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107 lines
5.0 KiB
TypeScript
107 lines
5.0 KiB
TypeScript
/**
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* Deep validation: SONA optimizer, embeddings transparency, neural tools
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*/
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import { describe, it, expect, beforeEach } from 'vitest';
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import { SONAOptimizer, resetSONAOptimizer } from '../src/memory/sona-optimizer.js';
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import { generateEmbedding } from '../src/ruvector/vector-db.js';
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// ---------- SONA Optimizer ----------
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describe('SONA Optimizer', () => {
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let sona: SONAOptimizer;
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beforeEach(() => {
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resetSONAOptimizer();
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sona = new SONAOptimizer({ persistencePath: '/tmp/sona-test-' + Date.now() + '.json' });
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});
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it('1: getRoutingSuggestion() is async and returns a result with source field', async () => {
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const result = await sona.getRoutingSuggestion('implement a login page');
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expect(result).toBeDefined();
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expect(typeof result.source).toBe('string');
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});
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it('2: source field is one of the allowed values', async () => {
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const allowed = ['sona-native', 'sona-pattern', 'q-learning', 'sona-keyword', 'default'];
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const result = await sona.getRoutingSuggestion('write unit tests for the api');
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expect(allowed).toContain(result.source);
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});
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it('3: keyword routing maps "implement authentication" to coder or security-architect', async () => {
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const result = await sona.getRoutingSuggestion('implement authentication');
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// "implement" is a coder keyword, "authentication" is security-architect
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expect(['coder', 'security-architect']).toContain(result.agent);
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expect(result.source).toMatch(/sona-keyword|default/);
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});
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it('4: loadSonaEngine() gracefully handles missing @ruvector/sona', async () => {
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// With no @ruvector/sona installed, should still return a result via keyword/default
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const result = await sona.getRoutingSuggestion('design a database schema');
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expect(['sona-keyword', 'default', 'sona-pattern']).toContain(result.source);
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expect(result.agent).toBeDefined();
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});
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it('5: return type has agentType-equivalent, confidence, source, reasoning-equivalent fields', async () => {
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const result = await sona.getRoutingSuggestion('optimize performance of the cache layer');
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// RoutingSuggestion uses `agent` (not `agentType`) and `alternatives` (not `reasoning`)
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expect(typeof result.agent).toBe('string');
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expect(typeof result.confidence).toBe('number');
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expect(typeof result.source).toBe('string');
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expect(Array.isArray(result.alternatives)).toBe(true);
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expect(typeof result.usedQLearning).toBe('boolean');
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});
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});
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// ---------- Embeddings Transparency ----------
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describe('Embeddings Transparency (vector-db)', () => {
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it('6: generateHashEmbedding via generateEmbedding returns Float32Array of length 384', () => {
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// generateEmbedding defaults to 768, but we request 384
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const emb = generateEmbedding('hello world', 384);
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expect(emb).toBeInstanceOf(Float32Array);
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expect(emb.length).toBe(384);
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});
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it('7: hash embedding is deterministic (same input -> same output)', () => {
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const a = generateEmbedding('deterministic test input', 384);
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const b = generateEmbedding('deterministic test input', 384);
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expect(Array.from(a)).toEqual(Array.from(b));
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});
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it('8: hash embedding has _warning property (non-enumerable) on fallback', () => {
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const emb = generateEmbedding('test transparency', 384);
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// _warning is defined as non-enumerable
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const descriptor = Object.getOwnPropertyDescriptor(emb, '_warning');
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expect(descriptor).toBeDefined();
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expect(descriptor!.enumerable).toBe(false);
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expect(typeof descriptor!.value).toBe('string');
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expect(descriptor!.value).toContain('hash-based');
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});
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});
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// ---------- Neural Tools ----------
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describe('Neural Tools (neural-tools)', () => {
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it('9: generateEmbedding function exists in neural-tools and is callable', async () => {
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// neural-tools has a module-scoped generateEmbedding; we test it indirectly
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// by importing the neuralTools array and calling the neural_predict handler
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const { neuralTools } = await import('../src/mcp-tools/neural-tools.js');
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const predictTool = neuralTools.find(t => t.name === 'neural_predict');
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expect(predictTool).toBeDefined();
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// Call it — should succeed without real embeddings
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const result = await predictTool!.handler({ input: 'test embedding generation' });
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expect(result).toHaveProperty('embeddingDims', 384);
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});
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it('10: embeddingServiceName reflects active provider (real or hash-fallback)', async () => {
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const { neuralTools } = await import('../src/mcp-tools/neural-tools.js');
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const statusTool = neuralTools.find(t => t.name === 'neural_status');
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expect(statusTool).toBeDefined();
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const result = await statusTool!.handler({});
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const provider = (result as any).embeddingProvider as string;
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// Must be a non-empty string indicating which embedding backend is active
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expect(typeof provider).toBe('string');
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expect(provider.length).toBeGreaterThan(0);
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// Must match one of the known provider tiers or fallback
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const knownProviders = /agentic-flow|onnx|mock|hash|fallback|reasoningbank|none/i;
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expect(provider).toMatch(knownProviders);
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});
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});
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