Add Vitest test suite with 184 tests covering all game engine systems
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
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import { describe, it, expect, beforeEach, afterEach } from 'vitest';
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import {
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createTestState,
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createTestTrainingPipeline,
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createTestBaseModel,
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createTestModelFamily,
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createSeededRNG,
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} from '../__test-utils__';
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import { processModels } from './modelSystem';
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import {
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POINT_RELEASE_CAPABILITY_GAIN,
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VRAM_REQUIREMENTS_BY_GENERATION,
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} from '@ai-tycoon/shared';
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import type { ResearchBonuses } from './researchBonuses';
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const rng = createSeededRNG(42);
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beforeEach(() => rng.install());
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afterEach(() => rng.uninstall());
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/** Helper: build state with a single active pipeline, talent, and compute */
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function stateWithPipeline(
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pipelineOverrides?: Parameters<typeof createTestTrainingPipeline>[0],
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familyOverrides?: Parameters<typeof createTestModelFamily>[0],
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stateOverrides?: Parameters<typeof createTestState>[0],
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) {
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const family = createTestModelFamily({
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id: 'fam-1',
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name: 'Test',
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baseModelIds: [],
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variants: [],
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generation: 1,
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createdAtTick: 0,
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...familyOverrides,
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});
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const pipeline = createTestTrainingPipeline({
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familyId: 'fam-1',
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...pipelineOverrides,
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});
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return createTestState({
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models: {
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activeTrainingPipelines: [pipeline],
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families: [family],
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},
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compute: { totalTrainingFlops: 1e15, trainingAllocation: 0.5, totalVramGB: 256 },
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talent: {
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departments: {
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research: { headcount: 5, effectiveness: 0.5 },
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engineering: { headcount: 5, effectiveness: 0.5 },
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},
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},
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...stateOverrides,
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});
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}
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function defaultResearchBonuses(overrides?: Partial<ResearchBonuses>): ResearchBonuses {
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return {
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energyCostReduction: 0,
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pipelineSpeedBonus: 0,
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trainingSpeedBonus: 0,
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inferenceEfficiencyBonus: 0,
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tokensPerFlopBonus: 0,
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dataQualityBonus: 0,
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sdkCoverageBonus: 0,
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globalCapabilityBonus: 0,
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reasoningBonus: 0,
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codingBonus: 0,
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creativeBonus: 0,
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multimodalBonus: 0,
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agentsBonus: 0,
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reputationBonus: 0,
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safetyBonus: 0,
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autoScalingBonus: 0,
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...overrides,
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};
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}
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// ---------- Pipeline stage progression ----------
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describe('processModels', () => {
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describe('pipeline stage progression', () => {
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it('increments pretraining progressTicks each tick', () => {
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const state = stateWithPipeline({
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currentStage: 'pretraining',
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stages: {
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pretraining: { progressTicks: 0, totalTicks: 1000 },
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},
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});
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const result = processModels(state);
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const pre = result.modelsState.activeTrainingPipelines[0].stages.pretraining;
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expect(pre.progressTicks).toBeGreaterThan(0);
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});
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it('applies speed formula: (1 + talent*0.15) * (1 + trainingSpeedBonus)', () => {
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// researcher boost = 5*0.5 = 2.5, engineer boost = 5*0.5 = 2.5
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// speedMultiplier = (1 + (2.5+2.5)*0.15) * (1 + 0.2) = (1 + 0.75) * 1.2 = 1.75 * 1.2 = 2.1
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const state = stateWithPipeline({
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currentStage: 'pretraining',
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stages: {
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pretraining: { progressTicks: 0, totalTicks: 10000 },
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},
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});
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const bonuses = defaultResearchBonuses({ trainingSpeedBonus: 0.2 });
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const result = processModels(state, bonuses);
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const pre = result.modelsState.activeTrainingPipelines[0].stages.pretraining;
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// With seeded RNG, events may or may not occur. The base progress without events = 2.1
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// We check it's approximately right (events can add delays).
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// Use a range to account for possible training events with the seeded rng.
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expect(pre.progressTicks).toBeGreaterThan(0);
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expect(pre.progressTicks).toBeLessThanOrEqual(2.1);
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});
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it('applies MoE 0.8 speed penalty during pretraining', () => {
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const denseState = stateWithPipeline({
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currentStage: 'pretraining',
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architecture: { type: 'dense', totalParameters: 7e9, activeParameters: 7e9, contextWindow: 8192, vocabularySize: 32000 },
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stages: { pretraining: { progressTicks: 0, totalTicks: 10000 } },
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});
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const moeState = stateWithPipeline({
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currentStage: 'pretraining',
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architecture: { type: 'moe', totalParameters: 7e9, activeParameters: 2e9, contextWindow: 8192, vocabularySize: 32000, expertCount: 8, expertTopK: 2 },
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stages: { pretraining: { progressTicks: 0, totalTicks: 10000 } },
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});
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const denseResult = processModels(denseState);
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const moeResult = processModels(moeState);
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const densePre = denseResult.modelsState.activeTrainingPipelines[0].stages.pretraining;
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const moePre = moeResult.modelsState.activeTrainingPipelines[0].stages.pretraining;
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// MoE should be slower (0.8x of dense progress, modulo random events)
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// Both might have events; we just check MoE is not faster than dense without events
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// dense speed = 1.75, moe speed = 1.75 * 0.8 = 1.4
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// Use a threshold: moe progress should be less than dense progress (approximately)
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expect(moePre.progressTicks).toBeLessThanOrEqual(densePre.progressTicks);
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});
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it('transitions from pretraining to sft when progressTicks >= totalTicks', () => {
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const state = stateWithPipeline({
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currentStage: 'pretraining',
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stages: {
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pretraining: { progressTicks: 999, totalTicks: 1000 },
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},
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});
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.stages.pretraining.isComplete).toBe(true);
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expect(pipeline.currentStage).toBe('sft');
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});
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it('generates "Pre-training Complete" notification on pretraining completion', () => {
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const state = stateWithPipeline({
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currentStage: 'pretraining',
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stages: {
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pretraining: { progressTicks: 999, totalTicks: 1000 },
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},
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});
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const result = processModels(state);
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const pretrainNotif = result.notifications.find(n => n.title === 'Pre-training Complete');
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expect(pretrainNotif).toBeDefined();
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expect(pretrainNotif!.type).toBe('info');
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});
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it('transitions from sft to alignment when progressTicks >= totalTicks', () => {
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const state = stateWithPipeline({
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currentStage: 'sft',
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { progressTicks: 99, totalTicks: 100 },
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},
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});
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.stages.sft.isComplete).toBe(true);
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expect(pipeline.currentStage).toBe('alignment');
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});
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it('generates "SFT Complete" notification on sft completion', () => {
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const state = stateWithPipeline({
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currentStage: 'sft',
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { progressTicks: 99, totalTicks: 100 },
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},
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});
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const result = processModels(state);
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const sftNotif = result.notifications.find(n => n.title === 'SFT Complete');
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expect(sftNotif).toBeDefined();
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expect(sftNotif!.type).toBe('info');
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});
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it('creates a BaseModel when alignment completes', () => {
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const state = stateWithPipeline({
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currentStage: 'alignment',
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { specializations: ['general'], progressTicks: 100, totalTicks: 100, isComplete: true },
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alignment: { progressTicks: 79, totalTicks: 80 },
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},
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});
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.stages.alignment.isComplete).toBe(true);
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expect(pipeline.status).toBe('completed');
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expect(result.completedModels).toHaveLength(1);
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expect(result.modelsState.baseModels.length).toBeGreaterThanOrEqual(1);
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});
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it('adds completed model to the family baseModelIds', () => {
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const state = stateWithPipeline({
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currentStage: 'alignment',
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { specializations: ['general'], progressTicks: 100, totalTicks: 100, isComplete: true },
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alignment: { progressTicks: 79, totalTicks: 80 },
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},
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});
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const result = processModels(state);
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const family = result.modelsState.families.find(f => f.id === 'fam-1');
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expect(family).toBeDefined();
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expect(family!.baseModelIds.length).toBe(1);
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expect(family!.baseModelIds[0]).toBe(result.completedModels[0].id);
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});
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it('progresses SFT stage without MoE penalty', () => {
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// SFT uses plain speedMultiplier without MoE penalty
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const state = stateWithPipeline({
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currentStage: 'sft',
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architecture: { type: 'moe', totalParameters: 7e9, activeParameters: 2e9, contextWindow: 8192, vocabularySize: 32000, expertCount: 8, expertTopK: 2 },
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { progressTicks: 0, totalTicks: 1000 },
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},
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});
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const result = processModels(state);
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const sft = result.modelsState.activeTrainingPipelines[0].stages.sft;
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// speedMultiplier = (1 + (2.5+2.5)*0.15) * 1 = 1.75
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// SFT does not apply MoE penalty
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expect(sft.progressTicks).toBeCloseTo(1.75, 1);
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});
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});
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// ---------- VRAM stalling ----------
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describe('VRAM stalling', () => {
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it('stalls pipeline when VRAM is insufficient for generation', () => {
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const requiredVram = VRAM_REQUIREMENTS_BY_GENERATION[1]; // 48 GB
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const state = stateWithPipeline(
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{ currentStage: 'pretraining', stages: { pretraining: { progressTicks: 0, totalTicks: 1000 } } },
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{ generation: 1 },
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{ compute: { totalVramGB: requiredVram - 1 } },
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);
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.status).toBe('stalled');
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});
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it('does not stall when VRAM is sufficient', () => {
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const requiredVram = VRAM_REQUIREMENTS_BY_GENERATION[1]; // 48 GB
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const state = stateWithPipeline(
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{ currentStage: 'pretraining', stages: { pretraining: { progressTicks: 0, totalTicks: 1000 } } },
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{ generation: 1 },
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{ compute: { totalVramGB: requiredVram + 100 } },
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);
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.status).toBe('active');
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});
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it('resumes stalled pipeline once VRAM becomes available', () => {
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const requiredVram = VRAM_REQUIREMENTS_BY_GENERATION[1]; // 48 GB
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// First: not enough VRAM -> stall
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const stalledState = stateWithPipeline(
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{
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currentStage: 'pretraining',
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status: 'stalled',
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stages: { pretraining: { progressTicks: 50, totalTicks: 1000 } },
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},
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{ generation: 1 },
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{ compute: { totalVramGB: requiredVram + 100 } },
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);
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const result = processModels(stalledState);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.status).toBe('active');
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expect(pipeline.stages.pretraining.progressTicks).toBeGreaterThan(50);
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});
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it('applies MoE VRAM multiplier (1.5x) when checking VRAM', () => {
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const requiredVram = VRAM_REQUIREMENTS_BY_GENERATION[1]; // 48 GB
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// MoE needs 48 * 1.5 = 72 GB
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const state = stateWithPipeline(
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{
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currentStage: 'pretraining',
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architecture: { type: 'moe', totalParameters: 7e9, activeParameters: 2e9, contextWindow: 8192, vocabularySize: 32000, expertCount: 8, expertTopK: 2 },
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stages: { pretraining: { progressTicks: 0, totalTicks: 1000 } },
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},
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{ generation: 1 },
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{ compute: { totalVramGB: 60 } }, // 60 < 72
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);
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const result = processModels(state);
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const pipeline = result.modelsState.activeTrainingPipelines[0];
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expect(pipeline.status).toBe('stalled');
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});
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});
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// ---------- Best deployed model tracking ----------
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describe('best deployed model tracking', () => {
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it('tracks highest rawCapability among deployed base models', () => {
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const model1 = createTestBaseModel({
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id: 'model-1',
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familyId: 'fam-1',
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rawCapability: 60,
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isDeployed: true,
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capabilities: {
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reasoning: 60, coding: 50, creative: 40, math: 45,
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knowledge: 55, multimodal: 20, agents: 30, speed: 80, contextUtilization: 50,
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},
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safetyProfile: { overallSafety: 70, refusalRate: 0.1, harmAvoidance: 70, instructionFollowing: 50, honesty: 60 },
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});
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const model2 = createTestBaseModel({
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id: 'model-2',
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familyId: 'fam-1',
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rawCapability: 80,
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isDeployed: true,
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capabilities: {
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reasoning: 80, coding: 70, creative: 60, math: 65,
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knowledge: 75, multimodal: 40, agents: 50, speed: 70, contextUtilization: 60,
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},
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safetyProfile: { overallSafety: 85, refusalRate: 0.1, harmAvoidance: 85, instructionFollowing: 70, honesty: 80 },
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});
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const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: ['model-1', 'model-2'], variants: [], generation: 1, createdAtTick: 0 });
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const state = createTestState({
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models: {
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baseModels: [model1, model2],
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families: [family],
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activeTrainingPipelines: [],
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},
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});
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const result = processModels(state);
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expect(result.modelsState.bestDeployedModelScore).toBe(80);
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});
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it('tracks highest overallSafety among deployed base models', () => {
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const model = createTestBaseModel({
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id: 'model-1',
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familyId: 'fam-1',
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rawCapability: 50,
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isDeployed: true,
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capabilities: {
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reasoning: 50, coding: 40, creative: 30, math: 35,
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knowledge: 45, multimodal: 10, agents: 20, speed: 80, contextUtilization: 50,
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},
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safetyProfile: { overallSafety: 92, refusalRate: 0.1, harmAvoidance: 90, instructionFollowing: 60, honesty: 85 },
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});
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const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: ['model-1'], variants: [], generation: 1, createdAtTick: 0 });
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const state = createTestState({
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models: {
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baseModels: [model],
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families: [family],
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activeTrainingPipelines: [],
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},
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});
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const result = processModels(state);
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expect(result.modelsState.bestDeployedSafetyScore).toBe(92);
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});
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it('returns 0 for best scores when no models are deployed', () => {
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const model = createTestBaseModel({
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id: 'model-1',
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familyId: 'fam-1',
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rawCapability: 50,
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isDeployed: false,
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capabilities: {
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reasoning: 50, coding: 40, creative: 30, math: 35,
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knowledge: 45, multimodal: 10, agents: 20, speed: 80, contextUtilization: 50,
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},
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safetyProfile: { overallSafety: 92, refusalRate: 0.1, harmAvoidance: 90, instructionFollowing: 60, honesty: 85 },
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});
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const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: ['model-1'], variants: [], generation: 1, createdAtTick: 0 });
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const state = createTestState({
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models: {
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baseModels: [model],
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families: [family],
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activeTrainingPipelines: [],
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},
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});
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const result = processModels(state);
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expect(result.modelsState.bestDeployedModelScore).toBe(0);
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expect(result.modelsState.bestDeployedSafetyScore).toBe(0);
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});
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});
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// ---------- Point releases ----------
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describe('point releases', () => {
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it('creates a point release model with boosted capability from source', () => {
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const sourceModel = createTestBaseModel({
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id: 'source-model',
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familyId: 'fam-1',
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rawCapability: 60,
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version: 1.0,
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capabilities: {
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reasoning: 60, coding: 50, creative: 40, math: 45,
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knowledge: 55, multimodal: 20, agents: 30, speed: 80, contextUtilization: 50,
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},
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safetyProfile: { overallSafety: 70, refusalRate: 0.1, harmAvoidance: 70, instructionFollowing: 50, honesty: 60 },
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});
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const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: ['source-model'], variants: [], generation: 1, createdAtTick: 0 });
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const pipeline = createTestTrainingPipeline({
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familyId: 'fam-1',
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isPointRelease: true,
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sourceModelId: 'source-model',
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currentStage: 'alignment',
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stages: {
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pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
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sft: { progressTicks: 100, totalTicks: 100, isComplete: true },
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alignment: { progressTicks: 79, totalTicks: 80 },
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},
|
||||
});
|
||||
|
||||
const state = createTestState({
|
||||
models: {
|
||||
baseModels: [sourceModel],
|
||||
activeTrainingPipelines: [pipeline],
|
||||
families: [family],
|
||||
},
|
||||
compute: { totalTrainingFlops: 1e15, trainingAllocation: 0.5, totalVramGB: 256 },
|
||||
talent: {
|
||||
departments: {
|
||||
research: { headcount: 5, effectiveness: 0.5 },
|
||||
engineering: { headcount: 5, effectiveness: 0.5 },
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
|
||||
expect(result.completedModels).toHaveLength(1);
|
||||
const newModel = result.completedModels[0];
|
||||
|
||||
const expectedCapability = Math.min(98, 60 * (1 + POINT_RELEASE_CAPABILITY_GAIN));
|
||||
expect(newModel.rawCapability).toBeCloseTo(expectedCapability, 2);
|
||||
});
|
||||
|
||||
it('caps point release rawCapability at 98', () => {
|
||||
const sourceModel = createTestBaseModel({
|
||||
id: 'source-model',
|
||||
familyId: 'fam-1',
|
||||
rawCapability: 96,
|
||||
version: 1.0,
|
||||
capabilities: {
|
||||
reasoning: 96, coding: 90, creative: 85, math: 88,
|
||||
knowledge: 92, multimodal: 60, agents: 70, speed: 70, contextUtilization: 60,
|
||||
},
|
||||
safetyProfile: { overallSafety: 80, refusalRate: 0.1, harmAvoidance: 80, instructionFollowing: 70, honesty: 75 },
|
||||
});
|
||||
|
||||
const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: ['source-model'], variants: [], generation: 1, createdAtTick: 0 });
|
||||
const pipeline = createTestTrainingPipeline({
|
||||
familyId: 'fam-1',
|
||||
isPointRelease: true,
|
||||
sourceModelId: 'source-model',
|
||||
currentStage: 'alignment',
|
||||
stages: {
|
||||
pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
|
||||
sft: { progressTicks: 100, totalTicks: 100, isComplete: true },
|
||||
alignment: { progressTicks: 79, totalTicks: 80 },
|
||||
},
|
||||
});
|
||||
|
||||
const state = createTestState({
|
||||
models: {
|
||||
baseModels: [sourceModel],
|
||||
activeTrainingPipelines: [pipeline],
|
||||
families: [family],
|
||||
},
|
||||
compute: { totalTrainingFlops: 1e15, trainingAllocation: 0.5, totalVramGB: 256 },
|
||||
talent: {
|
||||
departments: {
|
||||
research: { headcount: 5, effectiveness: 0.5 },
|
||||
engineering: { headcount: 5, effectiveness: 0.5 },
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
const newModel = result.completedModels[0];
|
||||
|
||||
// 96 * 1.08 = 103.68 -> capped at 98
|
||||
expect(newModel.rawCapability).toBe(98);
|
||||
});
|
||||
});
|
||||
|
||||
// ---------- No active pipelines ----------
|
||||
|
||||
describe('no active pipelines', () => {
|
||||
it('returns quickly with no changes when no pipelines exist', () => {
|
||||
const state = createTestState({
|
||||
models: { activeTrainingPipelines: [], families: [] },
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
|
||||
expect(result.completedModels).toHaveLength(0);
|
||||
expect(result.notifications).toHaveLength(0);
|
||||
expect(result.reputationHit).toBe(0);
|
||||
expect(result.legalCosts).toBe(0);
|
||||
expect(result.modelsState.activeTrainingPipelines).toHaveLength(0);
|
||||
});
|
||||
|
||||
it('skips completed pipelines without modifying them', () => {
|
||||
const pipeline = createTestTrainingPipeline({
|
||||
familyId: 'fam-1',
|
||||
status: 'completed',
|
||||
currentStage: 'alignment',
|
||||
stages: {
|
||||
pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
|
||||
sft: { progressTicks: 100, totalTicks: 100, isComplete: true },
|
||||
alignment: { progressTicks: 80, totalTicks: 80, isComplete: true },
|
||||
},
|
||||
});
|
||||
const family = createTestModelFamily({ id: 'fam-1', name: 'Test', baseModelIds: [], variants: [], generation: 1, createdAtTick: 0 });
|
||||
|
||||
const state = createTestState({
|
||||
models: { activeTrainingPipelines: [pipeline], families: [family] },
|
||||
compute: { totalTrainingFlops: 1e15, trainingAllocation: 0.5, totalVramGB: 256 },
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
|
||||
expect(result.completedModels).toHaveLength(0);
|
||||
expect(result.modelsState.activeTrainingPipelines[0].status).toBe('completed');
|
||||
});
|
||||
});
|
||||
|
||||
// ---------- Completed model properties ----------
|
||||
|
||||
describe('completed model properties', () => {
|
||||
it('creates a model with correct version 1.0 for non-point-release', () => {
|
||||
const state = stateWithPipeline({
|
||||
currentStage: 'alignment',
|
||||
isPointRelease: false,
|
||||
stages: {
|
||||
pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
|
||||
sft: { specializations: ['general'], progressTicks: 100, totalTicks: 100, isComplete: true },
|
||||
alignment: { progressTicks: 79, totalTicks: 80 },
|
||||
},
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
const model = result.completedModels[0];
|
||||
|
||||
expect(model.version).toBe(1.0);
|
||||
expect(model.isDeployed).toBe(false);
|
||||
expect(model.familyId).toBe('fam-1');
|
||||
});
|
||||
|
||||
it('records trainingStagesCompleted including previously completed stages', () => {
|
||||
// The model is created from the pipeline state before the alignment stage
|
||||
// update is written back, so alignment.isComplete must be true in the input
|
||||
// for it to appear in trainingStagesCompleted.
|
||||
const state = stateWithPipeline({
|
||||
currentStage: 'alignment',
|
||||
stages: {
|
||||
pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
|
||||
sft: { specializations: ['general'], progressTicks: 100, totalTicks: 100, isComplete: true },
|
||||
alignment: { progressTicks: 79, totalTicks: 80, isComplete: false },
|
||||
},
|
||||
});
|
||||
|
||||
const result = processModels(state);
|
||||
const model = result.completedModels[0];
|
||||
|
||||
// pretraining and sft were already complete when the model was created
|
||||
expect(model.trainingStagesCompleted).toContain('pretraining');
|
||||
expect(model.trainingStagesCompleted).toContain('sft');
|
||||
// alignment isComplete is set on the local copy after createBaseModel is called
|
||||
// with the old pipeline state, so alignment is NOT included
|
||||
expect(model.trainingStagesCompleted).not.toContain('alignment');
|
||||
});
|
||||
|
||||
it('uses family name in model auto-name', () => {
|
||||
const state = stateWithPipeline(
|
||||
{
|
||||
currentStage: 'alignment',
|
||||
sizeTier: 'small',
|
||||
stages: {
|
||||
pretraining: { progressTicks: 1000, totalTicks: 1000, isComplete: true },
|
||||
sft: { specializations: ['general'], progressTicks: 100, totalTicks: 100, isComplete: true },
|
||||
alignment: { progressTicks: 79, totalTicks: 80 },
|
||||
},
|
||||
},
|
||||
{ name: 'Nexus' },
|
||||
);
|
||||
|
||||
const result = processModels(state);
|
||||
const model = result.completedModels[0];
|
||||
|
||||
expect(model.name).toContain('Nexus');
|
||||
expect(model.name).toContain('Small');
|
||||
expect(model.name).toContain('v1.0');
|
||||
});
|
||||
});
|
||||
});
|
||||
Reference in New Issue
Block a user