Wire vector quantization (the §3.1 production knob): arborist embed
--quant int8 [--rebuild]. The chunk_vecs vec0 column becomes int8[384]
vs float[384] per quant; the quant folds into VEC_BACKEND_VERSION
(...-384int8-... / ...-384float32-...) and vec_meta records it per
shard. Switching quant on an existing chunk_vecs requires --rebuild
(the vec0 element type can't be altered in place — embed_documents
raises ValueError telling you to --rebuild).
int8 serialization: scale each bge component by 127 (theoretical
[-1,1] range), clamp to [-127,127], round, serialize_int8. The same
scaling on the query vector → distances comparable; cosine is
scale-invariant so the uniform x127 cancels in the ranking.
sqlite-vec v0.1.9 quirk worked around: a bare blob inserted into a
vec0 column is interpreted as float32 regardless of the column's
declared type — int8 vectors MUST be wrapped in vec_int8(...). So
the INSERT and the MATCH now wrap the blob in vec_f32(?) (float32)
or vec_int8(?) (int8) — constructor name from a fixed dict, no
injection surface. (Discovered the hard way: a bare int8 blob into
an int8[384] column → "expected int8, but a float32 vector was
provided".)
VecBackend reads the quant from the existing chunk_vecs schema (or
defaults to float32) so search uses the matching wrapper. New module
exports: QUANTS, EMBED_QUANT, vec_backend_version(quant), existing_quant.
int8 head-to-head on crawl_appliedcombinatorics_org.db (168 chunks):
- storage: float32 1,597,440 B -> int8 417,792 B = 3.8x smaller
(~4x at corpus scale where the 1024-vector blocks fill; the
~28 KB of vec0 metadata doesn't quarter, hence 3.8 not 4.0).
- recall vs the float32 baseline:
Q "how many ways to choose k things from n":
identical top-5 (Combinations, Permutations, Exercises,
Derangements, Graph Coloring).
Q "pigeonhole principle counting":
identical top-2 (Graph Coloring, Exercises); ranks 3-4 swap
Derangements <-> Permutations at Δdistance 0.002 — sub-noise.
- embed speed unchanged (~3.9 chunks/s — model-load-dominated).
Conclusion: int8 is the obvious production config (§3.1's +6%-tax
recommendation confirmed empirically). v1 default stays float32 for
max fidelity; flipping the default to int8 is a fox call.
CLI (arborist/cli.py): arborist embed --quant {float32,int8}; output
JSON gains "quant"; embed_documents ValueError → exit 2 with the
"--rebuild" hint.
tests/test_search_vec.py (9 -> 16): test_int8_quant_roundtrips
(int8[384] schema, vec_meta version, search round-trip, quant
inferred by VecBackend), test_quant_mismatch_requires_rebuild,
test_invalid_quant_rejected.
#000039 status updated. Full suite: 2343 passed, 28 skipped.
(Unrelated parallel-clone work in the tree — Makefile, arborist/qa/
verify.py, bench/fixtures/5f/*, tests/test_bench_batteries.py,
tests/test_verify.py — is #000046's hard-fixture tier, not touched.)
russell@unturf.com
06f5a11651