Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

This commit is contained in:
ruv
2026-02-28 14:39:40 -05:00
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/**
* @ruvector/rvf-solver — Self-learning temporal solver with AGI capabilities.
*
* Provides Thompson Sampling policy learning, ReasoningBank pattern
* distillation, and SHAKE-256 tamper-evident witness chains.
*
* @example
* ```ts
* import { RvfSolver } from '@ruvector/rvf-solver';
*
* const solver = await RvfSolver.create();
*
* // Train on 100 puzzles
* const result = solver.train({ count: 100, minDifficulty: 1, maxDifficulty: 5 });
* console.log(`Accuracy: ${(result.accuracy * 100).toFixed(1)}%`);
*
* // Run full acceptance test
* const manifest = solver.acceptance({ cycles: 3 });
* console.log(`Mode C passed: ${manifest.allPassed}`);
*
* // Get policy state
* const policy = solver.policy();
* console.log(`Context buckets: ${Object.keys(policy?.contextStats ?? {}).length}`);
*
* // Get witness chain
* const chain = solver.witnessChain();
* console.log(`Witness chain: ${chain?.length ?? 0} bytes`);
*
* solver.destroy();
* ```
*/
export { RvfSolver } from './solver';
export type {
TrainOptions,
TrainResult,
AcceptanceOptions,
AcceptanceManifest,
AcceptanceModeResult,
CycleMetrics,
PolicyState,
SkipMode,
SkipModeStats,
CompiledConfig,
} from './types';

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import type { RvfSolverWasmExports } from '../pkg/rvf_solver';
import type {
TrainOptions,
TrainResult,
AcceptanceOptions,
AcceptanceManifest,
PolicyState,
} from './types';
let wasmExports: RvfSolverWasmExports | null = null;
async function getWasm(): Promise<RvfSolverWasmExports> {
if (wasmExports) return wasmExports;
// Dynamic import to support both CJS and ESM
const initModule = await import('../pkg/rvf_solver');
const init = initModule.default || initModule;
wasmExports = await init();
return wasmExports;
}
function splitSeed(seed?: bigint | number): [number, number] {
if (seed === undefined) {
const s = BigInt(Math.floor(Math.random() * 2 ** 64));
return [Number(s & 0xFFFFFFFFn), Number((s >> 32n) & 0xFFFFFFFFn)];
}
const s = typeof seed === 'number' ? BigInt(seed) : seed;
return [Number(s & 0xFFFFFFFFn), Number((s >> 32n) & 0xFFFFFFFFn)];
}
function readJson<T>(
wasm: RvfSolverWasmExports,
handle: number,
lenFn: (h: number) => number,
readFn: (h: number, ptr: number) => number,
): T | null {
const len = lenFn(handle);
if (len <= 0) return null;
const ptr = wasm.rvf_solver_alloc(len);
if (ptr === 0) return null;
try {
readFn(handle, ptr);
const buf = new Uint8Array(wasm.memory.buffer, ptr, len);
const text = new TextDecoder().decode(buf);
return JSON.parse(text) as T;
} finally {
wasm.rvf_solver_free(ptr, len);
}
}
/**
* RVF Self-Learning Solver.
*
* Wraps the rvf-solver-wasm WASM module providing:
* - PolicyKernel with Thompson Sampling (two-signal model)
* - Context-bucketed bandit (18 buckets)
* - KnowledgeCompiler with signature-based pattern cache
* - Speculative dual-path execution
* - Three-loop adaptive solver (fast/medium/slow)
* - SHAKE-256 tamper-evident witness chain
*/
export class RvfSolver {
private handle: number;
private wasm: RvfSolverWasmExports;
private constructor(handle: number, wasm: RvfSolverWasmExports) {
this.handle = handle;
this.wasm = wasm;
}
/**
* Create a new solver instance.
* Initializes the WASM module on first call.
*/
static async create(): Promise<RvfSolver> {
const wasm = await getWasm();
const handle = wasm.rvf_solver_create();
if (handle < 0) {
throw new Error('Failed to create solver instance (max 8 concurrent instances)');
}
return new RvfSolver(handle, wasm);
}
/**
* Train the solver on generated puzzles.
*
* Uses the three-loop architecture:
* - Fast loop: constraint propagation solver
* - Medium loop: PolicyKernel skip-mode selection
* - Slow loop: KnowledgeCompiler pattern distillation
*/
train(options: TrainOptions): TrainResult {
const [seedLo, seedHi] = splitSeed(options.seed);
const correct = this.wasm.rvf_solver_train(
this.handle,
options.count,
options.minDifficulty ?? 1,
options.maxDifficulty ?? 10,
seedLo,
seedHi,
);
if (correct < 0) {
throw new Error('Training failed: invalid handle');
}
const result = readJson<TrainResult>(
this.wasm,
this.handle,
(h) => this.wasm.rvf_solver_result_len(h),
(h, p) => this.wasm.rvf_solver_result_read(h, p),
);
return result ?? {
trained: options.count,
correct,
accuracy: correct / options.count,
patternsLearned: 0,
};
}
/**
* Run the full acceptance test with training/holdout cycles.
*
* Runs all three ablation modes:
* - Mode A: Fixed heuristic policy
* - Mode B: Compiler-suggested policy
* - Mode C: Learned Thompson Sampling policy
*
* Returns the full manifest with per-cycle metrics and witness chain.
*/
acceptance(options?: AcceptanceOptions): AcceptanceManifest {
const opts = options ?? {};
const [seedLo, seedHi] = splitSeed(opts.seed);
const status = this.wasm.rvf_solver_acceptance(
this.handle,
opts.holdoutSize ?? 50,
opts.trainingPerCycle ?? 200,
opts.cycles ?? 5,
opts.stepBudget ?? 500,
seedLo,
seedHi,
);
if (status < 0) {
throw new Error('Acceptance test failed: invalid handle');
}
const manifest = readJson<any>(
this.wasm,
this.handle,
(h) => this.wasm.rvf_solver_result_len(h),
(h, p) => this.wasm.rvf_solver_result_read(h, p),
);
if (!manifest) {
throw new Error('Failed to read acceptance manifest');
}
return {
version: manifest.version,
modeA: manifest.mode_a,
modeB: manifest.mode_b,
modeC: manifest.mode_c,
allPassed: manifest.all_passed,
witnessEntries: manifest.witness_entries,
witnessChainBytes: manifest.witness_chain_bytes,
};
}
/**
* Get the current policy state (Thompson Sampling parameters,
* context buckets, KnowledgeCompiler cache stats).
*/
policy(): PolicyState | null {
return readJson<PolicyState>(
this.wasm,
this.handle,
(h) => this.wasm.rvf_solver_policy_len(h),
(h, p) => this.wasm.rvf_solver_policy_read(h, p),
);
}
/**
* Get the raw SHAKE-256 witness chain bytes.
*
* The witness chain is 73 bytes per entry and provides
* tamper-evident proof of all training/acceptance operations.
* Verifiable using `rvf_witness_verify` from `@ruvector/rvf-wasm`.
*/
witnessChain(): Uint8Array | null {
const len = this.wasm.rvf_solver_witness_len(this.handle);
if (len <= 0) return null;
const ptr = this.wasm.rvf_solver_alloc(len);
if (ptr === 0) return null;
try {
this.wasm.rvf_solver_witness_read(this.handle, ptr);
const buf = new Uint8Array(this.wasm.memory.buffer, ptr, len);
// Copy to avoid referencing WASM memory after free
return new Uint8Array(buf);
} finally {
this.wasm.rvf_solver_free(ptr, len);
}
}
/**
* Destroy the solver instance and free WASM resources.
*/
destroy(): void {
if (this.handle > 0) {
this.wasm.rvf_solver_destroy(this.handle);
this.handle = 0;
}
}
}

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/** Configuration for solver training. */
export interface TrainOptions {
/** Number of puzzles to generate and solve. */
count: number;
/** Minimum puzzle difficulty (1-10). Default: 1. */
minDifficulty?: number;
/** Maximum puzzle difficulty (1-10). Default: 10. */
maxDifficulty?: number;
/** RNG seed (BigInt or number). Default: random. */
seed?: bigint | number;
}
/** Result of a training run. */
export interface TrainResult {
/** Number of puzzles trained on. */
trained: number;
/** Number solved correctly. */
correct: number;
/** Accuracy (correct / trained). */
accuracy: number;
/** Number of patterns learned by the ReasoningBank. */
patternsLearned: number;
}
/** Configuration for acceptance testing. */
export interface AcceptanceOptions {
/** Number of holdout puzzles per cycle. Default: 50. */
holdoutSize?: number;
/** Number of training puzzles per cycle. Default: 200. */
trainingPerCycle?: number;
/** Number of train/test cycles. Default: 5. */
cycles?: number;
/** Maximum steps per puzzle. Default: 500. */
stepBudget?: number;
/** RNG seed (BigInt or number). Default: random. */
seed?: bigint | number;
}
/** Per-cycle metrics from an acceptance mode. */
export interface CycleMetrics {
cycle: number;
accuracy: number;
costPerSolve: number;
}
/** Result of a single acceptance mode (A, B, or C). */
export interface AcceptanceModeResult {
passed: boolean;
finalAccuracy: number;
cycles: CycleMetrics[];
}
/** Full acceptance test manifest. */
export interface AcceptanceManifest {
version: number;
/** Mode A: fixed heuristic policy. */
modeA: AcceptanceModeResult;
/** Mode B: compiler-suggested policy. */
modeB: AcceptanceModeResult;
/** Mode C: learned Thompson Sampling policy. */
modeC: AcceptanceModeResult;
/** True if Mode C passed (the full learned mode). */
allPassed: boolean;
/** Number of witness entries in the chain. */
witnessEntries: number;
/** Total witness chain bytes. */
witnessChainBytes: number;
}
/** Skip mode for the PolicyKernel. */
export type SkipMode = 'none' | 'weekday' | 'hybrid';
/** Per-arm stats from Thompson Sampling. */
export interface SkipModeStats {
attempts: number;
successes: number;
totalSteps: number;
alphaSafety: number;
betaSafety: number;
costEma: number;
earlyCommitWrongs: number;
}
/** Compiled knowledge entry. */
export interface CompiledConfig {
maxSteps: number;
avgSteps: number;
observations: number;
expectedCorrect: boolean;
hitCount: number;
counterexampleCount: number;
compiledSkip: SkipMode;
}
/** Full policy state from the PolicyKernel. */
export interface PolicyState {
contextStats: Record<string, Record<string, SkipModeStats>>;
earlyCommitPenalties: number;
earlyCommitsTotal: number;
earlyCommitsWrong: number;
prepass: string;
speculativeAttempts: number;
speculativeArm2Wins: number;
}