perf(deck): optimize card lookup by storing board_id/stack_id in metadata
Addresses reviewer feedback on PR #395 about O(n²) performance issue. Changes: - scanner.py: Add metadata field to DocumentTask with board_id/stack_id - scanner.py: Populate metadata during deck card scanning (both initial and incremental sync) - processor.py: Use metadata for O(1) card lookup via get_card() API when available - processor.py: Fallback to iteration for legacy data without metadata - context.py: Add _get_deck_metadata_from_qdrant() helper to retrieve metadata from Qdrant - context.py: Use metadata for fast path lookup in chunk context expansion - context.py: Add user_id parameter to _fetch_document_text() for metadata retrieval Performance Impact: - Before: O(boards × stacks × cards) iteration for each card lookup - After: O(1) direct API call using stored board_id/stack_id - Graceful degradation: Falls back to iteration for legacy data Testing: - All existing integration tests pass (test_deck_vector_search.py) - Type checking passes with no new errors 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
Chris Coutinho
co-authored by
Claude Sonnet 4.5
Claude Sonnet 4.5
parent
034e405824
commit
e0320e761c
@@ -209,6 +209,64 @@ async def _get_file_path_from_qdrant(
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return None
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async def _get_deck_metadata_from_qdrant(
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user_id: str, card_id: int
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) -> dict[str, int] | None:
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"""Retrieve board_id and stack_id for a deck card from Qdrant payload.
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Args:
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user_id: User ID who owns the card
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card_id: Card ID
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Returns:
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Dictionary with board_id and stack_id, or None if not found
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"""
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try:
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from qdrant_client.models import FieldCondition, Filter, MatchValue
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from nextcloud_mcp_server.config import get_settings
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from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client
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qdrant_client = await get_qdrant_client()
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settings = get_settings()
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# Query for any chunk of this card (we just need metadata)
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scroll_result = await qdrant_client.scroll(
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collection_name=settings.get_collection_name(),
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scroll_filter=Filter(
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must=[
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FieldCondition(key="user_id", match=MatchValue(value=user_id)),
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FieldCondition(key="doc_id", match=MatchValue(value=card_id)),
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FieldCondition(key="doc_type", match=MatchValue(value="deck_card")),
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]
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),
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limit=1,
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with_payload=["board_id", "stack_id"],
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with_vectors=False,
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)
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if scroll_result[0]:
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point = scroll_result[0][0]
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board_id = point.payload.get("board_id")
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stack_id = point.payload.get("stack_id")
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if board_id is not None and stack_id is not None:
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logger.debug(
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f"Retrieved deck metadata for card {card_id}: "
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f"board_id={board_id}, stack_id={stack_id}"
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)
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return {"board_id": int(board_id), "stack_id": int(stack_id)}
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logger.debug(
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f"Could not find deck metadata in Qdrant for card {card_id} "
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f"(might be legacy data without board_id/stack_id)"
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)
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return None
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except Exception as e:
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logger.debug(f"Error querying Qdrant for deck metadata: {e}")
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return None
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@dataclass
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class ChunkContext:
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"""Expanded chunk with surrounding context and position markers.
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@@ -394,7 +452,9 @@ async def get_chunk_with_context(
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logger.debug(f"Resolved file_id {doc_id} to file_path {file_path}")
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# Fetch full document text
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full_text = await _fetch_document_text(nc_client, resolved_doc_id, doc_type)
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full_text = await _fetch_document_text(
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nc_client, resolved_doc_id, doc_type, user_id
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)
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if full_text is None:
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logger.warning(
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f"Could not fetch document text for {doc_type} {doc_id}, "
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@@ -453,7 +513,7 @@ async def get_chunk_with_context(
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async def _fetch_document_text(
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nc_client: NextcloudClient, doc_id: str | int, doc_type: str
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nc_client: NextcloudClient, doc_id: str | int, doc_type: str, user_id: str
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) -> str | None:
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"""Fetch full text content of a document.
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@@ -546,44 +606,71 @@ async def _fetch_document_text(
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return "\n".join(content_parts)
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elif doc_type == "deck_card":
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# Fetch card from Deck API
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# Note: Deck API requires board_id and stack_id, but we don't store those
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# We need to search through boards to find the card (same as processor.py)
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boards = await nc_client.deck.get_boards()
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card_found = False
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# Try to get board_id/stack_id from Qdrant metadata (O(1) lookup)
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# Otherwise fall back to iteration (legacy data)
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card = None
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deck_metadata = await _get_deck_metadata_from_qdrant(user_id, int(doc_id))
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for board in boards:
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if card_found:
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break
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# Skip deleted boards (soft delete: deletedAt > 0)
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if board.deletedAt > 0:
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if deck_metadata:
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# Fast path: Direct lookup with known board_id/stack_id
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board_id = deck_metadata["board_id"]
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stack_id = deck_metadata["stack_id"]
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try:
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card = await nc_client.deck.get_card(
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board_id=board_id, stack_id=stack_id, card_id=int(doc_id)
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)
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logger.debug(
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f"Skipping deleted board {board.id} while searching for card {doc_id}"
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f"Retrieved deck card {doc_id} using metadata "
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f"(board_id={board_id}, stack_id={stack_id})"
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)
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except Exception as e:
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logger.warning(
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f"Failed to fetch card with metadata (board_id={board_id}, "
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f"stack_id={stack_id}, card_id={doc_id}): {e}, falling back to iteration"
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)
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continue
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stacks = await nc_client.deck.get_stacks(board.id)
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# Fallback: Iterate through all boards/stacks (for legacy data or if fast path failed)
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if card is None:
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boards = await nc_client.deck.get_boards()
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card_found = False
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for stack in stacks:
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for board in boards:
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if card_found:
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break
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if stack.cards:
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for card in stack.cards:
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if card.id == int(doc_id):
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# Reconstruct full content as indexed: title + "\n\n" + description
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# This ensures chunk offsets align with indexed content structure
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content_parts = [card.title]
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if card.description:
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content_parts.append(card.description)
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card_found = True
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logger.debug(
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f"Found deck card {doc_id} in board {board.id}, stack {stack.id}"
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)
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return "\n\n".join(content_parts)
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# Card not found (might be archived or deleted)
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logger.warning(f"Deck card {doc_id} not found in any board/stack")
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return None
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# Skip deleted boards (soft delete: deletedAt > 0)
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if board.deletedAt > 0:
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logger.debug(
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f"Skipping deleted board {board.id} while searching for card {doc_id}"
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)
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continue
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stacks = await nc_client.deck.get_stacks(board.id)
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for stack in stacks:
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if card_found:
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break
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if stack.cards:
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for c in stack.cards:
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if c.id == int(doc_id):
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card = c
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card_found = True
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logger.debug(
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f"Found deck card {doc_id} in board {board.id}, "
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f"stack {stack.id} (fallback iteration)"
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)
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break
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if not card_found:
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logger.warning(f"Deck card {doc_id} not found in any board/stack")
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return None
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# Reconstruct full content as indexed: title + "\n\n" + description
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# This ensures chunk offsets align with indexed content structure
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content_parts = [card.title]
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if card.description:
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content_parts.append(card.description)
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return "\n\n".join(content_parts)
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else:
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logger.warning(f"Unsupported doc_type for context expansion: {doc_type}")
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return None
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