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superseded during the 8.0 rework and never wired into init(): it emitted settings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

157 lines
5.1 KiB
Markdown

---
title: Zero Configuration
slug: concepts/zero-config
public: false
category: concepts
template: concept
order: 3
description: Brainy auto-detects storage, initializes embeddings, and builds indexes — no configuration required. Works in Node.js and Bun (server-only since 8.0).
next:
- 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](../api/README.md#configuration).
## 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
```typescript
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](../concepts/storage-adapters.md) for the full contract.
```typescript
// 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.
```typescript
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.
```typescript
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:
```typescript
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:
```typescript
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](../api/README.md#configuration) for the complete option
list.
## See Also
- [Architecture Overview](./overview.md)
- [Storage Adapters](../concepts/storage-adapters.md)
- [Scaling Guide](../SCALING.md)
- [API Reference](../api/README.md)