137d1d6c75
This commit addresses critical performance issues with vector visualization search (reducing time from 40s to ~2s) and improves result visualization through better visual encoding. ## Performance Fixes ### 1. Fix blocking sleep in retry decorator (base.py:51) - Changed `time.sleep(5)` to `await anyio.sleep(5)` in @retry_on_429 - Prevents entire event loop from freezing during rate limit retries - Impact: Reduced search time from 22s to 16s initially ### 2. Add concurrency limiting for verification (verification.py:77-93) - Added `anyio.Semaphore(20)` to limit concurrent HTTP requests - Prevents connection pool exhaustion (RequestError) from 90+ simultaneous requests - Fixes false filtering (was filtering 77/90 results incorrectly) - Note: Semaphore still in code but verification removed from viz endpoint ### 3. Remove unnecessary verification from viz endpoint (viz_routes.py:483-486) - Visualization only needs Qdrant metadata (title, excerpt), not full content - Verification only required for sampling (LLM needs full note content) - Impact: Reduced search time from 43.7s to ~2s (final fix) ### 4. Restore streaming scanner pattern (scanner.py) - Process notes one-at-a-time using async generator - Avoids loading all notes into memory ## Visualization Improvements ### 5. Result-relative score normalization (viz_routes.py:489-504) - Normalize scores within result set: best=1.0, worst=0.0 - Removes arbitrary RRF normalization (theoretical max didn't make sense) - Makes visual encoding meaningful regardless of algorithm scores ### 6. Power scaling for marker sizes (userinfo_routes.py:743) - Changed from linear `8 + (score * 12)` to power `6 + (score² * 14)` - Creates dramatic visual contrast: 0.0→6px, 0.5→9.5px, 1.0→20px - Combined with opacity (0.2-1.0) for clear visual hierarchy ### 7. Multi-channel visual encoding (userinfo_routes.py:740-745) - Size: Exponentially scaled with score² - Opacity: Linear 0.2-1.0 (keeps all points visible) - Color: Viridis gradient (blue→yellow) - Effect: Top results are large/bright/opaque, context results small/dim/transparent ## Result - Search time: 40s → ~2s (20x faster) - Visual contrast: Subtle → dramatic (clear result hierarchy) - No arbitrary cutoffs: All results visible, best naturally highlighted 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
316 lines
12 KiB
Python
316 lines
12 KiB
Python
"""Scanner task for vector database synchronization.
|
|
|
|
Periodically scans enabled users' content and queues changed documents for processing.
|
|
"""
|
|
|
|
import logging
|
|
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.qdrant_client import get_qdrant_client
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
|
|
@dataclass
|
|
class DocumentTask:
|
|
"""Document task for processing queue."""
|
|
|
|
user_id: str
|
|
doc_id: str
|
|
doc_type: str # "note", "file", "calendar"
|
|
operation: str # "index" or "delete"
|
|
modified_at: int
|
|
|
|
|
|
# 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"
|
|
)
|
|
|
|
# Get indexed state from Qdrant first (for incremental sync)
|
|
indexed_docs = {}
|
|
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", "indexed_at"],
|
|
with_vectors=False,
|
|
limit=10000,
|
|
)
|
|
|
|
indexed_docs = {
|
|
point.payload["doc_id"]: point.payload["indexed_at"]
|
|
for point in scroll_result[0]
|
|
}
|
|
|
|
logger.debug(f"Found {len(indexed_docs)} 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
|
|
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: compare with indexed state
|
|
indexed_at = indexed_docs.get(doc_id)
|
|
|
|
# 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]
|
|
|
|
# Send if never indexed or modified since last index
|
|
if indexed_at is None or modified_at > indexed_at:
|
|
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_docs:
|
|
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
|
|
|
|
if queued > 0:
|
|
logger.info(f"Sent {queued} documents for incremental sync: {user_id}")
|
|
else:
|
|
logger.debug(f"No changes detected for {user_id}")
|