feat: substitution search + build-status & OpenPOM-scope docs - #46
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…POM scope Add substitute() — Tanimoto/Morgan nearest-neighbor over the labeled molecule set (issue #22 core); each neighbor carries its known tastes. Track-A implementation; Track B mirrors it as a pgvector ANN query. Docs: - BUILD-STATUS.md: living inventory (built / needs-validation / stubbed / deferred) + product-vision staging (substitution now -> aroma-on-their-data pilot -> novel-molecule/retrosynthesis long-horizon). - AROMA.md: precise OpenPOM commercial scope — MIT *code* is usable, but its GS-LF training data is NonCommercial and its weights are encumbered; a usable aroma model must be our own, trained from scratch on licensed/customer data. - ARCHITECTURE.md: aroma row now points to AROMA.md.
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What
Substitution search (#22 core). Adds
substitute()topredict.py— Tanimoto/Morgan nearest-neighbor over the labeled molecule set, each neighbor returned with its known tastes. The reformulation / cost-down tool. Track-A implementation; Track B mirrors it as a pgvector ANN query over the same fingerprints (M6).Spot-checked: glucose → ribose/sugars (sim 0.94); vanillin → ethyl ferulate / creosol / anisaldehyde.
Docs
BUILD-STATUS.md(new) — living inventory of what's built / built-but-needs-validation / stubbed / deferred, plus the product-vision staging (substitution now → aroma-on-their-data pilot → novel-molecule + retrosynthesis long-horizon).AROMA.md— precise OpenPOM commercial scope: MIT code is usable, but the bundled GS-LF data is NonCommercial and weights trained on it are encumbered. A usable aroma model must be our own, trained from scratch on licensed (PMP 2001) or customer data.ARCHITECTURE.md— aroma row now points toAROMA.md.Notes
substitute()against the real labeled set;ruffclean; imports OK.