A review of 5289cb4 found the ASR report was not honest arithmetic:
- "audio s" was the last segment's end, not the media length. The real
container durations are 88.93 / 109.18 / 60.07 s, so the report understated
the audio by 48 s and every speed cell was wrong.
- Decoding was unpinned, so a rerun was a new draw: WER moved 0.242 to 0.262
and one video moved 0.278 to 0.583. Greedy single-temperature decoding with
no carry-over now answers the same way twice, and the harness runs the pass
twice to show it.
- The report claimed its WER was an upper bound. It is not a bound in either
direction: a caption that drops words also hides words the model dropped.
The denominators (201 / 296 / 36 reference words) are printed instead.
- "66 speech atoms" was bench-side arithmetic. The store now says 80 audio
atoms carrying 563 word timestamps, read back after a real ingest.
Same silent-skip bug in a second place: a text file over max_text_file_bytes
returned an empty batch with no reason. It raises FileTooLarge with its size,
and a walk records that refusal like any other.
Also fixed from the same review: the Go search tool never published the audio
modality, cli_senses carried a second json_dump, the no-audio-track branch had
a test that fed it markdown, _seconds was an empty wrapper, and the docstring
quoted a speed no report measured.
Gate root cause: bench/tests imports the bench package by name with no root
conftest, so bare pytest could not collect it at all. pythonpath in pyproject
fixes both launch styles; 212 tests pass either way.
Verification: 212 passed (bare pytest and python -m pytest), ruff clean,
mypy clean on the six touched files with a cold cache, repo-wide mypy 24/6
unchanged from HEAD, pyright 0 errors on the touched files, go build/vet/test
and gofmt clean.
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.
Local read-only Model Context Protocol server (Go) exposing the .ely_eye memory
store to coding agents such as Codex and Claude Code: nine tools over status,
cartridges, Evidence Atoms, compiled evidence packs, proof suites, and HashHop
proofs. One-line cross-platform install (no Docker), with a prebuilt-binary
release workflow.
ZacharyZhang-NY