feat(retrieval): a tuned number carries the space it was measured in (#4104)
CI & Build / Python lint (push) Successful in 3s
CI & Build / Plugin hooks (push) Successful in 10s
CI & Build / integration (push) Successful in 48s
CI & Build / TypeScript typecheck (push) Successful in 53s
CI & Build / Python tests (push) Failing after 1m4s
CI & Build / Build & push image (push) Skipped

Milestone 416 step 6. A retrieval floor is a cosine similarity, which only
means something inside one embedding model's geometry over documents cut one
particular way. Change either and every floor on the install keeps applying
while describing nothing — and nothing anywhere says so, because the scores
simply come out different and the bar goes on cutting.

`CHUNKER_VERSION` already solved this for documents: stamped per row, so the
backfill re-embeds precisely what is stale. The same idea, applied to the
numbers:

- `calibration_stamp()` — embedding model + document shape, one definition.
  TWO fields, never a fused string (rule 149): a mismatch has to say WHICH half
  moved, because they call for different responses.
- `retrieval_tuning_events` gains `embedding_model` / `shape_version`
  (migration 0104), stamped on every write. Nullable and NOT backfilled —
  "unstamped" is the honest answer for a row written before this existed, and
  it reports as `stale: null`, never as fine.
- `current_settings` reports calibration per dial: tuned rows from their event,
  untouched dials from the registry default's own stamp.
- `retrieval_surfaces` and the Settings panel show the mismatch. The panel
  renders ONLY when something is stale, so seeing it at all is the signal.
- `migrate_floor` / `migrate_retrieval_floor` answers "a path for thresholds to
  be inherited by the next model so that they don't have to recalibrate a lot":
  the raw cosine cannot cross models, but the PERCENTILE it represented can.
  Measure what fraction of a surface's logged calls the old floor admitted,
  re-score those queries under the current model, take the value admitting the
  same fraction. Dry run by default; applying writes an ordinary tuning event
  with the arithmetic in its reason.

Nothing auto-retunes. A stale stamp says a number is no longer a measurement;
it does not say what the number should be, and #4102 measured the one case
where the statistic and the correct action pointed opposite ways.

The load-bearing test is an ABSENCE: no chat-model identifier may appear
anywhere in the calibration path. Claude produces none of these scores, so a
Claude upgrade must trigger nothing — a false alarm here teaches the operator
to ignore the real one on the day bge-small becomes bge-base.

Backup v17 carries both columns, unfilled on the way out and on the way back:
a round trip must not turn "we don't know" into a stated fact.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01821k5B3Ysecp9fNYs92Kuy
This commit is contained in:
2026-09-17 12:45:48 -04:00
co-authored by Claude Opus 5
parent dcf800ed65
commit aee24c9c1c
13 changed files with 1002 additions and 2 deletions
+19 -1
View File
@@ -74,8 +74,14 @@ logger = logging.getLogger(__name__)
# argument for them silently dropped — and from this step on those dials are
# moved by the model, which is exactly the case where the operator needs the
# argument to review.
# v17 (2026-09) added retrieval_tuning_events.embedding_model / shape_version
# (milestone 416 step 6): a floor is a distance in ONE embedding model's
# geometry over documents cut one particular way, so the number alone cannot
# say whether it still measures anything. Both travel NULLABLE and unfilled —
# a row written before the stamp existed restores unstamped, because inventing
# the model it was measured under would turn "unknown" into a stated fact.
# Bump when the serialized schema changes.
BACKUP_VERSION = 16
BACKUP_VERSION = 17
# Every table this backup carries, by its REAL name. Paired with _NOT_INCLUDED
# below, these two lists must together account for the entire schema — which is
@@ -358,6 +364,12 @@ def _retrieval_tuning_event_rows(rows) -> list[dict]:
"user_id": r.user_id, "surface": r.surface, "dial": r.dial,
"old_value": r.old_value, "new_value": r.new_value,
"actor": r.actor, "reason": r.reason,
# Carried, and NOT defaulted to the current model on the way out
# (#4104): a row that was unstamped when it was written is still
# unstamped after a round trip, and a backup that quietly filled
# the gap would turn "we don't know" into a stated fact.
"embedding_model": r.embedding_model,
"shape_version": r.shape_version,
"created_at": r.created_at.isoformat() if r.created_at else None,
}
for r in rows
@@ -1247,6 +1259,12 @@ async def _restore_v2(data: dict) -> dict:
new_value=t_data.get("new_value"),
actor=t_data.get("actor") or "model",
reason=t_data.get("reason", ""),
# .get with no default, deliberately (v17): an archive written
# before the stamp existed has no key here, and None is the
# right answer for it — the same "unstamped" a pre-#4104 row
# carries in place.
embedding_model=t_data.get("embedding_model"),
shape_version=t_data.get("shape_version"),
created_at=_dt(t_data.get("created_at")),
))
stats["retrieval_tuning_events"] += 1