Files
mcp-nextcloud/tests/integration/_search_helpers.py
T
Chris CoutinhoandClaude Opus 4.8 7c13c6e49a test(integration): address round-4 review — type hints & small robustness
- Type the new helper signatures (CLAUDE.md A5): `mcp_client: Any` in
  document_is_searchable and `nc_mcp_client: Any` in _top_score.
- _top_score: guard the results list directly (`if not results`) instead of via
  total_found, so max() can't hit an empty sequence.
- _get_with_retry: replace `raise last_exc  # type: ignore` with an explicit
  `assert last_exc is not None` then raise — clearer intent, no suppressor.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-17 23:04:26 +02:00

51 lines
1.9 KiB
Python

"""Shared helpers for asserting vector-sync visibility in integration tests.
Kept dependency-light (no Playwright) so both the multi-user-basic UI tests and
the single-user sampling tests can import it.
"""
import json
import logging
from typing import Any
logger = logging.getLogger(__name__)
async def document_is_searchable(
mcp_client: Any, search_term: str, note_id: int | None = None
) -> bool:
"""Return True once a freshly-created document is retrievable.
Polls ``nc_semantic_search`` (hybrid: an exact unique term reliably matches
on the keyword side) and matches by ``note_id`` when provided, otherwise by
the term appearing in a result's title/excerpt. Transient errors return
False so callers can keep polling.
"""
try:
search = await mcp_client.call_tool(
"nc_semantic_search",
# limit is generous: a fresh note can sit below seed data (e.g. deck
# cards) in a crowded corpus, and the query is cheap.
arguments={"query": search_term, "limit": 50, "score_threshold": 0.0},
)
except Exception as e: # transient transport/availability blip — keep polling
logger.debug("Semantic search poll failed: %s", e)
return False
if search.isError:
logger.debug("Semantic search poll error: %s", search)
return False
results = json.loads(search.content[0].text).get("results", [])
# Token match (not contiguous substring) so multi-word terms work in the
# note_id-less fallback path.
tokens = search_term.lower().split()
for r in results:
if note_id is not None:
if r.get("id") == note_id and r.get("doc_type") == "note":
return True
else:
haystack = f"{r.get('title', '')} {r.get('excerpt', '')}".lower()
if tokens and all(t in haystack for t in tokens):
return True
return False