Commit History
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[NOTICKET] feat(knowledge): two review modes, recorded against a person (r1, r2, r3)
Rifqi Hafizuddin +1: Claude Opus 5Closes Sistem review. Section 7 landed in dedorch, so the columns are declared and written; verified read-only through the ORM against live before committing. r1 `review_mode` on the batch, chosen at ingest. "expert" leaves entries waiting for a human; "llm" approves them on arrival with NO reviewer step. Worth being plain about what the second one is: there is no second model call and no second opinion. The entries were written by a model already, and this mode means accepting them without a human looking. Default is "expert" - nobody gets LLM approval by accident. r2/r3 What makes that offerable rather than reckless is the record. `decided_by` says whether a human looked; `authorised_by` says on whose authority it happened. They are separate columns because the admin who clicks ingest and the expert who reviews can be different people, and in "llm" mode there is no reviewer at all - so without the clicker's id reaching the review row the de…6ef7990
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[NOTICKET] fix: gate spend in cluster units and surface the estimate (Step 6)
Rifqi Hafizuddin +1: Claude Opus 5Found on the way in, and it is the bigger half of this commit: the pre-flight ceiling was gating on a PARTIAL number. `estimate_cost` summed the glossary branch alone while reporting a field named `estimated_prompt_tokens`, so every consumer read a part as a whole. Measured on the three v2 artifacts, free: clusters calls old (glossary) new (all four) undercount BUMA 83 106 170,466 201,751 18.4% Komatsu 93 95 208,993 227,329 8.8% Open Pit 427 494 1,354,283 1,560,548 15.2% The Open Pit chapter is at 78.0% of the 2M ceiling, not 71%. Adds a SECOND ceiling on cluster count, which is what actually drives spend -- one LLM call per term cluster -- and unlike the token figure is exact and known for free. Two things the token ceiling cannot see: the cache hit rate degrades as a run grows, so the real bill rises faster than the estimate; and part of that estimate is…cdb5fe8
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/feat knowledge management (#20)
- [NOTICKET] docs: knowledge pipeline test integration — context, audited task checklist, DEV_PLAN §0.8 (8e69dc6c638509f4dd7b6775d520fb4aa4efbd3e) - [NOTICKET] docs: knowledge pipeline — reframe kex as prototype, not port target (7cce5ffc9ab88791ac139dbef8e88e124a3d049e) - [NOTICKET] feat(eval): knowledge-extraction gold set, scorer + frozen prototype baseline (60cf4a885ef31a8aa64916f5a70ac5a0e8062c5f) - [NOTICKET] chore: add missing planner and readiness eval results (bd6659b3bf523597e4482b04ab1fcff5e1284d25) - [NOTICKET] feat(knowledge_extraction): free stages — models, seam adapter, filters, cluster, ranking (024c30abd1189119d33508eded334fe5a3ed5011) - [NOTICKET] fix(knowledge_extraction): move runner into the package; fix two ranking defects (72605ff6876a7936ab685d417c766ce820f6214b) - [NOTICKET] feat(knowledge_extraction): span filter — E1 recall 0.8537, matches the frozen baseline (3a016343398753cf730d50548c0e92ff47c6716c) - [NOTICKET] feat(knowledge_extraction): paid extraction …b68816f
