profit
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Bundles PR #9's work for the audit pipeline: - N=3 consensus on cloud inference (gpt-oss:120b parallel) with qwen3-coder:480b tie-breaker - audit_discrepancies.jsonl logs N-run disagreements - scrum_master reviews route through llm_team fact extraction; source="scrum_review" - Verifier-gated persistence: drops INCORRECT, keeps UNVERIFIABLE/UNCHECKED; schema_version:2 - scrum_master_reviewed flag on accepted reviews - auditor/kb_stats.ts: on-demand observability script - claim_parser history/proof pattern class (verified-on-PR, was-flipping, the-proven-X) - claim_parser quoted-string guard (mirrors static.ts fix) - fact_extractor project context injection via docs/AUDITOR_CONTEXT.md - Fixed verifier-verdict parser to handle multiple gemma2 output formats Empirical: 3-run determinism test on unchanged PR #9 SHA showed 7/7 warn findings stable; block count oscillation eliminated; llm_team quality scores 8-9 on context-injected extract runs. See PR #9 for full run-by-run commit history.
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Auditor Context — project preamble for fact extraction
This file is read by auditor/fact_extractor.ts and prepended to the
extract-facts prompt sent to llm_team. The goal: give the extractor +
verifier enough grounding to ground domain-specific facts instead of
marking them UNVERIFIABLE by default.
Keep this short (< 400 words). Verifier only reads the first ~4KB of the prompt alongside the facts. Longer = noise, not signal.
Update when: a new Phase lands, a crate is added/removed, the project's primary domain shifts (e.g. staffing → DevOps).
What Lakehouse is
Lakehouse is a Rust-first data platform over S3-compatible object storage. Primary use: a staffing company ingesting legacy CRM data for AI-powered worker matching, contract fulfillment, and playbook-driven coordination.
Architecture: 13 Rust crates + a Python sidecar (Ollama) + TypeScript sub-agents (auditor, scrum_master, bot). Runs on a single server (Nvidia A4000, 128GB RAM). All services on localhost: gateway :3100, sidecar :3200, UI :3300, MCP :3700, observer :3800, MinIO :9000.
Key crates (each maps to a responsibility)
- shared — types, Arrow helpers, PII utilities, SecretsProvider
- proto — gRPC definitions
- storaged — S3/MinIO I/O, AppendLog, ErrorJournal
- catalogd — metadata authority (manifests, views, tombstones)
- queryd — DataFusion SQL, MemTable cache, compaction
- ingestd — CSV/JSON/PDF/Postgres/MySQL ingest
- vectord — embeddings, HNSW index, playbook_memory meta-index (Phase 19+)
- vectord-lance — Lance 4.0 firewall crate (separate Arrow version)
- journald — append-only mutation event log
- aibridge — Rust↔Python sidecar bridge, context budget + continuation
- gateway — Axum HTTP :3100 + gRPC :3101 (Phase 38+ adds /v1/chat)
- ui — Dioxus WASM (stale, pre-Phase-9)
- lance-bench — standalone benchmark
Current architectural direction (Phase 38-44)
Universal AI Control Plane: a /v1/chat OpenAI-compatible API that
routes all LLM traffic through one layer for token accounting + provider
fallback. Truth Layer + Validation Pipeline enforce staffing-domain
invariants (worker eligibility, PII, contract rules). The Auditor
(Phase A of cohesion plan) hard-blocks PR merges on placeholder code.
Auditor sub-agent role
auditor/ (TypeScript, Bun runtime) polls Gitea every 90s for open PRs.
For each fresh head SHA it runs 4 checks in parallel: static (grep-style
placeholder detection), dynamic (runs the hybrid fixture), inference
(gpt-oss:120b cloud review with N=3 consensus + qwen3-coder:480b
tie-breaker), and kb_query (reads data/_kb/*.jsonl for prior evidence).
Verdicts post to Gitea as commit status + review comment. Findings
append to data/_kb/audit_lessons.jsonl (path-agnostic signatures for
dedup). Curated scratchpads from tree-split get routed through this
extract-facts pipeline to populate audit_facts.jsonl — which is what
you (the extractor) are currently producing.
Things that are NOT the auditor
- The LLM Team UI at
/root/llm_team_ui.py(devop.live:5000) — a separate product for human-facing multi-model experimentation - The scrum_master pipeline at
tests/real-world/scrum_master_pipeline.ts— reviews files, not claims - The bot at
bot/— will apply fixes, doesn't audit