copy_store lived in dense_scale, so the two harnesses that also needed it reached back into a
measurement module for a plumbing helper. It now sits in systems beside the product path it
protects, and bench.run passes a scratch directory to the live check: the product path migrates
whatever database it opens, and the frozen baseline is cited evidence.
The dense leg used to be a pair of files next to the database: a full .npy
re-encoded from every atom, re-normalized on every query, and stale the moment
anything was ingested. It is now a vec0 table inside the same SQLite file,
written in the same transaction as the atom it describes, so a memory is
queryable the instant it is remembered.
- vector_index.py maintains the table; the writer inserts, the reader never
rebuilds. A repair scan (ely-eye build-dense-index) catches what a crash hid,
and it is not on the search path.
- Ranking stays in the engine; every boundary (closed, retired, not yet true,
another holder's private memory, the mounted cartridge) is checked once against
the atoms table afterwards. A visibility subquery inside the KNN cost 48.9s on
153,857 vectors; the same check over 200 candidates costs 0.2ms. When the
boundaries reject enough candidates the ask widens once, never twice.
- The Go mirror and the web panel carry the new status fields.
- bench/dense_scale.py and bench/quant_probe.py measure the leg at corpus size;
bench/scale_check.py now works on a copy so the frozen baseline stays frozen.
Measured on the frozen 165,973-atom corpus. bench/reports/DENSE.md, QUANT.md and
SCALE.md carry the numbers and the machine they were taken on.
Gates: 285 pytest, ruff clean, pyright 0 on the touched files, go build/vet/test
and gofmt clean, frontend build and eslint clean. mypy is 25 findings against the
parent's 24: the new one is "Skipping analyzing sqlite_vec: missing library stubs",
the same class as the two existing qwen_vl_utils lines, and the repo keeps no
type: ignore anywhere.
The 500-line rule and the one-line-comment rule were enforced only from
memory, so they drifted. bench/filesize_check.py now checks the budget on
every tracked source file, and it passes.
Split, with behaviour proven unchanged by comparing each moved function body
against HEAD byte for byte (53 training bodies, 21 benchmark bodies, 0
differences):
db.py 503 -> 396 store_search.py 105
bench/run.py 609 -> 351 query_set.py 80, report.py 211
benchmarks.py 619 -> 424 benchmark_scoring.py 262
training.py 1630 -> 94 training_{common,encode,metrics,datasets,lora,retrieval}
TrainingService stays as a thin facade for the CLI; the facade's parameter
lists are pinned against the module functions by inspect, which is what
catches a leaked self.
Deleted the eight top-level functions no file called, after fixing the scan
that had reported 201 false positives by skipping the defining file. The
v1/v2/v3 sweep found nothing to delete and says so: every remaining version
tag is an on-disk format marker, a migration step, a fixture name, or a
third-party model name.
Collapsed 39 multi-line comment blocks (86 lines) to one line each, keeping
the measured facts and error strings that justify the code.
269 tests pass; ruff clean; mypy 24 errors in 9 files against a 24-in-6
baseline, net zero; pyright 4, the same four HEAD measures.
The product path pulled every atom into Python and rebuilt a BM25Okapi
index per query: p50 20.16s over 165,973 atoms. It now runs one SQLite
statement with LIMIT/OFFSET.
- text_index.py: one normalizer for both sides of the index. CJK runs are
split per character (unicode61 cannot segment them), camelCase and
separators are split so "search atoms" finds SearchAtoms, latin tokens
get a prefix match. Rows written before this existed hold raw text in
atom_fts, so schema v3 rebuilds the index on upgrade.
- retrieval.py: filters (holder / scenario / source / modality / since /
until / min_trust), a base64 cursor, and reciprocal rank fusion in place
of the 0.55/0.35/0.10 blend whose graph term was always zero.
- An empty result is {status: "no_match"}, not a bare array.
- Go: search_atoms and compile_context rank through POST /api/search. The
second Go tokenizer is deleted; two implementations could drift, which
is what the MCP/HTTP parity requirement forbids.
- db.py passed 500 lines, so the row codec moved to row_codec.py.
- Tooling: installed the repo's own pyright. pyrightconfig.json had no
exclude and swept the downloaded corpus (1171 errors); with excludes the
count is 62, all pre-existing (evals 48, profiles 4, training 4,
ingestion 3, runtime 2, cartridge_assets 1). backend/pyproject.toml
carried a second [tool.pyright] that shadowed the root config; deleted.
- bench/scale_check.py measures the product search at corpus size. The
100k-atom p50 number is not written until it is measured on an idle
machine.
Verification: 112 pytest passed; go build/vet/test clean, gofmt clean;
ruff clean on every touched file; mypy clean on the 14 touched Python
files; repo pyright 62 errors, unchanged per-file ledger.
ZacharyZhang-NY