fix(vector-sync): sweep placeholder orphans at Pod startup (#101)

When the per-tenant nextcloud-mcp-server Pod OOMKills mid-batch, the
in-memory anyio processor queue is lost but the placeholder Qdrant
points (is_placeholder=true, status=pending) survive. The next Pod's
scanner re-runs, sees the existing placeholders, applies the
5 × VECTOR_SYNC_SCAN_INTERVAL staleness gate (~5h with the deployed
1h scan interval), and skips them. Result: 0 documents indexed for
the duration of the gate after every restart.

Stamps a process-level instance_id (UUID per Pod-process) onto every
placeholder write. A new sweep_orphan_placeholders helper, called
once from starlette_lifespan after the Qdrant client is initialised
and before the scanner / user-manager spawns, scrolls the collection
and deletes any placeholder whose instance_id doesn't match the
current Pod's (including placeholders with no instance_id field —
back-compat for pre-fix Pod versions). The scanner's next cycle
naturally re-creates fresh placeholders and queues work normally;
no DocumentTask reconstruction needed.

Sweep is one-shot at startup, not periodic — the existing staleness
gate still covers same-Pod recovery, and the cross-Pod-restart gap
was the only failure mode. Failure is non-fatal (logged via
vector_sync.orphan_sweep_failed) so a transient Qdrant hiccup at
boot doesn't prevent the scanner from running.

Both lifespan branches (single-user BasicAuth, OAuth / multi-user
BasicAuth) call the sweep via a module-local helper. A new
VECTOR_SYNC_ORPHAN_SWEEP_ENABLED setting (default True) provides
an escape hatch.

Closes Deck #101.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/app.py

@@ -129,6 +129,7 @@ from nextcloud_mcp_server.vector.oauth_sync import (
     oauth_processor_task,
     user_manager_task,
 )
+from nextcloud_mcp_server.vector.placeholder import sweep_orphan_placeholders
 from nextcloud_mcp_server.vector.processor import processor_task
 from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client
 from nextcloud_mcp_server.vector.scanner import scanner_task
@@ -1437,6 +1438,34 @@ def get_app(transport: str = "streamable-http", enabled_apps: list[str] | None =
             await stack.enter_async_context(_maybe_login_flow_cleanup(app))
             yield
 
+    async def _sweep_orphan_placeholders_if_enabled() -> None:
+        """One-shot Pod-startup sweep of cross-restart placeholder orphans.
+
+        See ``vector.placeholder.sweep_orphan_placeholders`` and Deck
+        card #101. Both lifespan branches (single-user BasicAuth and
+        OAuth / multi-user BasicAuth) call this after the qdrant
+        client is initialised and before the scanner / user-manager
+        tasks spawn. Failures are non-fatal — the existing staleness
+        gate will eventually re-queue orphans on the slow ~5h path.
+        """
+        if not settings.vector_sync_orphan_sweep_enabled:
+            return
+        try:
+            qdrant_client = await get_qdrant_client()
+            swept, kept = await sweep_orphan_placeholders(
+                qdrant_client, settings.qdrant_collection
+            )
+            logger.info(
+                "vector_sync.orphan_sweep",
+                extra={
+                    "swept": swept,
+                    "kept": kept,
+                    "collection": settings.qdrant_collection,
+                },
+            )
+        except Exception:
+            logger.exception("vector_sync.orphan_sweep_failed")
+
     @asynccontextmanager
     async def starlette_lifespan(app: Starlette):
         # Set OAuth context for OAuth login routes (ADR-004)
@@ -1612,6 +1641,9 @@ def get_app(transport: str = "streamable-http", enabled_apps: list[str] | None =
                     f"Cannot start vector sync - Qdrant initialization failed: {e}"
                 ) from e
 
+            # Orphan-sweep before scanner starts — card #101.
+            await _sweep_orphan_placeholders_if_enabled()
+
             # Initialize shared state
             send_stream, receive_stream = anyio.create_memory_object_stream(
                 max_buffer_size=settings.vector_sync_queue_max_size
@@ -1774,6 +1806,11 @@ def get_app(transport: str = "streamable-http", enabled_apps: list[str] | None =
                         f"Cannot start vector sync - Qdrant initialization failed: {e}"
                     ) from e
 
+                # Orphan-sweep before scanners spawn — card #101. Runs once
+                # across the shared (per-tenant) collection regardless of
+                # how many per-user scanners the user-manager later starts.
+                await _sweep_orphan_placeholders_if_enabled()
+
                 # Clean up stale app passwords at startup (BasicAuth mode only)
                 if not oauth_enabled:
                     try:

nextcloud_mcp_server/config.py

@@ -87,6 +87,12 @@ _DEFAULTS: dict[str, Any] = {
     "vector_sync_processor_workers": 3,
     "vector_sync_queue_max_size": 10000,
     "vector_sync_user_poll_interval": 60,
+    # Orphan-sweep at Pod startup (card #101). When True, delete any
+    # placeholders carrying a different / absent ``instance_id`` before
+    # the scanner's first cycle, so a Pod restart mid-batch doesn't
+    # leave work stuck behind the 5x-scan-interval staleness gate.
+    # Escape hatch only — leave on by default.
+    "vector_sync_orphan_sweep_enabled": True,
     # Verify-on-read concurrency cap (ADR-019)
     "verification_concurrency": 20,
     # Qdrant
@@ -585,6 +591,7 @@ class Settings:
     vector_sync_processor_workers: int = 3
     vector_sync_queue_max_size: int = 10000
     vector_sync_user_poll_interval: int = 60  # seconds - OAuth mode user discovery
+    vector_sync_orphan_sweep_enabled: bool = True  # card #101
 
     # Verify-on-read concurrency (ADR-019). Cap on parallel Nextcloud
     # round-trips during search-result verification fan-out. Lower this if the
@@ -1076,6 +1083,7 @@ def get_settings() -> Settings:
         "vector_sync_processor_workers": "VECTOR_SYNC_PROCESSOR_WORKERS",
         "vector_sync_queue_max_size": "VECTOR_SYNC_QUEUE_MAX_SIZE",
         "vector_sync_user_poll_interval": "VECTOR_SYNC_USER_POLL_INTERVAL",
+        "vector_sync_orphan_sweep_enabled": "VECTOR_SYNC_ORPHAN_SWEEP_ENABLED",
         # Verify-on-read (ADR-019)
         "verification_concurrency": "VERIFICATION_CONCURRENCY",
         # Qdrant settings

nextcloud_mcp_server/vector/placeholder.py

@@ -30,6 +30,13 @@ from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client
 
 logger = logging.getLogger(__name__)
 
+# Stamped on every placeholder this Pod-process writes. A fresh UUID per
+# process means a restarted Pod sees its predecessor's placeholders as
+# "not mine" and deletes them in ``sweep_orphan_placeholders`` at startup,
+# instead of waiting out the ``5 × VECTOR_SYNC_SCAN_INTERVAL`` staleness
+# gate (~5h with the deployed 1h scan interval). Card #101.
+_INSTANCE_ID = str(uuid.uuid4())
+
 
 def _generate_placeholder_id(doc_type: str, doc_id: str) -> str:
     """Generate deterministic UUID for placeholder point.
@@ -98,6 +105,10 @@ async def write_placeholder_point(
             "modified_at": modified_at,
             "etag": etag,
             "queued_at": int(time.time()),
+            # Pod-process identity. ``sweep_orphan_placeholders`` uses
+            # the (placeholder.instance_id != _INSTANCE_ID) predicate to
+            # detect orphans from a crashed predecessor Pod.
+            "instance_id": _INSTANCE_ID,
         }
 
         # Add file_path for files
@@ -319,3 +330,88 @@ def get_placeholder_filter() -> FieldCondition:
         key="is_placeholder",
         match=MatchValue(value=False),
     )
+
+
+# Batch size for the orphan-sweep scroll + delete loop. Big enough to
+# keep round-trip count down, small enough that a single delete payload
+# isn't unreasonable. Matches the order of magnitude of a per-tenant
+# placeholder count (108 in the originating incident).
+_ORPHAN_SWEEP_BATCH_SIZE = 100
+
+
+async def sweep_orphan_placeholders(
+    qdrant_client,
+    collection_name: str,
+    *,
+    batch_size: int = _ORPHAN_SWEEP_BATCH_SIZE,
+) -> tuple[int, int]:
+    """Delete placeholder points written by a previous Pod-process.
+
+    Scrolls all ``is_placeholder=true`` points in the collection,
+    paginated. For each batch, partitions points by whether their
+    ``instance_id`` payload field matches the current Pod's
+    ``_INSTANCE_ID``. Orphans (different ``instance_id`` OR field
+    absent — back-compat for placeholders written by pre-fix Pod
+    versions) are deleted by point ID; own-Pod placeholders are
+    left alone for the scanner's staleness gate to handle normally.
+
+    Called once at Pod startup from ``app.starlette_lifespan`` —
+    NOT periodically. The own-Pod path relies on the existing
+    ``5 × VECTOR_SYNC_SCAN_INTERVAL`` gate; this helper only
+    addresses the cross-Pod-restart gap. Card #101.
+
+    Args:
+        qdrant_client: Async Qdrant client.
+        collection_name: Target collection.
+        batch_size: Scroll page size. Default 100 — small enough that
+            a single delete payload is reasonable, large enough that
+            round-trip count stays bounded for typical placeholder
+            counts (~hundreds per tenant).
+
+    Returns:
+        ``(swept, kept)`` — number of placeholders deleted as orphans,
+        and number left in place as belonging to the current Pod.
+    """
+    placeholder_filter = Filter(
+        must=[
+            FieldCondition(key="is_placeholder", match=MatchValue(value=True)),
+        ]
+    )
+    swept = 0
+    kept = 0
+    offset = None
+
+    while True:
+        points, offset = await qdrant_client.scroll(
+            collection_name=collection_name,
+            scroll_filter=placeholder_filter,
+            limit=batch_size,
+            offset=offset,
+            with_payload=True,
+            with_vectors=False,
+        )
+        if not points:
+            break
+
+        orphan_ids = []
+        for point in points:
+            payload = point.payload or {}
+            point_instance = payload.get("instance_id")
+            if point_instance == _INSTANCE_ID:
+                kept += 1
+            else:
+                orphan_ids.append(point.id)
+
+        if orphan_ids:
+            await qdrant_client.delete(
+                collection_name=collection_name,
+                points_selector=orphan_ids,
+            )
+            swept += len(orphan_ids)
+
+        # ``offset is None`` signals the scroll cursor has been
+        # exhausted — Qdrant's contract for paginated scroll.
+        if offset is None:
+            break
+
+    return swept, kept