- IndexRegistry: tracks all vector indexes with model metadata
(model_name, model_version, dimensions, build stats)
- Index metadata persisted as JSON in vectors/meta/
- Rebuilt on startup for crash recovery
- GET /vectors/indexes — list all indexes (filter by source/model)
- GET /vectors/indexes/{name} — get index metadata
- Background jobs auto-register metadata on completion
- Multi-version support: same data, different models, coexist
- Per ADR-014: enables incremental re-embed on model upgrade
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- /read-mem skill: reads PRD, phases, decisions, checks live services
- Updated PHASES.md with all 15 phases tracked
- Updated project_lakehouse.md memory with full context
- Updated CLAUDE.md with project reference
- Skill at ~/.claude/skills/read-mem/ and project level
- Triggers on: "read mem", "project status", "where were we", "catch me up"
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- DatasetManifest expanded: description, owner, sensitivity, columns,
lineage, freshness contract, tags, row_count
- All new fields use #[serde(default)] for backward compatibility
- PII auto-detection: scans column names for email, phone, SSN, salary,
address, DOB, medical terms — flags as PII/PHI/Financial
- Column-level metadata: name, type, sensitivity, is_pii flag
- Lineage tracking: source_system, source_file, ingest_job, timestamp
- Ingest pipeline auto-populates: PII scan, column meta, lineage, row count
- PATCH /catalog/datasets/by-name/{name}/metadata — update metadata
- Catalog responses now include all rich fields
- 25 unit tests passing (5 new PII detection tests)
Per ADR-013: datasets without metadata become mystery files.
This makes every ingested file self-describing from day one.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- journald crate: immutable event log for every data mutation
- Events: entity_type, entity_id, field, action, old_value, new_value,
actor, source, workspace_id, timestamp
- In-memory buffer with configurable flush threshold (default 100 events)
- Flush writes events as Parquet to journal/ directory
- Query: GET /journal/history/{entity_id} — full history of any record
- Query: GET /journal/recent?limit=50 — latest events across all entities
- Convenience methods: record_insert, record_update, record_ingest
- Stats: GET /journal/stats — buffer size, persisted file count
- Manual flush: POST /journal/flush
- Per ADR-012: events are never modified or deleted
This is the single most important future-proofing decision.
Once history is lost, it's gone forever.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- JobTracker: create/update/complete/fail jobs with progress tracking
- POST /vectors/index now returns immediately with job_id (HTTP 202)
- Embedding runs in tokio::spawn background task
- GET /vectors/jobs/{id} returns live progress (chunks embedded, rate, ETA)
- GET /vectors/jobs lists all jobs
- Progress logged every 100 batches with chunks/sec and ETA
- 100K embedding job running successfully at 44 chunks/sec
- System stays responsive during embedding (queries in 23ms)
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- WorkspaceManager: create/get/list workspaces with daily/weekly/monthly/pinned tiers
- Saved searches: agent stores SQL queries in workspace context
- Shortlist: tag candidates/records to a workspace with notes
- Activity log: track calls, emails, updates per workspace per agent
- Instant handoff: transfer workspace ownership with full history
Zero data copy — just a pointer swap, receiving agent sees everything
- Persistence: workspaces stored as JSON in object storage, rebuilt on startup
- Endpoints: /workspaces/create, /{id}, /{id}/handoff, /{id}/search,
/{id}/shortlist, /{id}/activity
- Tested: Sarah creates workspace, saves searches, shortlists 3 candidates,
logs activity, hands off to Mike who continues seamlessly
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- MemCache: LRU in-memory cache for hot datasets (configurable max, default 16GB)
Pin/evict/stats endpoints: POST /query/cache/pin, /cache/evict, GET /cache/stats
- Delta store: append-only delta Parquet files for row-level updates
Write deltas without rewriting base files, merge at query time
- Compaction: POST /query/compact merges deltas into base Parquet
- Query engine: checks cache first, falls back to Parquet, merges deltas
- Benchmarked on 2.47M rows:
1M row JOIN: 854ms cold → 96ms hot (8.9x speedup)
100K filter: 62ms cold → 21ms hot (3x speedup)
1.1M rows cached in 408MB RAM
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Previous regex routes for /catalog, /storage, /health intercepted main site.
Now all lakehouse API calls go through /lakehouse/api/ prefix, stripped by nginx rewrite.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- ui: Dioxus WASM app with dataset sidebar, SQL editor (Ctrl+Enter), results table
- ui: dynamic API base URL (same-origin for nginx, port-based for local dev)
- gateway: CORS enabled for cross-origin requests
- nginx: lakehouse.devop.live proxies UI (:3300) + API (:3100) on same origin
- justfile: ui-build, ui-serve, sidecar, up commands added
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- queryd: SessionContext with custom URL scheme to avoid path doubling with LocalFileSystem
- queryd: ListingTable registration from catalog ObjectRefs with schema inference
- queryd: POST /query/sql returns JSON {columns, rows, row_count}
- queryd→catalogd wiring: reads all datasets, registers as named tables
- gateway: wires QueryEngine with shared store + registry
- e2e verified: SELECT *, WHERE/ORDER BY, COUNT/AVG all correct
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
