diff --git a/src/paperless_ai/indexing.py b/src/paperless_ai/indexing.py
index 8c802433e..31b7b7c5c 100644
--- a/src/paperless_ai/indexing.py
+++ b/src/paperless_ai/indexing.py
@@ -1,6 +1,7 @@
 import json
 import logging
 from collections.abc import Iterable
+from contextlib import contextmanager
 from datetime import timedelta
 from typing import TYPE_CHECKING
 
@@ -71,6 +72,18 @@ def get_vector_store() -> "PaperlessLanceVectorStore":
     )
 
 
+@contextmanager
+def write_store():
+    """Acquire the write lock and yield the vector store.
+
+    All mutating operations (upsert, delete, rebuild, compact) must go through
+    this context manager to serialise concurrent Celery writers.
+    Read paths use ``get_vector_store()`` directly — no lock needed.
+    """
+    with FileLock(settings.LLM_INDEX_LOCK):
+        yield get_vector_store()
+
+
 def build_document_node(
     document: Document,
     *,
@@ -232,11 +245,10 @@ def update_llm_index(
     chunk_size = AIConfig().llm_embedding_chunk_size
     embed_model = get_embedding_model()
 
-    with FileLock(settings.LLM_INDEX_LOCK):
+    with write_store() as store:
         if rebuild or not llm_index_exists():
             (settings.LLM_INDEX_DIR / "meta.json").unlink(missing_ok=True)
             logger.info("Rebuilding LLM index.")
-            store = get_vector_store()
             store.drop_table()
             for document in iter_wrapper(documents):
                 nodes = build_document_node(document, chunk_size=chunk_size)
@@ -250,7 +262,6 @@ def update_llm_index(
                 store.add(nodes)
             msg = "LLM index rebuilt successfully."
         else:
-            store = get_vector_store()
             existing = _stored_modified_times(store)
             changed = 0
             for document in iter_wrapper(documents):
@@ -294,16 +305,14 @@ def llm_index_add_or_update_document(document: Document):
         ):
             node.embedding = emb
 
-    with FileLock(settings.LLM_INDEX_LOCK):
-        store = get_vector_store()
+    with write_store() as store:
         store.upsert_document(str(document.id), new_nodes)
         store.ensure_document_id_scalar_index()
 
 
 def llm_index_remove_document(document: Document):
     """Remove a document's chunks from the LLM index."""
-    with FileLock(settings.LLM_INDEX_LOCK):
-        store = get_vector_store()
+    with write_store() as store:
         store.delete(str(document.id))