fix(vector): normalize doc_id to str + add Qdrant keyword payload indexes

Production was logging two cascading classes of Qdrant errors against the
welcomed-malamute deployment:

1. HTTP 400 — "Bad request: Index required but not found for \"doc_id\" of
   one of the following types: [keyword]". The collection was created via
   create_collection() with no payload indexes, so any FieldCondition
   filter on doc_id failed at the Qdrant layer (placeholder writes/reads,
   eviction, search context lookups).

2. Compounding the missing index, producers wrote a mix of int and str
   doc_ids: webhook_parser stringified node_id, scanner stringified note
   IDs, news IDs, and deck card IDs — but the file scanner passed the
   numeric file_id through unchanged. A keyword index would not have
   covered both kinds even if it had existed.

This change:

- Normalizes doc_id to str at every producer site (scanner.py:459,
  DocumentTask.doc_id, indexed_*_ids reads from Qdrant).
- Tightens str|int annotations to str across placeholder.py,
  eviction.py, search/verification.py, search/context.py,
  SearchResult.id, and the auth/api visualization endpoints.
- Defensive str() coercion on doc_id reads in semantic.py /
  bm25_hybrid.py / vector/visualization.py for the transition window
  before the backfill runs.
- Adds an idempotent startup migration in get_qdrant_client():
  - _ensure_keyword_payload_indexes creates KEYWORD indexes for
    doc_id, user_id, and doc_type (tolerates "already exists" 400s).
  - _backfill_doc_id_to_string scrolls the collection once and rewrites
    int doc_ids to str. Skipped after a quick sample shows no legacy
    int payloads.
- Public API preserved: SemanticSearchResult.id stays int via explicit
  int(r.id) narrowing in server/semantic.py — surfaces a TypeError with
  actionable context if a future doc_type ships non-numeric ids.
- Documents the startup migration in docs/configuration.md.

Tests: 11 new unit tests in tests/unit/vector/test_qdrant_client.py
covering happy path / already-exists / unrelated-400 for the index
helpers, and sample-skip / mixed-batch rewrite / payload=None edge cases
for the backfill. 889 unit tests pass.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

nextcloud_mcp_server/vector/placeholder.py

@@ -31,7 +31,7 @@ from nextcloud_mcp_server.vector.qdrant_client import get_qdrant_client
 logger = logging.getLogger(__name__)
 
 
-def _generate_placeholder_id(doc_type: str, doc_id: str | int) -> str:
+def _generate_placeholder_id(doc_type: str, doc_id: str) -> str:
     """Generate deterministic UUID for placeholder point.
 
     Args:
@@ -46,7 +46,7 @@ def _generate_placeholder_id(doc_type: str, doc_id: str | int) -> str:
 
 
 async def write_placeholder_point(
-    doc_id: str | int,
+    doc_id: str,
     doc_type: str,
     user_id: str,
     modified_at: int,
@@ -60,7 +60,7 @@ async def write_placeholder_point(
     processing completes.
 
     Args:
-        doc_id: Document ID (int for notes/files)
+        doc_id: Document ID (always str — see DocumentTask)
         doc_type: Document type (note, file, etc.)
         user_id: User ID who owns the document
         modified_at: Document modification timestamp
@@ -135,7 +135,7 @@ async def write_placeholder_point(
 
 
 async def query_document_metadata(
-    doc_id: str | int,
+    doc_id: str,
     doc_type: str,
     user_id: str,
 ) -> dict | None:
@@ -185,7 +185,7 @@ async def query_document_metadata(
 
 
 async def delete_placeholder_point(
-    doc_id: str | int,
+    doc_id: str,
     doc_type: str,
     user_id: str,
 ) -> None:
@@ -230,7 +230,7 @@ async def delete_placeholder_point(
 
 
 async def update_placeholder_status(
-    doc_id: str | int,
+    doc_id: str,
     doc_type: str,
     user_id: str,
     status: str,