Nextcloud MCP Server

"""Scanner task for vector database synchronization. Periodically scans enabled users' content and queues changed documents for processing. """ import logging import os import time from dataclasses import dataclass import anyio from anyio.abc import TaskStatus from anyio.streams.memory import MemoryObjectSendStream from qdrant_client.models import FieldCondition, Filter, MatchValue from nextcloud_mcp_server.client import NextcloudClient from nextcloud_mcp_server.config import get_settings from nextcloud_mcp_server.observability.metrics import record_vector_sync_scan from nextcloud_mcp_server.observability.tracing import trace_operation from nextcloud_mcp_server.vector.placeholder import ( query_document_metadata, write_placeholder_point, ) from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client logger = logging.getLogger(__name__) @dataclass class DocumentTask: """Document task for processing queue.""" user_id: str doc_id: int | str # int for files/notes, str for legacy doc_type: str # "note", "file", "calendar" operation: str # "index" or "delete" modified_at: int file_path: str | None = None # File path for files (when doc_id is file_id) metadata: dict[str, int | str] | None = ( None # Additional metadata (e.g., board_id/stack_id for deck_card) ) # Track documents potentially deleted (grace period before actual deletion) # Format: {(user_id, doc_id): first_missing_timestamp} _potentially_deleted: dict[tuple[str, str], float] = {} async def get_last_indexed_timestamp(user_id: str) -> int | None: """Get the most recent indexed_at timestamp for user's notes in Qdrant. This timestamp can be used as pruneBefore parameter to optimize data transfer when fetching notes - only notes modified after this timestamp will be sent with full data. Args: user_id: User to query Returns: Unix timestamp of most recently indexed note, or None if no notes indexed yet """ try: qdrant_client = await get_qdrant_client() # Query for user's notes, ordered by indexed_at descending, limit 1 scroll_result = await qdrant_client.scroll( collection_name=get_settings().get_collection_name(), scroll_filter=Filter( must=[ FieldCondition(key="user_id", match=MatchValue(value=user_id)), FieldCondition(key="doc_type", match=MatchValue(value="note")), ] ), with_payload=["indexed_at"], with_vectors=False, limit=10000, # Get all to find max ) # Find max indexed_at across all results num_points = len(scroll_result[0]) if scroll_result[0] else 0 logger.info(f"Found {num_points} indexed notes in Qdrant for user {user_id}") if scroll_result[0]: timestamps = [ point.payload.get("indexed_at", 0) for point in scroll_result[0] if point.payload is not None ] max_timestamp = max(timestamps) if timestamps else 0 logger.info( f"Max indexed_at: {max_timestamp}, timestamps sample: {timestamps[:3]}" ) return int(max_timestamp) if max_timestamp > 0 else None logger.info(f"No indexed notes found for user {user_id}") return None except Exception as e: logger.warning(f"Failed to get last indexed timestamp: {e}", exc_info=True) return None async def scanner_task( send_stream: MemoryObjectSendStream[DocumentTask], shutdown_event: anyio.Event, wake_event: anyio.Event, nc_client: NextcloudClient, user_id: str, *, task_status: TaskStatus = anyio.TASK_STATUS_IGNORED, ): """ Periodic scanner that detects changed documents for enabled user. For BasicAuth mode, scans a single user with credentials available at runtime. Args: send_stream: Stream to send changed documents to processors shutdown_event: Event signaling shutdown wake_event: Event to trigger immediate scan nc_client: Authenticated Nextcloud client user_id: User to scan task_status: Status object for signaling task readiness """ logger.info(f"Scanner task started for user: {user_id}") settings = get_settings() # Signal that the task has started and is ready task_status.started() async with send_stream: while not shutdown_event.is_set(): try: # Scan user documents await scan_user_documents( user_id=user_id, send_stream=send_stream, nc_client=nc_client, ) except Exception as e: logger.error(f"Scanner error: {e}", exc_info=True) # Sleep until next interval or wake event try: with anyio.move_on_after(settings.vector_sync_scan_interval): # Wait for wake event or shutdown (whichever comes first) await wake_event.wait() except anyio.get_cancelled_exc_class(): # Shutdown, exit loop break logger.info("Scanner task stopped - stream closed") async def scan_user_documents( user_id: str, send_stream: MemoryObjectSendStream[DocumentTask], nc_client: NextcloudClient, initial_sync: bool = False, ): """ Scan a single user's documents and send changes to processor stream. Args: user_id: User to scan send_stream: Stream to send changed documents to processors nc_client: Authenticated Nextcloud client initial_sync: If True, send all documents (first-time sync) """ import random scan_id = random.randint(1000, 9999) logger.info( f"[SCAN-{scan_id}] Starting scan for user: {user_id}, initial_sync={initial_sync}" ) with trace_operation( "vector_sync.scan_user_documents", attributes={ "vector_sync.operation": "scan", "vector_sync.user_id": user_id, "vector_sync.initial_sync": initial_sync, "vector_sync.scan_id": scan_id, }, ): # Calculate prune timestamp for optimized data transfer # Only notes modified after this will be sent with full data prune_before = ( None if initial_sync else await get_last_indexed_timestamp(user_id) ) if prune_before: logger.info( f"[SCAN-{scan_id}] Using pruneBefore={prune_before} to optimize data transfer" ) # For deletion tracking, get all doc_ids in Qdrant (for incremental sync) # Note: We no longer bulk-query indexed_at, instead check per-document indexed_doc_ids = set() if not initial_sync: qdrant_client = await get_qdrant_client() scroll_result = await qdrant_client.scroll( collection_name=get_settings().get_collection_name(), scroll_filter=Filter( must=[ FieldCondition(key="user_id", match=MatchValue(value=user_id)), FieldCondition(key="doc_type", match=MatchValue(value="note")), ] ), with_payload=["doc_id"], with_vectors=False, limit=10000, ) indexed_doc_ids = { point.payload["doc_id"] for point in (scroll_result[0] or []) if point.payload is not None } logger.debug(f"Found {len(indexed_doc_ids)} indexed documents in Qdrant") # Stream notes from Nextcloud and process immediately note_count = 0 queued = 0 nextcloud_doc_ids = set() async for note in nc_client.notes.get_all_notes(prune_before=prune_before): note_count += 1 doc_id = str(note["id"]) nextcloud_doc_ids.add(doc_id) modified_at = note.get("modified", 0) if initial_sync: # Send everything on first sync - write placeholder first await write_placeholder_point( doc_id=doc_id, doc_type="note", user_id=user_id, modified_at=modified_at, etag=note.get("etag", ""), ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="note", operation="index", modified_at=modified_at, ) ) queued += 1 else: # Incremental sync: check if document exists and compare modified_at # If document reappeared, remove from potentially_deleted doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: logger.debug( f"Document {doc_id} reappeared, removing from deletion grace period" ) del _potentially_deleted[doc_key] # Query Qdrant for existing entry (placeholder or real) existing_metadata = await query_document_metadata( doc_id=doc_id, doc_type="note", user_id=user_id ) # Send if never indexed or modified since last index # Compare against stored modified_at (not indexed_at!) needs_indexing = False if existing_metadata is None: # Never seen before needs_indexing = True elif existing_metadata.get("modified_at", 0) < modified_at: # Document modified since last indexing needs_indexing = True elif existing_metadata.get("is_placeholder", False): # Placeholder exists - check if it's stale (processing may have failed) # Only requeue if placeholder is older than 5x scan interval # (Large PDFs can take 3-4 minutes to process) queued_at = existing_metadata.get("queued_at", 0) placeholder_age = time.time() - queued_at stale_threshold = get_settings().vector_sync_scan_interval * 5 if placeholder_age > stale_threshold: logger.debug( f"Found stale placeholder for note {doc_id} " f"(age={placeholder_age:.1f}s), requeuing" ) needs_indexing = True else: logger.debug( f"Skipping note {doc_id} with recent placeholder " f"(age={placeholder_age:.1f}s < {stale_threshold:.1f}s)" ) if needs_indexing: # Write placeholder before queuing await write_placeholder_point( doc_id=doc_id, doc_type="note", user_id=user_id, modified_at=modified_at, etag=note.get("etag", ""), ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="note", operation="index", modified_at=modified_at, ) ) queued += 1 # Log and record metrics after streaming logger.info(f"[SCAN-{scan_id}] Found {note_count} notes for {user_id}") record_vector_sync_scan(note_count) if initial_sync: logger.info(f"Sent {queued} documents for initial sync: {user_id}") return # Check for deleted documents (in Qdrant but not in Nextcloud) # Use grace period: only delete after 2 consecutive scans confirm absence settings = get_settings() grace_period = ( settings.vector_sync_scan_interval * 1.5 ) # Allow 1.5 scan intervals current_time = time.time() for doc_id in indexed_doc_ids: if doc_id not in nextcloud_doc_ids: doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: # Already marked as potentially deleted, check if grace period elapsed first_missing_time = _potentially_deleted[doc_key] time_missing = current_time - first_missing_time if time_missing >= grace_period: # Grace period elapsed, send for deletion logger.info( f"Document {doc_id} missing for {time_missing:.1f}s " f"(>{grace_period:.1f}s grace period), sending deletion" ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="note", operation="delete", modified_at=0, ) ) queued += 1 # Remove from tracking after sending deletion del _potentially_deleted[doc_key] else: logger.debug( f"Document {doc_id} still missing " f"({time_missing:.1f}s/{grace_period:.1f}s grace period)" ) else: # First time missing, add to grace period tracking logger.debug( f"Document {doc_id} missing for first time, starting grace period" ) _potentially_deleted[doc_key] = current_time # Scan tagged PDF files (after notes) # Get indexed file IDs from Qdrant (for deletion tracking) indexed_file_ids = set() if not initial_sync: file_scroll_result = await qdrant_client.scroll( collection_name=settings.get_collection_name(), scroll_filter=Filter( must=[ FieldCondition(key="user_id", match=MatchValue(value=user_id)), FieldCondition(key="doc_type", match=MatchValue(value="file")), ] ), limit=10000, # Reasonable limit for file count with_payload=["doc_id"], with_vectors=False, ) indexed_file_ids = { point.payload["doc_id"] for point in (file_scroll_result[0] or []) if point.payload is not None } logger.debug(f"Found {len(indexed_file_ids)} indexed files in Qdrant") # Scan for tagged PDF files file_count = 0 file_queued = 0 nextcloud_file_ids = set() try: # Find files with vector-index tag using OCS Tags API settings = get_settings() tag_name = os.getenv("VECTOR_SYNC_PDF_TAG", "vector-index") # Use NextcloudClient.find_files_by_tag() which uses proper OCS API # and filters by PDF MIME type tagged_files = await nc_client.find_files_by_tag( tag_name, mime_type_filter="application/pdf" ) for file_info in tagged_files: # Files are already filtered by MIME type in find_files_by_tag() file_count += 1 file_id = file_info["id"] # Use numeric file ID, not path file_path = file_info["path"] # Keep path for logging nextcloud_file_ids.add(file_id) # Use last_modified timestamp if available, otherwise use current time modified_at = file_info.get("last_modified_timestamp", int(time.time())) if isinstance(file_info.get("last_modified"), str): # Parse RFC 2822 date format if needed from email.utils import parsedate_to_datetime try: dt = parsedate_to_datetime(file_info["last_modified"]) modified_at = int(dt.timestamp()) except (ValueError, KeyError): pass if initial_sync: # Send everything on first sync - write placeholder first await write_placeholder_point( doc_id=file_id, doc_type="file", user_id=user_id, modified_at=modified_at, file_path=file_path, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=file_id, # Use numeric file ID doc_type="file", operation="index", modified_at=modified_at, file_path=file_path, # Pass file path for content retrieval ) ) file_queued += 1 else: # Incremental sync: check if file exists and compare modified_at # If file reappeared, remove from potentially_deleted file_key = (user_id, file_id) if file_key in _potentially_deleted: logger.debug( f"File {file_path} (ID: {file_id}) reappeared, removing from deletion grace period" ) del _potentially_deleted[file_key] # Query Qdrant for existing entry (placeholder or real) existing_metadata = await query_document_metadata( doc_id=file_id, doc_type="file", user_id=user_id ) # Send if never indexed or modified since last index # Compare against stored modified_at (not indexed_at!) needs_indexing = False if existing_metadata is None: # Never seen before needs_indexing = True elif existing_metadata.get("modified_at", 0) < modified_at: # File modified since last indexing needs_indexing = True elif existing_metadata.get("is_placeholder", False): # Placeholder exists - check if it's stale (processing may have failed) # Only requeue if placeholder is older than 5x scan interval # (Large PDFs can take 3-4 minutes to process) queued_at = existing_metadata.get("queued_at", 0) placeholder_age = time.time() - queued_at stale_threshold = get_settings().vector_sync_scan_interval * 5 if placeholder_age > stale_threshold: logger.debug( f"Found stale placeholder for file {file_path} (ID: {file_id}) " f"(age={placeholder_age:.1f}s), requeuing" ) needs_indexing = True else: logger.debug( f"Skipping file {file_path} (ID: {file_id}) with recent placeholder " f"(age={placeholder_age:.1f}s < {stale_threshold:.1f}s)" ) if needs_indexing: # Write placeholder before queuing await write_placeholder_point( doc_id=file_id, doc_type="file", user_id=user_id, modified_at=modified_at, file_path=file_path, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=file_id, # Use numeric file ID doc_type="file", operation="index", modified_at=modified_at, file_path=file_path, # Pass file path for content retrieval ) ) file_queued += 1 logger.info( f"[SCAN-{scan_id}] Found {file_count} tagged PDFs for {user_id}" ) record_vector_sync_scan(file_count) # Check for deleted files (not initial sync) if not initial_sync: for file_id in indexed_file_ids: if file_id not in nextcloud_file_ids: file_key = (user_id, file_id) if file_key in _potentially_deleted: # Check if grace period elapsed first_missing_time = _potentially_deleted[file_key] time_missing = current_time - first_missing_time if time_missing >= grace_period: # Grace period elapsed, send for deletion logger.info( f"File ID {file_id} missing for {time_missing:.1f}s " f"(>{grace_period:.1f}s grace period), sending deletion" ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=file_id, # Use numeric file ID doc_type="file", operation="delete", modified_at=0, ) ) file_queued += 1 del _potentially_deleted[file_key] else: # First time missing, add to grace period tracking logger.debug( f"File ID {file_id} missing for first time, starting grace period" ) _potentially_deleted[file_key] = current_time except Exception as e: logger.warning(f"Failed to scan tagged files for {user_id}: {e}") queued += file_queued # Scan News items (starred + unread) news_queued = 0 try: news_queued = await scan_news_items( user_id=user_id, send_stream=send_stream, nc_client=nc_client, initial_sync=initial_sync, scan_id=scan_id, ) queued += news_queued except Exception as e: logger.warning(f"Failed to scan news items for {user_id}: {e}") # Scan Deck cards deck_queued = 0 try: deck_queued = await scan_deck_cards( user_id=user_id, send_stream=send_stream, nc_client=nc_client, initial_sync=initial_sync, scan_id=scan_id, ) queued += deck_queued except Exception as e: logger.warning(f"Failed to scan deck cards for {user_id}: {e}") if queued > 0: logger.info( f"Sent {queued} documents ({file_queued} files, {news_queued} news items, {deck_queued} deck cards) for incremental sync: {user_id}" ) else: logger.debug(f"No changes detected for {user_id}") async def scan_news_items( user_id: str, send_stream: MemoryObjectSendStream[DocumentTask], nc_client: NextcloudClient, initial_sync: bool, scan_id: int, ) -> int: """ Scan user's News items and queue changed items for indexing. Indexes all items from the user's feeds. The News app's auto-purge feature (default: 200 items per feed) naturally limits the total number of items, making explicit filtering unnecessary. Args: user_id: User to scan send_stream: Stream to send changed documents to processors nc_client: Authenticated Nextcloud client initial_sync: If True, send all documents (first-time sync) scan_id: Scan identifier for logging Returns: Number of items queued for processing """ from nextcloud_mcp_server.client.news import NewsItemType settings = get_settings() queued = 0 # Get indexed news item IDs from Qdrant (for deletion tracking) indexed_item_ids: set[str] = set() if not initial_sync: qdrant_client = await get_qdrant_client() scroll_result = await qdrant_client.scroll( collection_name=settings.get_collection_name(), scroll_filter=Filter( must=[ FieldCondition(key="user_id", match=MatchValue(value=user_id)), FieldCondition(key="doc_type", match=MatchValue(value="news_item")), ] ), with_payload=["doc_id"], with_vectors=False, limit=10000, ) indexed_item_ids = { point.payload["doc_id"] for point in (scroll_result[0] or []) if point.payload is not None } logger.debug(f"Found {len(indexed_item_ids)} indexed news items in Qdrant") # Fetch all items (News app caps at ~200 per feed via auto-purge) all_items = await nc_client.news.get_items( batch_size=-1, type_=NewsItemType.ALL, get_read=True, ) logger.debug(f"[SCAN-{scan_id}] Found {len(all_items)} news items") item_count = len(all_items) nextcloud_item_ids: set[str] = set() for item in all_items: doc_id = str(item["id"]) nextcloud_item_ids.add(doc_id) # Use lastModified timestamp (microseconds in News API) modified_at = item.get("lastModified", 0) # Convert to seconds if needed (News API uses microseconds) if modified_at > 10000000000: # > year 2286 in seconds modified_at = modified_at // 1000000 if initial_sync: # Send everything on first sync - write placeholder first await write_placeholder_point( doc_id=doc_id, doc_type="news_item", user_id=user_id, modified_at=modified_at, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="news_item", operation="index", modified_at=modified_at, ) ) queued += 1 else: # Incremental sync: check if item exists and compare modified_at doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: logger.debug( f"News item {doc_id} reappeared, removing from deletion grace period" ) del _potentially_deleted[doc_key] # Query Qdrant for existing entry existing_metadata = await query_document_metadata( doc_id=doc_id, doc_type="news_item", user_id=user_id ) needs_indexing = False if existing_metadata is None: needs_indexing = True elif existing_metadata.get("modified_at", 0) < modified_at: needs_indexing = True elif existing_metadata.get("is_placeholder", False): queued_at = existing_metadata.get("queued_at", 0) placeholder_age = time.time() - queued_at stale_threshold = settings.vector_sync_scan_interval * 5 if placeholder_age > stale_threshold: logger.debug( f"Found stale placeholder for news item {doc_id} " f"(age={placeholder_age:.1f}s), requeuing" ) needs_indexing = True if needs_indexing: await write_placeholder_point( doc_id=doc_id, doc_type="news_item", user_id=user_id, modified_at=modified_at, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="news_item", operation="index", modified_at=modified_at, ) ) queued += 1 logger.info( f"[SCAN-{scan_id}] Found {item_count} news items (starred+unread) for {user_id}" ) record_vector_sync_scan(item_count) # Check for deleted items (not initial sync) # Items become "deleted" when they are no longer starred AND become read if not initial_sync: grace_period = settings.vector_sync_scan_interval * 1.5 current_time = time.time() for doc_id in indexed_item_ids: if doc_id not in nextcloud_item_ids: doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: first_missing_time = _potentially_deleted[doc_key] time_missing = current_time - first_missing_time if time_missing >= grace_period: logger.info( f"News item {doc_id} missing for {time_missing:.1f}s " f"(>{grace_period:.1f}s grace period), sending deletion" ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="news_item", operation="delete", modified_at=0, ) ) queued += 1 del _potentially_deleted[doc_key] else: logger.debug( f"News item {doc_id} missing for first time, starting grace period" ) _potentially_deleted[doc_key] = current_time return queued async def scan_deck_cards( user_id: str, send_stream: MemoryObjectSendStream[DocumentTask], nc_client: NextcloudClient, initial_sync: bool, scan_id: int, ) -> int: """ Scan user's Deck cards and queue changed cards for indexing. Indexes cards from all non-archived boards and stacks. Args: user_id: User to scan send_stream: Stream to send changed documents to processors nc_client: Authenticated Nextcloud client initial_sync: If True, send all documents (first-time sync) scan_id: Scan identifier for logging Returns: Number of cards queued for processing """ settings = get_settings() queued = 0 # Get indexed deck card IDs from Qdrant (for deletion tracking) indexed_card_ids: set[str] = set() if not initial_sync: qdrant_client = await get_qdrant_client() scroll_result = await qdrant_client.scroll( collection_name=settings.get_collection_name(), scroll_filter=Filter( must=[ FieldCondition(key="user_id", match=MatchValue(value=user_id)), FieldCondition(key="doc_type", match=MatchValue(value="deck_card")), ] ), with_payload=["doc_id"], with_vectors=False, limit=10000, ) indexed_card_ids = { point.payload["doc_id"] for point in (scroll_result[0] or []) if point.payload is not None } logger.debug(f"Found {len(indexed_card_ids)} indexed deck cards in Qdrant") # Fetch all boards boards = await nc_client.deck.get_boards() logger.debug(f"[SCAN-{scan_id}] Found {len(boards)} deck boards") card_count = 0 nextcloud_card_ids: set[str] = set() # Iterate through boards for board in boards: # Skip archived boards if board.archived: continue # Skip deleted boards (soft delete: deletedAt > 0) if board.deletedAt > 0: logger.debug(f"[SCAN-{scan_id}] Skipping deleted board {board.id}") continue # Get stacks for this board stacks = await nc_client.deck.get_stacks(board.id) # Iterate through stacks for stack in stacks: # Skip if stack has no cards if not stack.cards: continue # Iterate through cards in stack for card in stack.cards: # Skip archived cards if card.archived: continue card_count += 1 doc_id = str(card.id) nextcloud_card_ids.add(doc_id) # Use lastModified timestamp if available modified_at = card.lastModified or 0 if initial_sync: # Send everything on first sync - write placeholder first await write_placeholder_point( doc_id=doc_id, doc_type="deck_card", user_id=user_id, modified_at=modified_at, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="deck_card", operation="index", modified_at=modified_at, metadata={"board_id": board.id, "stack_id": stack.id}, ) ) queued += 1 else: # Incremental sync: check if card exists and compare modified_at doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: logger.debug( f"Deck card {doc_id} reappeared, removing from deletion grace period" ) del _potentially_deleted[doc_key] # Query Qdrant for existing entry existing_metadata = await query_document_metadata( doc_id=doc_id, doc_type="deck_card", user_id=user_id ) needs_indexing = False if existing_metadata is None: needs_indexing = True elif existing_metadata.get("modified_at", 0) < modified_at: needs_indexing = True elif existing_metadata.get("is_placeholder", False): queued_at = existing_metadata.get("queued_at", 0) placeholder_age = time.time() - queued_at stale_threshold = settings.vector_sync_scan_interval * 5 if placeholder_age > stale_threshold: logger.debug( f"Found stale placeholder for deck card {doc_id} " f"(age={placeholder_age:.1f}s), requeuing" ) needs_indexing = True if needs_indexing: await write_placeholder_point( doc_id=doc_id, doc_type="deck_card", user_id=user_id, modified_at=modified_at, ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="deck_card", operation="index", modified_at=modified_at, metadata={"board_id": board.id, "stack_id": stack.id}, ) ) queued += 1 logger.info( f"[SCAN-{scan_id}] Found {card_count} deck cards (non-archived) for {user_id}" ) record_vector_sync_scan(card_count) # Check for deleted cards (not initial sync) if not initial_sync: grace_period = settings.vector_sync_scan_interval * 1.5 current_time = time.time() for doc_id in indexed_card_ids: if doc_id not in nextcloud_card_ids: doc_key = (user_id, doc_id) if doc_key in _potentially_deleted: first_missing_time = _potentially_deleted[doc_key] time_missing = current_time - first_missing_time if time_missing >= grace_period: logger.info( f"Deck card {doc_id} missing for {time_missing:.1f}s " f"(>{grace_period:.1f}s grace period), sending deletion" ) await send_stream.send( DocumentTask( user_id=user_id, doc_id=doc_id, doc_type="deck_card", operation="delete", modified_at=0, ) ) queued += 1 del _potentially_deleted[doc_key] else: logger.debug( f"Deck card {doc_id} missing for first time, starting grace period" ) _potentially_deleted[doc_key] = current_time return queued