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git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
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/**
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* Tests for Self-Learning Generator
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*/
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import { describe, it, expect, beforeEach } from 'vitest';
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import { SelfLearningGenerator } from '../../src/generators/self-learning.js';
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import type { SelfLearningConfig, GenerateOptions } from '../../src/generators/self-learning.js';
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describe('SelfLearningGenerator', () => {
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let config: SelfLearningConfig;
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beforeEach(() => {
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config = {
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task: 'code-generation',
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learningRate: 0.1,
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iterations: 5
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};
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});
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describe('Initialization', () => {
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it('should create generator with valid config', () => {
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const generator = new SelfLearningGenerator(config);
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expect(generator).toBeDefined();
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});
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it('should accept quality threshold', () => {
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const generatorWithThreshold = new SelfLearningGenerator({
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...config,
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qualityThreshold: 0.9
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});
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expect(generatorWithThreshold).toBeDefined();
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});
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it('should accept maxAttempts option', () => {
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const generatorWithMax = new SelfLearningGenerator({
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...config,
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maxAttempts: 20
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});
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expect(generatorWithMax).toBeDefined();
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});
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});
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describe('Generation and Learning', () => {
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it('should generate output with quality improvement', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Generate a function to validate emails'
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});
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expect(result.output).toBeDefined();
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expect(result.finalQuality).toBeGreaterThan(0);
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expect(result.finalQuality).toBeLessThanOrEqual(1);
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expect(result.improvement).toBeGreaterThanOrEqual(0);
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expect(result.iterations).toBe(5);
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expect(result.metrics).toHaveLength(5);
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});
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it('should show quality improvement over iterations', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Test improvement tracking'
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});
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const firstQuality = result.metrics[0].quality;
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const lastQuality = result.metrics[result.metrics.length - 1].quality;
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// Quality should generally improve (or at least not decrease significantly)
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expect(lastQuality).toBeGreaterThanOrEqual(firstQuality * 0.95);
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expect(result.improvement).toBeDefined();
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});
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it('should track metrics for each iteration', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Track iteration metrics'
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});
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expect(result.metrics).toHaveLength(5);
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result.metrics.forEach((metric, index) => {
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expect(metric.iteration).toBe(index + 1);
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expect(metric.quality).toBeGreaterThan(0);
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expect(typeof metric.improvement).toBe('number');
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expect(Array.isArray(metric.feedback)).toBe(true);
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});
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});
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it('should apply learning rate correctly', async () => {
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const highLearningRate = new SelfLearningGenerator({
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...config,
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learningRate: 0.5,
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iterations: 3
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});
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const lowLearningRate = new SelfLearningGenerator({
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...config,
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learningRate: 0.05,
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iterations: 3
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});
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const highResult = await highLearningRate.generate({
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prompt: 'Test high learning rate'
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});
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const lowResult = await lowLearningRate.generate({
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prompt: 'Test low learning rate'
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});
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// Higher learning rate should generally lead to faster improvement
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expect(highResult.improvement).toBeDefined();
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expect(lowResult.improvement).toBeDefined();
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});
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});
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describe('Test Integration', () => {
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it('should evaluate against test cases', async () => {
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const generator = new SelfLearningGenerator(config);
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const tests = [
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(output: any) => output.content.length > 10,
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(output: any) => output.quality > 0.5,
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(output: any) => output.metadata !== undefined
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];
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const result = await generator.generate({
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prompt: 'Generate with tests',
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tests
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});
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expect(result.finalQuality).toBeGreaterThan(0);
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result.metrics.forEach(metric => {
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expect(metric.testsPassingRate).toBeDefined();
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expect(metric.testsPassingRate).toBeGreaterThanOrEqual(0);
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expect(metric.testsPassingRate).toBeLessThanOrEqual(1);
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});
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});
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it('should track test passing rate', async () => {
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const generator = new SelfLearningGenerator(config);
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const tests = [
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(output: any) => output.quality > 0.6,
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(output: any) => output.quality > 0.7
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];
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const result = await generator.generate({
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prompt: 'Track test pass rate',
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tests
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});
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// Test passing rate should be tracked for each iteration
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result.metrics.forEach(metric => {
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expect(metric.testsPassingRate).toBeGreaterThanOrEqual(0);
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expect(metric.testsPassingRate).toBeLessThanOrEqual(1);
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});
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});
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it('should handle failing tests gracefully', async () => {
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const generator = new SelfLearningGenerator(config);
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const impossibleTests = [
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() => false, // Always fails
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() => false
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];
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const result = await generator.generate({
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prompt: 'Handle test failures',
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tests: impossibleTests
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});
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expect(result.output).toBeDefined();
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expect(result.finalQuality).toBeGreaterThan(0);
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// Should complete despite test failures
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});
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});
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describe('Event Emissions', () => {
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it('should emit start event', async () => {
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const generator = new SelfLearningGenerator(config);
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let startEmitted = false;
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generator.on('start', (data) => {
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startEmitted = true;
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expect(data.task).toBe('code-generation');
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expect(data.iterations).toBe(5);
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});
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await generator.generate({ prompt: 'Test start event' });
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expect(startEmitted).toBe(true);
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});
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it('should emit improvement events', async () => {
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const generator = new SelfLearningGenerator(config);
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const improvements: any[] = [];
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generator.on('improvement', (metrics) => {
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improvements.push(metrics);
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});
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await generator.generate({ prompt: 'Test improvement events' });
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expect(improvements).toHaveLength(5);
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improvements.forEach(metric => {
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expect(metric.iteration).toBeDefined();
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expect(metric.quality).toBeDefined();
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});
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});
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it('should emit complete event', async () => {
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const generator = new SelfLearningGenerator(config);
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let completeData: any = null;
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generator.on('complete', (data) => {
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completeData = data;
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});
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await generator.generate({ prompt: 'Test complete event' });
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expect(completeData).toBeDefined();
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expect(completeData.finalQuality).toBeDefined();
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expect(completeData.improvement).toBeDefined();
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expect(completeData.iterations).toBe(5);
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});
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it('should emit threshold-reached event', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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qualityThreshold: 0.6,
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iterations: 10
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});
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let thresholdReached = false;
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generator.on('threshold-reached', (data) => {
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thresholdReached = true;
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expect(data.quality).toBeGreaterThanOrEqual(0.6);
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});
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await generator.generate({ prompt: 'Test threshold' });
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// Threshold might or might not be reached depending on random variation
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});
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});
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describe('Quality Thresholds', () => {
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it('should stop when quality threshold is reached', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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qualityThreshold: 0.7,
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iterations: 10
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});
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const result = await generator.generate({
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prompt: 'Test early stopping'
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});
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// Should stop before completing all iterations if threshold reached
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expect(result.iterations).toBeLessThanOrEqual(10);
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if (result.finalQuality >= 0.7) {
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expect(result.iterations).toBeLessThan(10);
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}
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});
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it('should use initial quality if provided', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Test initial quality',
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initialQuality: 0.8
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});
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expect(result.output).toBeDefined();
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// Improvement calculation should be based on initial quality
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});
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});
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describe('History Tracking', () => {
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it('should maintain learning history', async () => {
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const generator = new SelfLearningGenerator(config);
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await generator.generate({ prompt: 'First generation' });
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const history = generator.getHistory();
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expect(history).toHaveLength(5);
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expect(history[0].iteration).toBe(1);
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expect(history[4].iteration).toBe(5);
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});
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it('should accumulate history across multiple generations', async () => {
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const generator = new SelfLearningGenerator(config);
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await generator.generate({ prompt: 'First' });
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await generator.generate({ prompt: 'Second' });
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const history = generator.getHistory();
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expect(history.length).toBe(10); // 5 + 5 iterations
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});
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it('should reset history when reset is called', async () => {
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const generator = new SelfLearningGenerator(config);
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await generator.generate({ prompt: 'Generate before reset' });
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expect(generator.getHistory().length).toBe(5);
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generator.reset();
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expect(generator.getHistory()).toHaveLength(0);
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});
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it('should emit reset event', () => {
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const generator = new SelfLearningGenerator(config);
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let resetEmitted = false;
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generator.on('reset', () => {
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resetEmitted = true;
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});
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generator.reset();
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expect(resetEmitted).toBe(true);
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});
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});
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describe('Feedback Generation', () => {
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it('should generate relevant feedback', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Test feedback generation'
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});
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result.metrics.forEach(metric => {
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expect(Array.isArray(metric.feedback)).toBe(true);
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expect(metric.feedback.length).toBeGreaterThan(0);
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metric.feedback.forEach(fb => {
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expect(typeof fb).toBe('string');
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expect(fb.length).toBeGreaterThan(0);
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});
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});
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});
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it('should provide contextual feedback based on quality', async () => {
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const generator = new SelfLearningGenerator(config);
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const result = await generator.generate({
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prompt: 'Test contextual feedback'
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});
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// Feedback should vary based on performance
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const feedbackTypes = new Set(
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result.metrics.flatMap(m => m.feedback)
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);
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expect(feedbackTypes.size).toBeGreaterThan(0);
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});
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});
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describe('Edge Cases', () => {
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it('should handle zero iterations', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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iterations: 0
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});
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const result = await generator.generate({
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prompt: 'Test zero iterations'
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});
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expect(result.output).toBeNull();
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expect(result.metrics).toHaveLength(0);
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});
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it('should handle very high learning rate', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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learningRate: 1.0
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});
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const result = await generator.generate({
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prompt: 'Test high learning rate'
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});
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expect(result.output).toBeDefined();
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expect(result.finalQuality).toBeLessThanOrEqual(1.0);
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});
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it('should handle very low learning rate', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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learningRate: 0.001
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});
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const result = await generator.generate({
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prompt: 'Test low learning rate'
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});
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expect(result.output).toBeDefined();
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// Improvement should be minimal but positive
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});
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it('should handle single iteration', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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iterations: 1
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});
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const result = await generator.generate({
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prompt: 'Single iteration test'
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});
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expect(result.iterations).toBe(1);
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expect(result.metrics).toHaveLength(1);
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expect(result.output).toBeDefined();
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});
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});
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describe('Performance', () => {
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it('should complete within reasonable time', async () => {
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const generator = new SelfLearningGenerator(config);
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const startTime = Date.now();
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await generator.generate({
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prompt: 'Performance test'
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});
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const duration = Date.now() - startTime;
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expect(duration).toBeLessThan(2000); // Should complete in under 2 seconds
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});
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it('should handle many iterations efficiently', async () => {
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const generator = new SelfLearningGenerator({
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...config,
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iterations: 20
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});
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const startTime = Date.now();
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await generator.generate({
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prompt: 'Many iterations test'
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});
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const duration = Date.now() - startTime;
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expect(duration).toBeLessThan(5000); // Even with 20 iterations
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});
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});
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});
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