brainy/docs/architecture/zero-config.md
David Snelling 35b9d7ef43 refactor(8.0)!: remove orphaned zero-config subsystem + dead cloud/progressive-init storage vestige
The old config-generation subsystem (src/config/ + autoConfiguration.ts) was
superseded during the 8.0 rework and never wired into init(): it emitted settings
for a partitioning subsystem that no longer exists and probed deleted cloud env
vars. The live zero-config path is inline — recall preset → HNSW knobs, storage
auto-detect, auto persistMode, container-memory-aware cache sizing.

The storage progressive-init / cloud-detection cluster was equally dead after the
cloud adapters were dropped: isCloudStorage() is permanently false (no overriders),
scheduleBackgroundInit/runBackgroundInit were never called (the latter an empty
body), initMode was never assigned, and Brainy.isFullyInitialized()/
awaitBackgroundInit() were always-trivial with zero callers. scheduleCountPersist()
collapses to its only-ever-taken immediate write-through path.

Removed:
- src/config/{index,zeroConfig,storageAutoConfig,modelAutoConfig,sharedConfigManager}.ts
- src/utils/autoConfiguration.ts + the inert BrainyZeroConfig export
- Brainy.isFullyInitialized()/awaitBackgroundInit() (+ BrainyInterface decls)
- InitMode type, isCloudStorage/detectCloudEnvironment/resolveInitMode,
  scheduleBackgroundInit/runBackgroundInit/ensureValidatedForWrite and their state
- Dead cloud env-var probes (K_SERVICE/K_REVISION/AWS_LAMBDA_FUNCTION_NAME/
  FUNCTIONS_TARGET/AZURE_FUNCTIONS_ENVIRONMENT)

Kept (verified live): production-detection logging (environment.ts), container-
memory cache sizing (memoryDetection/paramValidation), on-disk hash bucketing
(sharding.ts).

Docs: scrubbed deleted-subsystem references (JS quantization knobs, cloud/OPFS
adapters, partitioning, old zero-config API) across 14 files; deleted two wholly-
obsolete feature docs (complete-feature-list, v3-features); rewrote
architecture/zero-config for 8.0.

~3,700 LOC removed. Build clean; 1392 unit + 24 db-mvcc green.
2026-06-15 11:11:21 -07:00

5.1 KiB

title slug public category template order description next
Zero Configuration concepts/zero-config false concepts concept 3 Brainy auto-detects storage, initializes embeddings, and builds indexes — no configuration required. Works in Node.js and Bun (server-only since 8.0).
getting-started/installation
guides/storage-adapters

Zero Configuration & Auto-Adaptation

"Zero config by default, fully tunable when you need it." Construct a Brainy() with no options and it picks sensible, environment-aware defaults. Every default below is overridable through the constructor — see the API Reference.

Overview

Brainy 8.0 is server-only (Node.js 22+ / Bun). With no configuration it:

  • selects a storage adapter from the runtime,
  • initializes the embedding model (all-MiniLM-L6-v2, 384 dimensions),
  • builds and maintains the metadata, graph, and vector indexes,
  • sizes its caches and write buffers to the detected memory budget,
  • chooses a persistence mode that matches the storage backend, and
  • quiets its own logging when it detects a production environment.

There is no public config-generation function — adaptation happens inside the constructor and init().

Instant Start

import { Brainy } from '@soulcraft/brainy'

// That's it. No config needed.
const brain = new Brainy()
await brain.init()

await brain.add({ data: 'First entity', type: 'concept' })
const results = await brain.find('first')

What Auto-Adaptation Covers

1. Storage auto-detection

With no storage option, Brainy uses type: 'auto':

  • Filesystem when running on a runtime with a writable Node filesystem and a resolvable root directory. This is the default for typical Node/Bun servers and persists across restarts.
  • In-memory otherwise (no filesystem access, or an explicit memory request). Fast, zero I/O, discarded on process exit — ideal for tests and ephemeral caches.

8.0 ships exactly two storage adapters — memory and filesystem — plus the auto selector that resolves to one of them. See Storage Adapters for the full contract.

// Explicit override when you want a specific root
const brain = new Brainy({
  storage: { type: 'filesystem', rootDirectory: './brainy-data' }
})

2. HNSW quality from the recall preset

Vector-index quality comes from a single preset rather than hand-tuned graph parameters. config.vector.recall accepts 'fast', 'balanced', or 'accurate' and defaults to 'balanced'. The preset maps internally to the HNSW construction and search parameters (M / efConstruction / efSearch), so you trade recall against latency with one knob instead of three.

const brain = new Brainy({
  vector: { recall: 'fast' } // favor latency over recall
})

The default JS index is JsHnswVectorIndex. An optional native acceleration provider (the @soulcraft/cortex package) can replace it with a higher-performing implementation; the public knobs stay the same. Quantization and other index-internal acceleration are the native provider's concern, not a Brainy configuration option.

3. Persistence mode follows the backend

config.vector.persistMode accepts 'immediate' or 'deferred'. Left unset, Brainy chooses for you:

  • Immediate on filesystem storage, so the index file stays in lock-step with the data and survives a crash.
  • Deferred on in-memory storage, where there is nothing durable to sync to, so writes are batched for throughput.
const brain = new Brainy({
  vector: { persistMode: 'deferred' } // batch persistence for write-heavy loads
})

4. Memory-aware cache and buffer sizing

Brainy reads the container's memory budget — CLOUD_RUN_MEMORY, MEMORY_LIMIT, or the cgroup memory limit when running in a container — and sizes its read caches and write buffers to fit. On a small instance it stays conservative; on a large one it uses more of the available headroom. Query-result limits are capped against the same budget (roughly 25 KB per result) to keep a single oversized query from exhausting memory.

You can pin the cache explicitly:

const brain = new Brainy({
  cache: { maxSize: 10000, ttl: 3_600_000 }
})

5. Logging quiets in production

Brainy detects production-style environments (for example NODE_ENV set to a non-development value) and reduces its own log verbosity automatically. This is logging-only behavior — it does not change indexing, storage, or query results.

Configuration Override

Zero-config is the default, not a ceiling. Every adaptive decision above has an explicit constructor option:

const brain = new Brainy({
  storage: { type: 'filesystem', rootDirectory: '/var/lib/brainy' },
  vector: {
    recall: 'accurate',
    persistMode: 'immediate'
  },
  cache: { maxSize: 50000, ttl: 600_000 }
})

await brain.init()

See the API Reference for the complete option list.

See Also