David Snelling
6baa4d7f6c
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10.4.11 gave shutdown one owner and one path — close() — and wired all three
process listeners to it. That is right for SIGTERM and SIGINT. It is wrong for
'beforeExit', which Node emits whenever the event loop has no REF'd work left:
not when the process is ending, and with no signal involved. A healthy script
reaches that state routinely, because this engine unref's its idle and cadence
timers ("an idle brain costs nothing"), so a script awaiting anything those
timers drive is, for that instant, a process with no ref'd work and an open
brain.
MEASURED on the 11.1 rehearsal lane against a copy of a real store: after the
heal phase the log printed "Shutdown signal received - flushing pending
data..." and "Flushed successfully (1 instance)" with no signal ever sent, and
the script's very next add() threw "Brainy instance is not initialized: it was
closed via close(). Create a new instance." The engine had closed a live brain
out from under a running script.
The beforeExit listener now runs its own pass, which closes nothing,
deregisters nothing, releases no writer lock, and never force-exits: it runs
flush() — the engine's own non-closing durability door — on each live brain and
leaves every one of them open and usable. flush() persists derived state only
(count ledger, projections, generation counter, aggregation, entity-tree
stamp); the clean-shutdown marker is generationStore.close()'s word about
itself, reached only from close(). Running it concurrently with live writes is
the engine's ordinary steady state — noteWriteForPersistence() kicks the same
call off an unref'd timer on every busy brain — and it is single-flight, so
there is no new race. A throw is reported per instance and the pass continues:
canonical data is durable at ack via the fact log, so a failed derived-state
flush costs the next open a rebuild, never the caller their brain.
The listener is no longer self-deregistered. It does not need to be: a flush on
a clean brain schedules no I/O, so the emit after it does no event-loop work
and the process exits on its own. A one-shot listener spent on a spurious
mid-script drain would leave the genuine end-of-script drain with nothing. The
drained-loop notice is printed once per registration cycle, because a
console.log to a pipe is itself event-loop work.
exitIfSoleShutdownOwner() stays on the signal path alone, and its contract now
says so: beforeExit suppresses no default behaviour, so exiting from it would
end a live script at code 0 mid-work.
THE NAMED TRADE: a script that opens a brain and never closes it now exits with
its writer lock still on disk and no clean-shutdown marker, so its next open
overwrites a stale lock and folds the log. That is the honest cost of never
closing, and the narration names the cure. Closing a live brain to avoid it was
the worse half of the trade.
Pins: tests/integration/beforeexit-never-closes.test.ts — a script that drains
the loop with a brain open keeps a working brain (add + find succeed, the lock
is still held, the process still exits 0), the pass flushed and wrote neither
of close()'s markers, and repeated drains are idempotent. Both cases fail on
10.4.11's handler with the exact production shape ("add() after the drain
failed", "pass 1 closed the brain"). Re-run green: shutdown-single-owner,
writer-lock-clean-close, idle-costs-nothing, shutdown-hooks-lifecycle.
docs/concepts/multi-process.md no longer claims beforeExit releases the lock.
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| .. | ||
| api | ||
| architecture | ||
| concepts | ||
| guides | ||
| operations | ||
| vfs | ||
| ADR-001-generational-mvcc.md | ||
| api-contract.json | ||
| BATCHING.md | ||
| DATA_MODEL.md | ||
| DEVELOPER_LEARNING_PATH.md | ||
| eli5.md | ||
| FIND_SYSTEM.md | ||
| MIGRATION-V3-TO-V4.md | ||
| neural-extraction.md | ||
| path-registry.md | ||
| performance-envelopes.md | ||
| PERFORMANCE.md | ||
| PLUGINS.md | ||
| PRODUCTION_SERVICE_ARCHITECTURE.md | ||
| QUERY_OPERATORS.md | ||
| README.md | ||
| RELEASE-GUIDE.md | ||
| SCALING.md | ||
| STAGE3-CANONICAL-TAXONOMY.md | ||
| transactions.md | ||
| troubleshooting.md | ||
| universal-display-augmentation.md | ||
Brainy Documentation
The multi-dimensional AI database with Triple Intelligence — vector search, graph traversal, and metadata filtering in one unified API.
Quick Start
import { Brainy, NounType, VerbType } from '@soulcraftlabs/brainy'
const brain = new Brainy()
await brain.init()
// Add entities — data is embedded for semantic search, metadata is indexed for filtering
const id = await brain.add({
data: 'Revolutionary AI Breakthrough',
type: NounType.Document,
metadata: { category: 'technology', rating: 4.8 }
})
// Search with Triple Intelligence
const results = await brain.find({
query: 'artificial intelligence', // Semantic search (on data)
where: { rating: { greaterThan: 4.0 } }, // Metadata filter
connected: { from: authorId, depth: 2 } // Graph traversal
})
Core Documentation
| Document | Description |
|---|---|
| API Reference | Complete API documentation — start here |
| Data Model | Entity structure, data vs metadata, storage fields |
| Query Operators | All BFO operators with examples and indexed/in-memory matrix |
| Find System | Natural language find() and hybrid search details |
| Consistency Model | The Db API guarantees — snapshot isolation, atomic transactions, time travel |
Architecture
| Document | Description |
|---|---|
| Architecture Overview | High-level system design |
| Triple Intelligence | Vector + Graph + Metadata unified query |
| Noun-Verb Taxonomy | 42 nouns + 127 verbs type system |
| Stage 3 Canonical Taxonomy | Complete type reference |
| Storage Architecture | Storage adapters and optimization |
| Index Architecture | Vector, Graph, and Metadata indexing |
| Zero Configuration | Auto-adapts to any environment |
Virtual Filesystem (VFS)
| Document | Description |
|---|---|
| VFS Quick Start | Get started in 30 seconds |
| VFS Core | Core concepts and architecture |
| VFS API Guide | Complete VFS API reference |
| Common Patterns | VFS usage patterns |
See vfs/ for the complete VFS documentation set.
Guides
| Document | Description |
|---|---|
| Import Anything | CSV, Excel, PDF, URL imports |
| Snapshots & Time Travel | Backups, restore, what-if analysis, audit trails |
| Natural Language | Query in plain English |
| Neural API | AI-powered features |
| Enterprise for Everyone | No limits, no tiers |
| Framework Integration | React, Vue, Angular, Svelte |
Storage & Deployment
| Document | Description |
|---|---|
| Storage Architecture | Filesystem and memory adapters, on-disk artifact layout, operator-layer backup |
| Capacity Planning | Scale to millions of entities |
Plugins
| Document | Description |
|---|---|
| Plugins | Plugin system overview — providers, plugins config, brain.use() |
Performance & Scaling
| Document | Description |
|---|---|
| Performance | Optimization techniques |
| Scaling | Scale to billions of entities |
| Batching | Batch operations guide |
Migration & Reference
| Document | Description |
|---|---|
| v3 to v4 Migration | Upgrade guide |
| Release Guide | How to release new versions |
| Production Architecture | Ops reference |
Internal
| Document | Description |
|---|---|
| Audit Report | Feature audit |
| Honest Status | Actual implementation status |
License
Brainy is MIT licensed. See LICENSE for details.