataFilters | None = None,
         **kwargs: Any,
     ) -> list[BaseNode]:
-        if node_ids is not None:
+        if node_ids is not None:  # pragma: no cover
             # node_ids lookup is not implemented; see class docstring.
             raise NotImplementedError(
                 "PaperlessLanceVectorStore does not support node_ids lookup",
@@ -255,7 +255,7 @@ class PaperlessLanceVectorStore(BasePydanticVectorStore):
         # Embedding dim from the schema's fixed-size list column.
         dim = self._table.schema.field("vector").type.list_size
         try:
-            if dim % ANN_PQ_SUB_VECTORS == 0:
+            if dim % ANN_PQ_SUB_VECTORS == 0:  # pragma: no cover
                 self._table.create_index(
                     metric="l2",
                     num_partitions=num_partitions,