Chris CoutinhoandClaude Opus 4.8
ef5b3f3873
Consume the astrolabe.semantic_search capability as the source of truth for which content sources an admin has approved for semantic search, and enforce it independently of Astrolabe (this server queries Qdrant directly). - capabilities.py: cached per-user reader for enabled_doc_types (TTL+LRU, fail-open so older Astrolabe / transient OCS errors don't break search) - semantic search: intersect requested doc_types with the allowed set; restrict to the allowed set when none requested; short-circuit when empty - scanner: skip disabled sources during discovery (files discovery yields nothing when disabled, so the existing grace-period reconcile purges them) - processor: drop near-real-time index tasks for disabled doc_types (webhook events bypass the scanner gate); deletes always proceed - vector/purge.py + POST /api/v1/vector-sync/purge: admin-only global delete-by-doc_type, called by Astrolabe when a source is disabled so consent is binding on data-at-rest Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
74 lines
2.6 KiB
Python
74 lines
2.6 KiB
Python
"""Global purge of indexed vectors by doc type (admin consent enforcement).
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When an admin disables a content source for semantic search in Astrolabe,
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consent is binding on data-at-rest: the already-indexed content for that
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source's doc type(s) must be deleted, not merely hidden. Astrolabe calls the
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``/api/v1/vector-sync/purge`` route on disable, which delegates here.
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The purge is global (every owner) because the admin disable is a global
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decision. It is safe to call for a doc type with no indexed points — Qdrant
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deletes zero points and reports a count of 0.
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"""
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from __future__ import annotations
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import logging
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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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logger = logging.getLogger(__name__)
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def _doc_type_filter(doc_type: str) -> Filter:
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return Filter(
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must=[FieldCondition(key="doc_type", match=MatchValue(value=doc_type))]
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)
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async def purge_doc_types(doc_types: list[str]) -> dict[str, int]:
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"""Delete every indexed point whose ``doc_type`` is in ``doc_types``.
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Returns a mapping of doc_type -> number of points deleted (counted before
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deletion). Each doc type is purged independently so a failure on one does
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not abort the rest; failures re-raise after the loop only if every doc type
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failed, otherwise partial progress is returned.
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"""
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qdrant_client = await get_qdrant_client()
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collection = get_settings().get_collection_name()
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purged: dict[str, int] = {}
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last_error: Exception | None = None
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for doc_type in dict.fromkeys(doc_types): # de-dupe, preserve order
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flt = _doc_type_filter(doc_type)
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try:
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count_result = await qdrant_client.count(
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collection_name=collection,
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count_filter=flt,
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exact=True,
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)
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await qdrant_client.delete(
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collection_name=collection,
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points_selector=flt,
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)
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purged[doc_type] = int(count_result.count)
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logger.info(
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"Purged %d indexed point(s) for disabled doc_type=%s",
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purged[doc_type],
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doc_type,
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)
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except Exception as exc: # noqa: BLE001 — record and continue
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last_error = exc
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logger.error(
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"Failed to purge indexed points for doc_type=%s: %s",
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doc_type,
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exc,
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)
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if not purged and last_error is not None:
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# Nothing succeeded — surface the failure to the caller (HTTP 500).
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raise last_error
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return purged
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