Read-only natural-language query over the curated nl_query endpoint, answered
in-thread. Two entry points (room-per-purpose model): a dedicated Q&A room
(MATRIX_QUERY_ROOM) where every top-level message is a question, plus the
?/@bot trigger in the intake room as a cross-room convenience. Both routes hit
the same handle_query -> crm_client.nl_query -> POST /api/query/nl; translation
runs on the box's local model, nothing leaves the box, and there is no write
path so no approval gate applies.
Pure logic (trigger parsing, answer rendering) in query.py with offline tests;
async room wiring in bot.py (live-smoke only, per the bot's convention).
Bot-side only, ships on the Spark via git pull + restart. Depends on the
box-side /api/query/nl endpoint, which lands with the v93 s9pk (reminders + W2):
until v93 is installed the Q&A surface 404s, so the bot deploy is staged to
follow that install.
Read-only "ask the database in plain English" backend. Translation runs on
the local Qwen via Spark Control (question -> {intent, slots}); nothing leaves
the box, no Claude and no redaction boundary (the simplification chosen after
pressure-testing). The safe surface is a curated catalog of ~12 hand-written
parameterized queries; a slot validator is the trust boundary (no generic SQL,
no dynamic identifiers). POST /api/query/nl + GET /api/query/catalog, gated
require_bot_or_admin, read-only, audited. Soft-delete-correct per table.
Local Qwen translated 12/12 real example questions correctly against the live
Spark. Web "Ask" box and Matrix bot still to come (steps 4-5).
Keysat