root 06e71520c4 matrix: playbook memory + boost — SPEC §3.4 component 5 of 5 (LEARNING LOOP)
Closes SPEC §3.4. The matrix indexer is now a learning meta-index per
feedback_meta_index_vision.md — every successful (query → answer)
pair recorded via /matrix/playbooks/record boosts that answer for
future similar queries.

This is the architectural piece that lifts vectord from "static
hybrid search" to the meta-index J originally framed in Phase 19 of
the Rust system.

What's new:
  - internal/matrix/playbook.go — PlaybookEntry, PlaybookHit,
    ApplyPlaybookBoost. Pure-function boost math:
      distance' = distance * (1 - 0.5 * score)
    Score 0 = no boost (factor 1.0); score 1 = halve distance
    (factor 0.5). Capped at 0.5 deliberately so a single high-
    confidence playbook can't dominate the base ranking forever
    (runaway-feedback-loop guard).
  - Retriever.Record(entry, corpus) — embeds query_text, ensures
    playbook corpus exists (idempotent), upserts via deterministic
    sha256-derived ID (last score wins on re-record of same triple).
  - Retriever.Search extended with UsePlaybook + PlaybookCorpus +
    PlaybookTopK + PlaybookMaxDistance. Reuses the query vector —
    no extra embed call. Missing-corpus 404 = no-op (cold-start
    state before any Record call), not an error.
  - POST /v1/matrix/playbooks/record (matrixd) — caller submits
    {query_text, answer_id, answer_corpus, score, tags?}; gets
    {playbook_id} back.

Storage: a vectord index named "playbook_memory" (configurable per
request) with embed(query_text) as the vector and the
PlaybookEntry JSON as metadata. Just another corpus — observable
from /vectors/index, persistable through G1P, etc.

Match key for boost: (AnswerID, AnswerCorpus). Cross-corpus ID
collisions don't false-match — verified by
TestApplyPlaybookBoost_CorpusAttributionRespected.

End-to-end smoke (scripts/playbook_smoke.sh, all assertions PASS):
  - Baseline search: widget-c at distance 0.6566 (rank 3)
  - Record playbook: query → widget-c, score=1.0
  - Re-search with use_playbook=true:
      widget-c distance: 0.3283 (rank 2)
      ratio: 0.5 EXACTLY (matches boost math precisely)
      playbook_boosted: 1
  - widget-c jumped from #3 to #2 — learning loop visible

Tests:
  - 8 unit tests in internal/matrix/playbook_test.go covering
    Validate, BoostFactor (5 cases), the no-boost identity, the
    boost-moves-result-up scenario, highest-score wins on duplicate
    matches, cross-corpus attribution, JSON round-trip, and
    rejection of empty metadata
  - scripts/playbook_smoke.sh integration test (3 assertions PASS)

15-smoke regression sweep all green (D1-D6, G1, G1P, G2,
storaged_cap, pathway, matrix, relevance, downgrade, playbook).

SPEC §3.4 NOW COMPLETE: 5 of 5 components shipped. The matrix
indexer's port is done as a substrate; remaining work is operational
(rating signal sources, telemetry, eventual structured filtering for
staffing data — none in §3.4).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 19:34:24 -05:00

golangLAKEHOUSE

Go reimplementation of the Lakehouse — a versioned knowledge substrate for staffing analytics + local AI workloads.

Status

Phase G0 complete + G1/G1P/G2 shipped. Six binaries plus a seventh (vectord) and an eighth (embedd) on top, fronted by a single gateway. Acceptance smokes green for D1-D6 + G1 + G1P + G2.

End-to-end staffing co-pilot pipeline functional through the gateway:

text → /v1/embed → /v1/vectors/index/<name>/add
text → /v1/embed → /v1/vectors/index/<name>/search → top-K hits

Plus the SQL path:

CSV  → /v1/ingest    (parses, writes Parquet via storaged, registers
                      manifest with catalogd)
SQL  → /v1/sql       (DuckDB over the registered Parquets via httpfs)

See docs/PHASE_G0_KICKOFF.md for the day-by-day record (D1-D6 + real-scale validation + G1/G1P/G2 pointer at the bottom).

Service inventory

Bin Port Role
gateway 3110 Reverse proxy fronting all backing services
storaged 3211 Object I/O over S3 (MinIO in dev)
catalogd 3212 Parquet manifest registry, ADR-020 idempotency
ingestd 3213 CSV → Parquet → register loop
queryd 3214 DuckDB SELECT over registered Parquets via httpfs
vectord 3215 HNSW vector search (+ optional persistence to storaged)
embedd 3216 Text → vector via Ollama (default nomic-embed-text 768-d)
mcpd stdio Model Context Protocol server (Claude Desktop / Code consumers)

MCP server

bin/mcpd exposes Lakehouse capabilities as MCP tools over stdio: list_datasets, get_manifest, query_sql, embed_text, search_vectors. All tools proxy to the gateway, so the gateway must be up first.

Wire into Claude Desktop / Claude Code by adding to the MCP config:

{
  "mcpServers": {
    "lakehouse": {
      "command": "/path/to/golangLAKEHOUSE/bin/mcpd",
      "args": ["--gateway", "http://127.0.0.1:3110"]
    }
  }
}

Replaces the Bun mcp-server.ts MCP-tool surface from the Rust system. HTTP demo routes (the staffing co-pilot UI) stay Bun until G5.

Acceptance smokes

scripts/d1_smoke.sh   # 5-binary skeleton + chi /health + gateway proxy probes
scripts/d2_smoke.sh   # storaged GET/PUT/LIST/DELETE + 256 MiB cap + concurrency cap
scripts/d3_smoke.sh   # catalogd register/manifest/list + rehydrate-across-restart
scripts/d4_smoke.sh   # ingestd CSV → Parquet round-trip + schema-drift 409
scripts/d5_smoke.sh   # queryd DuckDB SELECT through httpfs over MinIO
scripts/d6_smoke.sh   # full ingest → query through gateway only
scripts/g1_smoke.sh   # vectord HNSW recall + dim mismatch + duplicate-create 409
scripts/g1p_smoke.sh  # vectord state survives kill+restart via storaged
scripts/g2_smoke.sh   # embed → vectord add → search round-trip

Or run the full gate via the task runner (see below):

just verify     # vet + tests + 9 smokes; ~33s wall

Task runner

just                 # show available recipes
just verify          # full Sprint 0 gate (vet + tests + 9 smokes)
just smoke <day>     # single smoke (d1..d6, g1, g1p, g2)
just doctor          # check cold-start deps; --json for CI
just install-hooks   # install pre-push hook that runs just verify

After a fresh clone, run just install-hooks once so git push is gated on the same green chain that ran here. Hook lives in .git/hooks/pre-push (not tracked; recreated by the recipe).

Cold-start dependencies

  • Go 1.25+ at /usr/local/go/bin (arrow-go pulled the 1.25 floor)
  • gcc + libc-dev for the DuckDB cgo binding (ADR-001 §1.1)
  • just task runner (apt install just on Debian 13+)
  • MinIO running on :9000 with bucket lakehouse-go-primary
  • Ollama running on :11434 with nomic-embed-text loaded (G2)
  • /etc/lakehouse/secrets-go.toml with [s3.primary] credentials (storaged + queryd both read this)

just doctor probes all of the above and reports the fix command for each missing dep. CI / scripts can use just doctor --json.

Layout

docs/                         Direction + spec + ADRs + day-by-day
cmd/                          One main package per binary
internal/                     Shared packages — storeclient, catalogclient,
                                secrets, shared, embed, gateway, plus
                                per-service implementation packages
scripts/                      Smokes + ancillary tooling

Reading order

  1. docs/PRD.md — what we're building and why
  2. docs/SPEC.md — how, per-component
  3. docs/DECISIONS.md — ADRs (ADR-001 foundational)
  4. docs/PHASE_G0_KICKOFF.md — day-by-day from D1 through G2
  5. docs/RUST_PATHWAY_MEMORY_NOTE.md — historical reference for the Rust era's pathway memory (not migrated, by ADR-001 #5)

Predecessor

The Rust Lakehouse this rewrite supersedes lives at git.agentview.dev/profit/lakehouse. It remains the live system serving devop.live/lakehouse/ until this Go implementation reaches feature parity per docs/SPEC.md §7. Then Rust enters maintenance-only mode.

Description
Go reimplementation of the Lakehouse — versioned knowledge substrate for staffing analytics + local AI workloads
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