"""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)
# 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]
]
max_timestamp = max(timestamps)
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]}
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]
}
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
if queued > 0:
logger.info(
f"Sent {queued} documents ({file_queued} files) for incremental sync: {user_id}"
)
else:
logger.debug(f"No changes detected for {user_id}")
