feat(retrieval): a tuned number carries the space it was measured in (#4104)
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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
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@@ -5,6 +5,7 @@ bar did; these say what the bar IS, and let it be changed with the argument
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attached.
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"""
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from scribe.mcp._context import current_user_id
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from scribe.services import retrieval_migration as migration_svc
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from scribe.services import retrieval_tuning as tuning_svc
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@@ -37,6 +38,33 @@ async def retrieval_surfaces() -> dict:
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are starting points: they were measured against one corpus with one
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embedding model and cannot be right for another install by construction.
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That is why this tool exists rather than a better set of defaults.
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`calibration` says what SPACE each number was chosen in, per dial, and
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whether that space has moved. A floor is a cosine distance in one embedding
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model's geometry over documents cut one particular way; swap the model and
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every score shifts at once, re-cut the documents and the same record embeds
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different text. Either way the number is a measurement of something that no
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longer exists, and no amount of telemetry will say so — the scores simply
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come out different and the bar keeps applying.
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Read the three fields apart:
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- `stale: true` with `model_changed` — the geometry is new. Every floor on
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this install needs re-measuring, not adjusting; a number that meant "quite
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similar" in the old space means nothing particular in this one.
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- `stale: true` with `shape_changed` — the documents are cut differently.
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The scale still holds, but what a record embeds has changed, so which
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records clear a bar has.
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- `stale: null`, `source: "unstamped"` — the dial was moved before Scribe
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recorded this. It was measured under SOMETHING and there is no way to say
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what, which is a different answer from "it is fine". Treat it as worth
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re-measuring, and the next tuning call stamps it.
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NOTHING IS RETUNED AUTOMATICALLY on the strength of this, here or anywhere.
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A stale stamp says a number is no longer a measurement; it does not say what
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the number should be. That judgement wants the same procedure as any other
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tuning change — `retrieval_telemetry(near_miss_samples=5)`, open the records
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it names, then `tune_retrieval` with what you read in the reason.
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"""
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return {"surfaces": await tuning_svc.current_settings(current_user_id())}
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@@ -109,7 +137,53 @@ async def retrieval_tuning_history(surface: str = "", limit: int = 20) -> dict:
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}
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async def migrate_retrieval_floor(
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surface: str, sample: int = 200, apply: bool = False,
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) -> dict:
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"""Carry one surface's floor across an embedding-model or chunker change.
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Reach for this when `retrieval_surfaces` reports a dial `stale` — and only
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then. A floor is a cosine similarity, so a new embedding model moves every
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score on the install at once and the stored number silently stops describing
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anything. Re-deriving six floors by reading telemetry is the work this
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avoids.
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WHAT IT TRANSFERS. Not the number — the SELECTIVITY. A floor's real content
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is a decision about how much of what an arm sees is worth spending attention
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on, and that decision survives a change of units. This measures what fraction
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of the surface's recent calls the old floor admitted, re-scores those same
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queries under the current model, and proposes the value that admits the same
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fraction.
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DRY RUN BY DEFAULT. With `apply=False` it returns the arithmetic and writes
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nothing. Read it before applying: the sample sizes, both score ranges, and
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whether the shift looks like a change of scale or like a corpus that has not
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finished re-embedding. A model change is the moment every number is
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uncertain at once, which is the worst moment to let a statistic move dials
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unattended.
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AND IT IS STILL A STARTING POINT. Percentile-preserving means the new floor
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is as good as the old one was, not better — if the old floor was wrong, this
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faithfully carries the wrongness onto the new scale. It is the number to
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begin from while the surface collects enough calls to judge properly, which
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is `retrieval_telemetry(near_miss_samples=5)` and `tune_retrieval` as usual.
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Args:
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surface: the surface name from `retrieval_surfaces`.
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sample: how many recent logged calls to re-score, default 200. Each one
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is an embedding plus a scan, so this is real work; a surface with
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only a handful of logged calls gives a percentile made of noise.
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apply: False (default) returns the proposal. True writes it, as an
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ordinary tuning event with the arithmetic in its reason — so a
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migrated floor is reviewable and revertible like any other.
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"""
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return await migration_svc.migrate_floor(
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current_user_id(), surface, sample=sample, apply=apply,
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)
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def register(mcp) -> None:
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mcp.tool(name="retrieval_surfaces")(retrieval_surfaces)
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mcp.tool(name="migrate_retrieval_floor")(migrate_retrieval_floor)
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mcp.tool(name="tune_retrieval")(tune_retrieval)
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mcp.tool(name="retrieval_tuning_history")(retrieval_tuning_history)
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