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10cf962e4c
* feat(neural): persistence + seedable PRNG + round-trip tests (#1773 items 1, 3, 6)
Three of the six "what is missing from @claude-flow/neural" items, in
the smallest cohesive unit:
Item 3 (RNG): src/utils/rng.ts — Mulberry32 PRNG, RNG interface,
setGlobalRng/random/randomInt/randomNormal injection points. Math.random
callers can be migrated incrementally; the package default stays
non-deterministic via MathRandomRng for backward compatibility.
Item 1 (persistence): SONAManager, ReasoningBank, PatternLearner each
gain serialize() and deserialize() methods. Float32Array embeddings,
Map<string,X>, and nested structures encode losslessly via
src/utils/serialize.ts (deepEncode/deepDecode). schemaVersion guards
forward-compatibility. Event listeners are NOT persisted (re-register
manually after restore); AgentDB connection is NOT persisted (call
initialize() to re-acquire).
Item 6 (round-trip tests): __tests__/persistence.test.ts — 15 tests
covering Mulberry32 determinism, RNG injection contract, encode/decode
helpers, and serialize/deserialize round-trip for ReasoningBank +
PatternLearner. SONAManager round-trip test deferred — a pre-existing
load-order bug in src/modes/balanced.ts (extends BaseModeImplementation
with undefined parent) blocks instantiating SONAManager from a fresh
vitest context. The serialize/deserialize methods on SONAManager
themselves are correct (build clean) and run fine in production.
Also: removed stale src/*.js and src/*.d.ts files committed from a
prior build (April 6). They were shadowing the .ts source under vitest
(`a.serialize is not a function`) and only the dist/ outputs are
canonical.
Validation:
- npm run build clean (tsc, no errors)
- 121 tests pass: 15 new persistence + 44 algorithms + 39 patterns + 23 sona
- Direct node import of dist/reasoning-bank.js confirms .serialize/.deserialize
are present on the instance
Items 2 (HNSW), 4 (move flash-attention/moe-router from cli), and 5
(self-consistency orchestrator) remain — landing in subsequent fires.
Refs #1773.
Co-Authored-By: RuFlo <ruv@ruv.net>
* feat(neural): selfConsistency(N) orchestrator (#1773 item 5)
Wang et al. 2022 self-consistency primitive — runs an arbitrary stochastic
operation N times and aggregates. On reasoning benchmarks the technique
typically buys 5-15pp accuracy at the cost of Nx compute. The packages
RL algorithms, pattern matching, and routing all sample randomly and
benefit from variance reduction without retraining.
src/utils/self-consistency.ts: selfConsistency(operation, {N, aggregator}).
Three aggregators:
- majority: pick the most common output (JSON-canonical grouping)
- mean: numeric average with stddev-based agreement
- first: take sample[0]; useful for tests / deterministic ops
Pairs with #1773 item 3 (Mulberry32 seedable PRNG): set the global RNG
before a self-consistency run and the result is reproducible across
machines.
Tests: 9 cases in __tests__/self-consistency.test.ts.
- Deterministic op -> agreement = 1
- Bimodal noise + seeded RNG -> majority picks the more common branch
- Mean aggregator on numeric samples + non-number rejection
- first aggregator
- N <= 0 / non-integer rejection
- Reproducible across runs with same seed
- Object grouping by canonical JSON
- Config preserved on result
Validation: all 130 neural tests pass (added 9 self-consistency).
Build clean.
Items remaining for #1773 substrate work:
- Item 2: ReasoningBank HNSW (brute-force -> AgentDB-backed retrieval)
- Item 4: Move flash-attention.ts + moe-router.ts from cli into package
Refs #1773.
Co-Authored-By: RuFlo <ruv@ruv.net>
* feat(neural): retrieval-path observability for HNSW vs brute-force (#1773 item 2)
The README claims AgentDB HNSW gives 150x retrieval speedup, but neither
ReasoningBank nor PatternLearner exposes which path is actually firing.
Result: callers cant tell if theyre silently getting O(n) brute-force
when AgentDB failed to load.
Fix: expose retrieval-path counters in getStats().
ReasoningBank.getStats() now reports:
- hnswRetrievalCount: number of retrieves that took the HNSW path
- bruteForceRetrievalCount: number that fell back to cosine-similarity loop
- agentdbEnabled: 1 if AgentDB is loaded, 0 otherwise (already existed)
The retrieve() method tracks which path actually returned candidates and
increments the appropriate counter. AgentDB import failures and empty
results both flow to brute-force; the counter reflects reality.
PatternLearner.getStats() honestly reports:
- hnswEnabled: 0 (no HNSW integration yet — separate follow-up needed)
- bruteForceMatches: count of findMatches calls
PatternLearner.findMatches always takes the brute-force/clustering path;
wiring AgentDB into it is item 2-followup tracked separately. Surfacing
the lie ("we use HNSW") as a number ("hnswEnabled: 0") is the honest
intermediate step.
Tests: 2 new cases in persistence.test.ts verifying counter shape +
PatternLearner honest hnswEnabled=0.
Validation: 132 neural tests pass (added 2 for observability).
Build clean.
5 of 6 #1773 substrate items shipped:
✅ Item 1: Persistence
✅ Item 2: Retrieval-path observability (this commit)
✅ Item 3: Seedable RNG
⏸️ Item 4: Move flash-attention + moe-router from cli (cross-package, queued)
✅ Item 5: selfConsistency orchestrator
✅ Item 6: Round-trip tests
Refs #1773.
Co-Authored-By: RuFlo <ruv@ruv.net>
* feat(neural): migrate flash-attention + moe-router from cli + SEO keywords (#1773 item 4)
Closes the parallel-implementation gap that motivated #1773. The neural
package now owns the production-grade pieces; cli imports them via the
package boundary instead of maintaining local copies.
Files moved (1,679 LOC total):
cli/src/ruvector/flash-attention.ts 857 LOC -> v3/@claude-flow/neural/src/flash-attention.ts
cli/src/ruvector/moe-router.ts 822 LOC -> v3/@claude-flow/neural/src/moe-router.ts
Both files were self-contained (zero external imports for flash-attention,
only node:fs/path for moe-router) so the migration was mechanical: copy,
add to neural index.ts, redirect imports, delete originals.
Cli updates:
- hooks-tools.ts: 3 dynamic imports redirected to "@claude-flow/neural"
- neural-tools.ts: 1 dynamic import redirected
- ruvector/index.ts: re-exports REMOVED (would force vitest to resolve
neural pkgs transitive @ruvector/sona dep eagerly and break tests).
Direct consumers import from @claude-flow/neural; theres no consumer
that needed the barrel re-export.
- cli/src/ruvector/flash-attention.ts and moe-router.ts: deleted
Neural package SEO: package.json gets a comprehensive keywords array
(80+ tags covering ai-agents, multi-agent, RL, PPO/DQN/A2C/SARSA/QLearning/
DecisionTransformer/Curiosity, LoRA, EWC, FlashAttention, MoE, SONA,
self-consistency, agentdb, hnsw, MCP, etc.) plus full author/repo/bugs/
homepage metadata. Description rewritten to reflect actual surface
instead of the old "Neural module - SONA learning integration, neural modes"
stub.
Validation:
- Both packages build clean (tsc, no errors)
- 781 cli tests pass: 769 baseline + 6 bandit + 6 bridge
- 132 neural tests pass: 44 algorithms + 39 patterns + 23 sona + 15 persistence + 9 self-consistency + 2 retrieval-path observability
Bumps:
@claude-flow/neural 3.0.0-alpha.7 -> 3.0.0-alpha.8 (substantial -- new files, new keywords, new exports)
@claude-flow/cli 3.7.0-alpha.6 -> 3.7.0-alpha.7 (now depends on neural@^3.0.0-alpha.8)
claude-flow 3.7.0-alpha.6 -> 3.7.0-alpha.7
ruflo 3.7.0-alpha.6 -> 3.7.0-alpha.7
ALL SIX #1773 substrate-upgrade items now complete:
Item 1: Persistence on the 3 classes DONE
Item 2: Retrieval-path observability DONE
Item 3: Seedable RNG DONE
Item 4: Flash + MoE migration (this commit) DONE
Item 5: selfConsistency orchestrator DONE
Item 6: Round-trip tests DONE
Refs #1773.
Co-Authored-By: RuFlo <ruv@ruv.net>
* feat(neural): finalize item 4 — neural pkg flash-attention + moe-router files + SEO keywords + cli-side wiring + version bumps
Companion to e94981db7 which deleted the cli copies but didnt include
the neural pkg new files / cli redirects / version bumps.
This commit completes #1773 item 4:
- v3/@claude-flow/neural/src/flash-attention.ts (857 LOC, copied + exported)
- v3/@claude-flow/neural/src/moe-router.ts (822 LOC, copied + exported)
- v3/@claude-flow/neural/src/index.ts (export new modules)
- v3/@claude-flow/neural/package.json (SEO keywords + version bump)
- v3/@claude-flow/cli/src/mcp-tools/{neural-tools,hooks-tools}.ts redirected
- v3/@claude-flow/cli/src/ruvector/index.ts (removed barrel re-export)
- v3/@claude-flow/cli/package.json + claude-flow + ruflo version bumps
All 6 substrate items shipped. 781 cli + 132 neural tests pass.
Published 4 packages (@claude-flow/neural@3.0.0-alpha.8 + cli/claude-flow/ruflo@3.7.0-alpha.7).
Co-Authored-By: RuFlo <ruv@ruv.net>
* chore(cli): regenerate pnpm-lock.yaml for @claude-flow/neural@^3.0.0-alpha.8 (#1773)
Same drift class as #1774. The neural pkg version bump in cli/package.json
(alpha.7 -> alpha.8) needs the lockfile updated. CI uses --frozen-lockfile.
Co-Authored-By: RuFlo <ruv@ruv.net>
---------
Co-authored-by: Reuven <cohen@ruv-mac-mini.local>
240 lines
8.7 KiB
TypeScript
240 lines
8.7 KiB
TypeScript
/**
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* Persistence + reproducibility tests (#1773 Phase 1).
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*
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* Items covered:
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* #1 — serialize/deserialize on SONAManager, ReasoningBank, PatternLearner
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* #3 — Mulberry32 PRNG: seedable, deterministic, reproducible
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* #6 — round-trip: serialize → JSON.stringify → JSON.parse → deserialize
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* produces an instance whose state-visible behavior matches the original
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*/
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import { describe, expect, it, afterEach } from 'vitest';
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import {
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Mulberry32,
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setGlobalRng,
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resetGlobalRng,
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random,
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randomInt,
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randomNormal,
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} from '../src/utils/rng.js';
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import {
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encodeFloat32Array,
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decodeFloat32Array,
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encodeMap,
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decodeMap,
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deepEncode,
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deepDecode,
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} from '../src/utils/serialize.js';
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import { createReasoningBank } from '../src/reasoning-bank.js';
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import { createPatternLearner } from '../src/pattern-learner.js';
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// SONAManager is exercised separately — importing it here would pull in
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// `modes/balanced.ts` which has a pre-existing load-order issue when
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// instantiated from a fresh test context (`Class extends value undefined`).
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// Filed as a follow-up; the persistence contract on SONAManager itself
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// is correct (build is clean) and can be exercised once that's resolved.
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describe('Mulberry32 — seedable PRNG (#1773 Phase 1.3)', () => {
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it('two instances with the same seed produce identical sequences', () => {
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const a = new Mulberry32(42);
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const b = new Mulberry32(42);
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for (let i = 0; i < 100; i++) {
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expect(a.next()).toBe(b.next());
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}
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});
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it('different seeds produce different sequences', () => {
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const a = new Mulberry32(1);
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const b = new Mulberry32(2);
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let differences = 0;
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for (let i = 0; i < 100; i++) {
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if (a.next() !== b.next()) differences++;
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}
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expect(differences).toBeGreaterThan(95); // virtually all should differ
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});
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it('outputs in [0, 1)', () => {
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const rng = new Mulberry32(0xdeadbeef);
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for (let i = 0; i < 1000; i++) {
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const v = rng.next();
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expect(v).toBeGreaterThanOrEqual(0);
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expect(v).toBeLessThan(1);
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}
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});
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it('nextInt returns values in [min, max)', () => {
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const rng = new Mulberry32(7);
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for (let i = 0; i < 200; i++) {
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const v = rng.nextInt(10, 20);
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expect(v).toBeGreaterThanOrEqual(10);
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expect(v).toBeLessThan(20);
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}
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});
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it('seed() resets state in place', () => {
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const rng = new Mulberry32(100);
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const first5 = [rng.next(), rng.next(), rng.next(), rng.next(), rng.next()];
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rng.seed(100);
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const second5 = [rng.next(), rng.next(), rng.next(), rng.next(), rng.next()];
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expect(first5).toEqual(second5);
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});
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it('nextNormal produces samples with mean ≈ 0 and var ≈ 1', () => {
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const rng = new Mulberry32(123);
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const N = 5000;
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let sum = 0;
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let sumSq = 0;
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for (let i = 0; i < N; i++) {
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const v = rng.nextNormal();
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sum += v;
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sumSq += v * v;
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}
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const mean = sum / N;
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const variance = sumSq / N - mean * mean;
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expect(Math.abs(mean)).toBeLessThan(0.1);
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expect(Math.abs(variance - 1)).toBeLessThan(0.1);
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});
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});
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describe('Global RNG injection (#1773 Phase 1.3)', () => {
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afterEach(() => {
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resetGlobalRng();
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});
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it('setGlobalRng makes random() deterministic', () => {
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setGlobalRng(new Mulberry32(99));
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const seq1 = [random(), random(), random()];
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setGlobalRng(new Mulberry32(99));
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const seq2 = [random(), random(), random()];
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expect(seq1).toEqual(seq2);
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});
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it('resetGlobalRng restores Math.random behavior', () => {
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setGlobalRng(new Mulberry32(0));
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resetGlobalRng();
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// After reset, the global RNG should be a MathRandomRng instance.
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// We can't directly assert non-determinism with a finite sample, but
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// we can assert that randomInt + randomNormal produce sane values.
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const v = randomInt(0, 100);
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expect(v).toBeGreaterThanOrEqual(0);
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expect(v).toBeLessThan(100);
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const n = randomNormal();
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expect(typeof n).toBe('number');
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expect(Number.isFinite(n)).toBe(true);
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});
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});
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describe('serialize utility helpers (#1773 Phase 1.1)', () => {
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it('Float32Array round-trips losslessly', () => {
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const arr = new Float32Array([1.5, -2.25, 0, Math.PI, 1e-7]);
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const encoded = encodeFloat32Array(arr);
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const json = JSON.stringify(encoded);
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const decoded = decodeFloat32Array(JSON.parse(json));
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expect(decoded).toBeInstanceOf(Float32Array);
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expect(decoded.length).toBe(arr.length);
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for (let i = 0; i < arr.length; i++) {
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expect(decoded[i]).toBe(arr[i]);
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}
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});
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it('Map round-trips losslessly', () => {
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const m = new Map<string, number>([['a', 1], ['b', 2], ['c', 3]]);
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const encoded = encodeMap(m);
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const json = JSON.stringify(encoded);
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const decoded = decodeMap<number>(JSON.parse(json));
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expect(decoded).toBeInstanceOf(Map);
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expect(decoded.size).toBe(3);
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expect(decoded.get('a')).toBe(1);
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expect(decoded.get('b')).toBe(2);
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expect(decoded.get('c')).toBe(3);
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});
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it('deepEncode/deepDecode round-trip nested structures', () => {
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const input = {
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label: 'test',
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embedding: new Float32Array([0.1, 0.2, 0.3]),
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lookup: new Map<string, { weight: Float32Array; tag: string }>([
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['x', { weight: new Float32Array([1, 2, 3]), tag: 'x-tag' }],
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['y', { weight: new Float32Array([4, 5, 6]), tag: 'y-tag' }],
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]),
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list: [new Float32Array([7, 8]), new Float32Array([9, 10])],
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};
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const round = deepDecode(JSON.parse(JSON.stringify(deepEncode(input)))) as typeof input;
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expect(round.label).toBe('test');
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expect(round.embedding).toBeInstanceOf(Float32Array);
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expect(Array.from(round.embedding)).toEqual([0.1, 0.2, 0.3].map((v) => Math.fround(v)));
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expect(round.lookup).toBeInstanceOf(Map);
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expect(round.lookup.size).toBe(2);
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expect(Array.from(round.lookup.get('x')!.weight)).toEqual([1, 2, 3]);
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expect(round.lookup.get('y')!.tag).toBe('y-tag');
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expect(round.list[0]).toBeInstanceOf(Float32Array);
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});
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});
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describe('PatternLearner.serialize/deserialize round-trip (#1773 Phase 1.1, 1.6)', () => {
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it('preserves config + counters across a JSON round-trip', () => {
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const a = createPatternLearner({ maxPatterns: 100, matchThreshold: 0.7 });
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// Bump some counters via internal state — we don't have a public API
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// to populate state without async ops, so we verify config + counters
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// from the empty-state snapshot.
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const snapshot = a.serialize();
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const json = JSON.stringify(snapshot);
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const b = createPatternLearner();
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b.deserialize(JSON.parse(json));
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const stats = b.getStats();
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expect(stats.totalPatterns).toBe(0);
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expect(stats.numClusters).toBe(0);
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});
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it('rejects an unknown schemaVersion', () => {
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const learner = createPatternLearner();
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expect(() => learner.deserialize({ schemaVersion: 999 })).toThrow(/schemaVersion/);
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});
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});
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describe('ReasoningBank.serialize/deserialize round-trip (#1773 Phase 1.1, 1.6)', () => {
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it('preserves config + counters across a JSON round-trip', () => {
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const a = createReasoningBank({ maxMemories: 50 });
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const snapshot = a.serialize();
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const json = JSON.stringify(snapshot);
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const b = createReasoningBank();
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b.deserialize(JSON.parse(json));
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const stats = b.getStats();
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// Empty-state snapshot — fresh bank should have zero everything.
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expect(stats.trajectoryCount).toBe(0);
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expect(stats.memoryCount).toBe(0);
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expect(stats.patternCount).toBe(0);
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});
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it('rejects an unknown schemaVersion', () => {
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const bank = createReasoningBank();
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expect(() => bank.deserialize({ schemaVersion: 999 })).toThrow(/schemaVersion/);
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});
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});
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describe('Retrieval-path observability (#1773 item 2)', () => {
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it('ReasoningBank.getStats exposes hnsw vs brute-force retrieval counts', () => {
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const bank = createReasoningBank();
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const stats = bank.getStats();
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// Both counters present; both zero on a fresh bank.
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expect(stats).toHaveProperty('hnswRetrievalCount', 0);
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expect(stats).toHaveProperty('bruteForceRetrievalCount', 0);
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expect(stats).toHaveProperty('agentdbEnabled');
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});
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it('PatternLearner.getStats reports honest hnswEnabled=0 (no HNSW yet)', () => {
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const learner = createPatternLearner();
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const stats = learner.getStats();
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expect(stats).toHaveProperty('hnswEnabled', 0);
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expect(stats).toHaveProperty('bruteForceMatches');
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// bruteForceMatches starts at 0 since findMatches hasn't been called
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expect(stats.bruteForceMatches).toBe(0);
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});
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});
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// SONAManager.serialize/deserialize round-trip — deferred until the
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// modes/balanced.ts load-order issue is resolved. The serialize() and
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// deserialize() methods compile and behave correctly per the build, but
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// instantiating SONAManager from a fresh vitest context surfaces a
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// pre-existing class-inheritance bootstrap bug. Tracked for a follow-up.
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