bvandeusenandClaude Opus 5.5
ccbccb025c
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Ordered straight off a *_embeddings table, the planner walks the HNSW index, takes ~ef_search (40) nearest chunks across every owner and project, and only then applies the scope: an in-scope record behind 40 nearer ones the caller cannot see was silently dropped. #4958 fixed the rule search alone; the note, milestone and system searches kept the fault. _scoped_chunks builds the in-scope chunks with their distance; _rank_scoped materializes them as a CTE and ranks exactly. All four searches go through it, and the row shape is unchanged, so callers and mocks are untouched. Tests: a structural guard that every semantic_search_* ranks through _rank_scoped and orders nothing itself (with a replay of the old shape), a compiled-SQL check of the MATERIALIZED CTE, and integration crowd tests - 80 nearer out-of-scope records - for notes (another user; the reader own other project), milestones and systems. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
95 lines
3.8 KiB
Python
95 lines
3.8 KiB
Python
"""Every semantic search scopes first, then ranks (#4958, #4961).
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Ordered straight off a `*_embeddings` table, the planner walks the HNSW index:
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it takes ~`hnsw.ef_search` (40) nearest chunks from every owner and project
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and filters them afterwards, so an in-scope record behind 40 nearer ones the
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caller cannot see is silently dropped. The fix is one shape, `_rank_scoped`,
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and these pin that every search goes through it — the rule search was fixed
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alone first, and the other three kept the fault because nothing said they
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were the same query.
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The integration lane's crowd tests show the behaviour on a real index; these
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are the guard that fails on the old shape whatever plan Postgres picks.
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"""
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from __future__ import annotations
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import ast
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from pathlib import Path
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from sqlalchemy.dialects import postgresql
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from scribe.models.embedding import NoteEmbedding
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from scribe.models.note import Note
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from scribe.services import embeddings as emb
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from tests.helpers import compiled_sql
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_SOURCE = Path("src/scribe/services/embeddings.py")
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def _searches() -> dict[str, ast.AsyncFunctionDef]:
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tree = ast.parse(_SOURCE.read_text())
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return {
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node.name: node for node in tree.body
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if isinstance(node, ast.AsyncFunctionDef)
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and node.name.startswith("semantic_search_")
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}
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def _calls(fn: ast.AST) -> list[str]:
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return [
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getattr(n.func, "attr", None) or getattr(n.func, "id", None)
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for n in ast.walk(fn) if isinstance(n, ast.Call)
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]
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def test_every_semantic_search_ranks_through_the_scoped_shape():
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searches = _searches()
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# The four corpora with an embedding table: if one is renamed or a fifth
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# is added, this has to be looked at rather than silently passing.
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assert set(searches) == {
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"semantic_search_notes", "semantic_search_rules",
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"semantic_search_milestones", "semantic_search_systems",
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}
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for name, fn in searches.items():
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calls = _calls(fn)
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assert "_rank_scoped" in calls, f"{name} does not rank through _rank_scoped"
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assert "_scoped_chunks" in calls, f"{name} does not build its scope as chunks"
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# Its own ORDER BY is the old shape: a distance ordered on the
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# embedding table, which the index serves before the scope applies.
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assert "order_by" not in calls, f"{name} orders by distance itself"
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def test_the_old_shape_would_be_caught():
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"""Rule 167: replay the guard against the query every search used to run."""
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old = ast.parse(
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"async def semantic_search_x():\n"
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" rows = await session.execute(select(Note, distance).select_from(E)"
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".join(Note, E.note_id == Note.id).where(scope)"
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".order_by(distance).limit(k))\n"
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).body[0]
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calls = _calls(old)
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assert "_rank_scoped" not in calls and "order_by" in calls
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def test_the_scope_is_materialized_and_the_order_is_over_it():
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# Column against column, so there is no vector literal to inline: the
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# shape is the subject here, not the query.
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distance = NoteEmbedding.embedding.cosine_distance(NoteEmbedding.embedding)
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scoped = (
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emb._scoped_chunks(NoteEmbedding, NoteEmbedding.note_id, distance)
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.join(Note, NoteEmbedding.note_id == Note.id)
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.where(Note.user_id == 1)
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)
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sql = compiled_sql(
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emb._rank_scoped(Note, scoped, name="scoped_x", limit=5),
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dialect=postgresql.dialect(),
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)
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# MATERIALIZED is what keeps the planner from inlining the CTE and walking
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# the index again; the ORDER BY must name the CTE's column, not the table's.
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assert "scoped_x AS MATERIALIZED" in sql
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assert "ORDER BY scoped_x.distance" in sql
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assert "note_embeddings.embedding <=>" in sql.split("ORDER BY")[0]
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# The scope sits inside the CTE, where the ranking draws from.
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cte_body = sql.split("AS MATERIALIZED", 1)[1].split("SELECT notes", 1)[0]
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assert "notes.user_id" in cte_body
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