@clduab11/gemini-flow
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Revolutionary AI agent swarm coordination platform with Google Services integration, multimedia processing, and production-ready monitoring. Features 8 Google AI services, quantum computing capabilities, and enterprise-grade security.
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text/typescript
/**
* Comprehensive TDD Test Suite for Veo3 Video Generator
*
* Following London School TDD with emphasis on contract testing,
* video generation pipeline coordination, and performance validation.
*
* RED-GREEN-REFACTOR CYCLE:
* Focus on video generation workflow orchestration, worker pool management,
* rendering pipeline coordination, and AI-powered content generation.
*/
import {
describe,
it,
expect,
beforeEach,
afterEach,
jest,
} from "@jest/globals";
import { EventEmitter } from "events";
import { Veo3VideoGenerator } from "../veo3-video-generator.js";
import {
MockFactory,
TestDataGenerator,
MockBuilder,
ContractTester,
PerformanceTester,
PropertyGenerator,
} from "./test-utilities.js";
// Mock external dependencies following London School principles
jest.mock("../../../utils/logger.js");
jest.mock("../../../ai/video-ai-engine.js");
jest.mock("../../../rendering/worker-pool.js");
describe("Veo3VideoGenerator - London School TDD", () => {
let veo3Generator: Veo3VideoGenerator;
let mockConfig: any;
let mockLogger: jest.Mocked<any>;
let mockWorkerPool: jest.Mocked<any>;
let mockPipelineManager: jest.Mocked<any>;
let mockAIEngine: jest.Mocked<any>;
let mockStorageManager: jest.Mocked<any>;
let mockPerformanceMonitor: jest.Mocked<any>;
let mockQualityController: jest.Mocked<any>;
let mockBuilder: MockBuilder;
beforeEach(() => {
// Setup comprehensive mock configuration
mockConfig = {
rendering: {
engine: "cuda",
maxConcurrentRenders: 8,
memoryLimit: 16384,
timeoutMinutes: 60,
quality: {
draft: {
renderSamples: 16,
denoising: false,
motionBlur: false,
antiAliasing: "none",
compression: {
codec: "h264",
bitrate: 1000000,
quality: 70,
preset: "fast",
},
},
preview: {
renderSamples: 32,
denoising: true,
motionBlur: false,
antiAliasing: "fxaa",
compression: {
codec: "h264",
bitrate: 2000000,
quality: 80,
preset: "medium",
},
},
standard: {
renderSamples: 64,
denoising: true,
motionBlur: true,
antiAliasing: "msaa",
compression: {
codec: "h264",
bitrate: 5000000,
quality: 85,
preset: "slow",
},
},
high: {
renderSamples: 128,
denoising: true,
motionBlur: true,
antiAliasing: "taa",
compression: {
codec: "h265",
bitrate: 10000000,
quality: 90,
preset: "veryslow",
},
},
ultra: {
renderSamples: 256,
denoising: true,
motionBlur: true,
antiAliasing: "taa",
compression: {
codec: "av1",
bitrate: 20000000,
quality: 95,
preset: "placebo",
},
},
},
},
ai: {
model: "veo3-generation-v2",
promptEnhancement: true,
styleTransfer: true,
contentAnalysis: true,
qualityAssessment: true,
},
storage: {
inputPath: "/tmp/veo3/input",
outputPath: "/tmp/veo3/output",
tempPath: "/tmp/veo3/temp",
cleanup: true,
retention: 7,
},
optimization: {
gpu: {
enabled: true,
multiGPU: false,
memoryFraction: 0.8,
cudaGraphs: true,
},
memory: {
streaming: true,
tiling: true,
compression: false,
maxFramesInMemory: 30,
},
disk: {
ssdCache: true,
compression: true,
prefetching: true,
parallelIO: true,
},
network: {
distributedRendering: false,
loadBalancing: false,
caching: true,
cdn: false,
},
},
pipeline: {
stages: [
{
name: "preprocessing",
enabled: true,
priority: 1,
resources: { cpu: 2, memory: 2048, gpu: 0, disk: 1024 },
timeout: 300000,
},
{
name: "generation",
enabled: true,
priority: 2,
resources: { cpu: 8, memory: 8192, gpu: 1, disk: 4096 },
timeout: 1800000,
},
{
name: "postprocessing",
enabled: true,
priority: 3,
resources: { cpu: 4, memory: 4096, gpu: 0.5, disk: 2048 },
timeout: 600000,
},
{
name: "encoding",
enabled: true,
priority: 4,
resources: { cpu: 4, memory: 2048, gpu: 0, disk: 8192 },
timeout: 900000,
},
],
parallelization: {
maxWorkers: 8,
loadBalancing: "resource_based",
affinity: true,
},
monitoring: {
progress: true,
performance: true,
quality: true,
errors: true,
},
recovery: {
checkpoints: true,
retryFailedFrames: true,
fallbackQuality: "standard",
maxRetries: 3,
},
},
};
mockBuilder = new MockBuilder();
// Setup Logger mock
mockLogger = mockBuilder
.mockFunction("info", jest.fn())
.mockFunction("debug", jest.fn())
.mockFunction("warn", jest.fn())
.mockFunction("error", jest.fn())
.build() as any;
// Setup WorkerPool mock
mockWorkerPool = {
initialize: jest.fn().mockResolvedValue(undefined),
allocateWorkers: jest
.fn()
.mockResolvedValue([
createMockWorker("worker-1", "gpu"),
createMockWorker("worker-2", "gpu"),
createMockWorker("worker-3", "cpu"),
]),
releaseWorkers: jest.fn().mockResolvedValue(undefined),
getAvailableWorkers: jest.fn().mockReturnValue(3),
getWorkerMetrics: jest.fn().mockReturnValue({
totalWorkers: 8,
activeWorkers: 3,
utilizationRate: 0.375,
}),
on: jest.fn(),
emit: jest.fn(),
};
// Setup PipelineManager mock
mockPipelineManager = {
initialize: jest.fn().mockResolvedValue(undefined),
createPipeline: jest.fn().mockResolvedValue({
stages: mockConfig.pipeline.stages.map((stage) => ({
name: stage.name,
type: stage.name,
processor: `${stage.name}_processor`,
parameters: {},
dependencies: stage.name === "preprocessing" ? [] : ["preprocessing"],
})),
parallelization: 8,
optimization: {
gpu: true,
multicore: true,
memory: {
tiling: true,
streaming: true,
compression: true,
maxUsage: 8192,
},
caching: {
enabled: true,
size: 1024,
strategy: "lru",
persistence: false,
},
},
output: {
location: "/output",
format: { container: "mp4", codec: "h264", bitrate: 5000000 },
metadata: { title: "Generated Video", timestamp: true },
delivery: {
method: "download",
compression: true,
encryption: false,
},
},
}),
executeStage: jest.fn().mockResolvedValue(undefined),
on: jest.fn(),
emit: jest.fn(),
};
// Setup VideoAIEngine mock
mockAIEngine = {
initialize: jest.fn().mockResolvedValue(undefined),
enhancePrompt: jest
.fn()
.mockImplementation(
async (prompt, style) =>
`${prompt} (enhanced for ${style.type} style)`,
),
analyzeContent: jest.fn().mockResolvedValue({
complexity: 0.7,
elements: ["landscape", "water", "mountains"],
recommendations: ["increase_render_samples", "enable_motion_blur"],
}),
generateStoryboard: jest.fn().mockResolvedValue([
{ frame: 0, description: "Opening landscape shot" },
{ frame: 15, description: "Camera pan across water" },
{ frame: 30, description: "Final mountain vista" },
]),
optimizeRenderSettings: jest.fn().mockResolvedValue({
renderSamples: 96,
denoising: true,
motionBlur: true,
}),
};
// Setup VideoStorageManager mock
mockStorageManager = {
initialize: jest.fn().mockResolvedValue(undefined),
prepareAssets: jest.fn().mockResolvedValue(undefined),
storeFrame: jest.fn().mockResolvedValue("/storage/frame-001.exr"),
finalizeOutput: jest.fn().mockResolvedValue({
path: "/output/video.mp4",
size: 52428800,
duration: 30.0,
format: "mp4",
}),
cleanup: jest.fn().mockResolvedValue(undefined),
createCheckpoint: jest.fn().mockResolvedValue("checkpoint-123"),
restoreCheckpoint: jest.fn().mockResolvedValue(undefined),
};
// Setup PerformanceMonitor mock
mockPerformanceMonitor = {
start: jest.fn().mockResolvedValue(undefined),
recordFrameRender: jest.fn(),
recordStageCompletion: jest.fn(),
getMetrics: jest
.fn()
.mockResolvedValue(MockFactory.createPerformanceMetrics()),
getCurrentThroughput: jest.fn().mockReturnValue(24.5), // FPS
getProjectMetrics: jest.fn().mockResolvedValue({
averageFrameTime: 2.1,
totalRenderTime: 1250000,
memoryPeakUsage: 12800,
gpuUtilization: 85,
}),
on: jest.fn(),
emit: jest.fn(),
};
// Setup QualityController mock
mockQualityController = {
assessQuality: jest.fn().mockResolvedValue(0.92),
validateOutput: jest.fn().mockResolvedValue({
passed: true,
score: 0.88,
issues: [],
recommendations: [],
}),
adjustQualitySettings: jest.fn().mockResolvedValue({
renderSamples: 80,
denoising: true,
}),
};
// Mock constructor dependencies
jest.mocked(require("../../../utils/logger.js")).Logger = jest
.fn()
.mockImplementation(() => mockLogger);
// Create Veo3VideoGenerator instance
veo3Generator = new Veo3VideoGenerator(mockConfig);
// Inject mocks
(veo3Generator as any).workerPool = mockWorkerPool;
(veo3Generator as any).pipelineManager = mockPipelineManager;
(veo3Generator as any).aiEngine = mockAIEngine;
(veo3Generator as any).storageManager = mockStorageManager;
(veo3Generator as any).performanceMonitor = mockPerformanceMonitor;
(veo3Generator as any).qualityController = mockQualityController;
});
afterEach(() => {
jest.clearAllMocks();
mockBuilder.clear();
});
// ==================== INITIALIZATION BEHAVIOR ====================
describe("Initialization and Component Orchestration", () => {
it("should coordinate initialization of all rendering subsystems", async () => {
// ARRANGE
const initializeSpy = jest.spyOn(veo3Generator, "initialize");
// ACT
await veo3Generator.initialize();
// ASSERT - Verify initialization coordination
expect(initializeSpy).toHaveBeenCalledTimes(1);
expect(mockAIEngine.initialize).toHaveBeenCalled();
expect(mockWorkerPool.initialize).toHaveBeenCalled();
expect(mockPipelineManager.initialize).toHaveBeenCalled();
expect(mockStorageManager.initialize).toHaveBeenCalled();
expect(mockPerformanceMonitor.start).toHaveBeenCalled();
expect(mockLogger.info).toHaveBeenCalledWith(
"Initializing Veo3 Video Generator",
);
});
it("should handle component initialization failures with proper error propagation", async () => {
// ARRANGE
const initError = new Error("Worker pool initialization failed");
mockWorkerPool.initialize.mockRejectedValueOnce(initError);
// ACT & ASSERT
await expect(veo3Generator.initialize()).rejects.toThrow(
"Worker pool initialization failed",
);
expect(mockLogger.error).toHaveBeenCalledWith(
"Failed to initialize video generator",
initError,
);
});
it("should establish event handler contracts for component coordination", async () => {
// ACT
await veo3Generator.initialize();
// ASSERT - Verify event handler setup
expect(mockWorkerPool.on).toHaveBeenCalledWith(
"worker:error",
expect.any(Function),
);
expect(mockPerformanceMonitor.on).toHaveBeenCalledWith(
"performance:degraded",
expect.any(Function),
);
expect(mockPipelineManager.on).toHaveBeenCalledWith(
"stage:completed",
expect.any(Function),
);
});
});
// ==================== PROJECT CREATION BEHAVIOR ====================
describe("Project Creation and Validation", () => {
beforeEach(async () => {
await veo3Generator.initialize();
});
it("should coordinate project creation with AI prompt enhancement", async () => {
// ARRANGE
const videoRequest = MockFactory.createVideoGenerationRequest();
const projectName = "Test Video Project";
// ACT
const result = await veo3Generator.createProject(
projectName,
videoRequest,
);
// ASSERT - Verify creation coordination
expect(result.success).toBe(true);
expect(result.data.name).toBe(projectName);
expect(result.data.status).toBe("pending");
expect(mockAIEngine.enhancePrompt).toHaveBeenCalledWith(
videoRequest.prompt,
videoRequest.style,
);
expect(mockLogger.info).toHaveBeenCalledWith(
"Creating video project",
expect.objectContaining({
name: projectName,
duration: videoRequest.duration,
}),
);
});
it("should validate video generation request parameters", async () => {
// ARRANGE
const invalidRequest = {
...MockFactory.createVideoGenerationRequest(),
prompt: "", // Empty prompt
duration: 0, // Invalid duration
frameRate: 150, // Too high frame rate
resolution: { width: 8000, height: 8000, aspectRatio: "1:1" }, // Exceeds limits
};
// ACT
const result = await veo3Generator.createProject(
"Invalid Project",
invalidRequest,
);
// ASSERT
expect(result.success).toBe(false);
expect(result.error?.code).toBe("PROJECT_CREATION_FAILED");
expect(mockLogger.error).toHaveBeenCalled();
});
it("should calculate total frames and project metrics correctly", async () => {
// ARRANGE
const videoRequest = {
...MockFactory.createVideoGenerationRequest(),
duration: 30,
frameRate: 24,
};
// ACT
const result = await veo3Generator.createProject(
"Metrics Test",
videoRequest,
);
// ASSERT
expect(result.success).toBe(true);
expect(result.data.metrics.totalFrames).toBe(720); // 30 * 24
expect(result.data.metrics.framesRendered).toBe(0);
});
});
// ==================== VIDEO GENERATION PIPELINE ====================
describe("Video Generation Pipeline Orchestration", () => {
let projectId: string;
beforeEach(async () => {
await veo3Generator.initialize();
const project = await veo3Generator.createProject(
"Pipeline Test",
MockFactory.createVideoGenerationRequest(),
);
projectId = project.data!.id;
});
it("should coordinate generation pipeline with worker allocation", async () => {
// ARRANGE
const startSpy = jest.spyOn(veo3Generator, "startGeneration");
// ACT
const result = await veo3Generator.startGeneration(projectId);
// ASSERT - Verify pipeline coordination
expect(result.success).toBe(true);
expect(startSpy).toHaveBeenCalledWith(projectId);
expect(mockWorkerPool.allocateWorkers).toHaveBeenCalled();
expect(mockStorageManager.prepareAssets).toHaveBeenCalledWith(projectId);
expect(mockLogger.info).toHaveBeenCalledWith(
"Starting video generation",
expect.objectContaining({ projectId }),
);
});
it("should execute preprocessing stage with AI content analysis", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
// Mock pipeline execution
jest
.spyOn(veo3Generator as any, "executePreprocessingStage")
.mockResolvedValue(undefined);
// ACT
await (veo3Generator as any).executePreprocessingStage(
{ name: "preprocessing", type: "preprocessing" },
{ project },
);
// ASSERT
expect(mockAIEngine.analyzeContent).toHaveBeenCalledWith(
project.request.prompt,
project.request.style,
);
expect(mockStorageManager.prepareAssets).toHaveBeenCalledWith(projectId);
});
it("should coordinate frame generation across worker pool", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
const workers = await mockWorkerPool.allocateWorkers(project.request);
// Mock generation stage execution
jest
.spyOn(veo3Generator as any, "generateFrames")
.mockImplementation(async (worker, startFrame, endFrame) => {
// Simulate frame generation
for (let i = startFrame; i < endFrame; i++) {
await (veo3Generator as any).generateFrame(worker, i, { project });
}
});
// ACT
await (veo3Generator as any).executeGenerationStage(
{ name: "generation", type: "generation" },
{ project, workers },
);
// ASSERT
expect(workers.length).toBeGreaterThan(0);
expect(mockPerformanceMonitor.recordFrameRender).toHaveBeenCalled();
});
it("should coordinate postprocessing with quality assessment", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
// Mock postprocessing execution
jest
.spyOn(veo3Generator as any, "applyEffects")
.mockResolvedValue(undefined);
// ACT
await (veo3Generator as any).executePostprocessingStage(
{ name: "postprocessing", type: "postprocessing" },
{ project },
);
// ASSERT
expect(mockQualityController.assessQuality).toHaveBeenCalledWith(
projectId,
);
});
it("should coordinate encoding stage with output file generation", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
// Mock encoding execution
jest.spyOn(veo3Generator as any, "encodeVideo").mockResolvedValue({
type: "video",
path: "/output/test-video.mp4",
size: 52428800,
format: "mp4",
duration: 30,
resolution: { width: 1920, height: 1080 },
});
// ACT
await (veo3Generator as any).executeEncodingStage(
{ name: "encoding", type: "encoding" },
{ project },
);
// ASSERT
expect(project.outputFiles.length).toBeGreaterThan(0);
expect(project.outputFiles[0].type).toBe("video");
});
});
// ==================== WORKER POOL MANAGEMENT ====================
describe("Worker Pool Management and Load Balancing", () => {
beforeEach(async () => {
await veo3Generator.initialize();
});
it("should coordinate worker allocation based on project complexity", async () => {
// ARRANGE
const simpleRequest = {
...MockFactory.createVideoGenerationRequest(),
duration: 10,
resolution: { width: 1280, height: 720, aspectRatio: "16:9" },
effects: [],
};
const complexRequest = {
...MockFactory.createVideoGenerationRequest(),
duration: 120,
resolution: { width: 3840, height: 2160, aspectRatio: "16:9" },
effects: [
{
type: "color_grading",
parameters: {},
timing: { start: 0, duration: 120, easing: "linear" },
},
{
type: "motion_blur",
parameters: {},
timing: { start: 0, duration: 120, easing: "linear" },
},
{
type: "particle_system",
parameters: {},
timing: { start: 10, duration: 60, easing: "ease-in-out" },
},
],
};
// ACT
const simpleWorkers = await mockWorkerPool.allocateWorkers(simpleRequest);
const complexWorkers =
await mockWorkerPool.allocateWorkers(complexRequest);
// ASSERT
expect(mockWorkerPool.allocateWorkers).toHaveBeenCalledTimes(2);
// Complex projects should potentially require more workers
expect(mockLogger.debug).toHaveBeenCalledWith(
"Allocating workers for project complexity",
expect.any(Object),
);
});
it("should handle worker failures with graceful recovery", async () => {
// ARRANGE
const projectId = "worker-failure-test";
const project = await veo3Generator.createProject(
"Worker Failure Test",
MockFactory.createVideoGenerationRequest(),
);
const failingWorker = createMockWorker("failing-worker", "gpu");
failingWorker.status = "error";
const workerError = new Error("GPU memory allocation failed");
// ACT
(veo3Generator as any).handleWorkerError({
workerId: "failing-worker",
error: workerError,
projectId: project.data!.id,
});
// ASSERT
expect(mockLogger.error).toHaveBeenCalledWith(
"Worker error",
expect.objectContaining({ workerId: "failing-worker" }),
);
});
it("should coordinate worker pool scaling based on demand", async () => {
// ARRANGE
const highDemandScenario = Array.from({ length: 10 }, (_, i) =>
veo3Generator.createProject(
`Project ${i}`,
MockFactory.createVideoGenerationRequest(),
),
);
// ACT
const projects = await Promise.all(highDemandScenario);
const startPromises = projects.map((p) =>
p.success
? veo3Generator.startGeneration(p.data!.id)
: Promise.resolve(),
);
await Promise.allSettled(startPromises);
// ASSERT
expect(mockWorkerPool.allocateWorkers).toHaveBeenCalledTimes(
projects.filter((p) => p.success).length,
);
});
});
// ==================== PERFORMANCE MONITORING ====================
describe("Performance Monitoring and Optimization", () => {
let projectId: string;
beforeEach(async () => {
await veo3Generator.initialize();
const project = await veo3Generator.createProject(
"Performance Test",
MockFactory.createVideoGenerationRequest(),
);
projectId = project.data!.id;
});
it("should coordinate performance metrics collection during generation", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
// Mock performance monitoring during generation
jest
.spyOn(veo3Generator as any, "generateFrame")
.mockImplementation(async (worker, frameIndex, context) => {
mockPerformanceMonitor.recordFrameRender(frameIndex, 2.1, worker.id);
context.project.metrics.framesRendered++;
});
// ACT
await (veo3Generator as any).generateFrame(
createMockWorker("perf-worker", "gpu"),
15,
{ project: (await veo3Generator.getProject(projectId)).data! },
);
// ASSERT
expect(mockPerformanceMonitor.recordFrameRender).toHaveBeenCalledWith(
15,
expect.any(Number),
"perf-worker",
);
});
it("should handle performance degradation with adaptive quality adjustment", async () => {
// ARRANGE
const degradationEvent = {
type: "rendering_slowdown",
metric: "frame_render_time",
currentValue: 5.2,
threshold: 3.0,
projectId,
};
// ACT
(veo3Generator as any).handlePerformanceDegradation(degradationEvent);
// ASSERT
expect(mockLogger.warn).toHaveBeenCalledWith(
"Performance degradation detected",
degradationEvent,
);
expect(mockQualityController.adjustQualitySettings).toHaveBeenCalled();
});
it("should provide comprehensive metrics for project monitoring", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
// ACT
const metricsResult = await veo3Generator.getMetrics();
// ASSERT
expect(metricsResult.success).toBe(true);
ContractTester.validatePerformanceMetrics(metricsResult.data);
expect(mockPerformanceMonitor.getMetrics).toHaveBeenCalled();
});
});
// ==================== ERROR HANDLING AND RECOVERY ====================
describe("Error Handling and Recovery Coordination", () => {
let projectId: string;
beforeEach(async () => {
await veo3Generator.initialize();
const project = await veo3Generator.createProject(
"Error Test",
MockFactory.createVideoGenerationRequest(),
);
projectId = project.data!.id;
});
it("should coordinate checkpoint creation for recovery", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
// Mock checkpoint creation during generation
jest
.spyOn(veo3Generator as any, "createCheckpoint")
.mockImplementation(async (context) => {
return await mockStorageManager.createCheckpoint(context.project.id);
});
// ACT
const checkpointId = await (veo3Generator as any).createCheckpoint({
project,
});
// ASSERT
expect(checkpointId).toBe("checkpoint-123");
expect(mockStorageManager.createCheckpoint).toHaveBeenCalledWith(
projectId,
);
});
it("should handle rendering failures with frame retry logic", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
const project = (await veo3Generator.getProject(projectId)).data!;
const renderError = new Error("Frame rendering failed");
const mockWorker = createMockWorker("failing-worker", "gpu");
// Mock frame rendering failure
jest
.spyOn(veo3Generator as any, "executeTask")
.mockRejectedValueOnce(renderError)
.mockResolvedValueOnce(undefined); // Success on retry
// ACT
await (veo3Generator as any).generateFrame(mockWorker, 10, { project });
// ASSERT
expect(mockLogger.warn).toHaveBeenCalledWith(
"Frame rendering failed, retrying",
expect.objectContaining({ frameIndex: 10 }),
);
});
it("should coordinate project cancellation with resource cleanup", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
// ACT
const result = await veo3Generator.cancelProject(projectId);
// ASSERT
expect(result.success).toBe(true);
expect(mockWorkerPool.releaseWorkers).toHaveBeenCalled();
expect(mockStorageManager.cleanup).toHaveBeenCalledWith(projectId);
expect(mockLogger.info).toHaveBeenCalledWith(
"Cancelling project",
expect.objectContaining({ projectId }),
);
});
});
// ==================== AI INTEGRATION BEHAVIOR ====================
describe("AI Integration and Enhancement", () => {
beforeEach(async () => {
await veo3Generator.initialize();
});
it("should coordinate AI prompt enhancement with style analysis", async () => {
// ARRANGE
const videoRequest = {
...MockFactory.createVideoGenerationRequest(),
prompt: "A beautiful sunset over the ocean",
style: {
type: "cinematic",
mood: "dramatic",
colorPalette: ["#FF6B35", "#F7931E", "#FFD23F"],
lighting: {
type: "golden_hour",
intensity: 0.8,
direction: "west",
color: "#FFD700",
},
},
};
// ACT
const result = await veo3Generator.createProject(
"AI Enhancement Test",
videoRequest,
);
// ASSERT
expect(result.success).toBe(true);
expect(mockAIEngine.enhancePrompt).toHaveBeenCalledWith(
"A beautiful sunset over the ocean",
expect.objectContaining({
type: "cinematic",
mood: "dramatic",
}),
);
});
it("should coordinate AI-driven render optimization", async () => {
// ARRANGE
const project = await veo3Generator.createProject(
"AI Optimization",
MockFactory.createVideoGenerationRequest(),
);
const projectId = project.data!.id;
// ACT
await veo3Generator.startGeneration(projectId);
// ASSERT
expect(mockAIEngine.optimizeRenderSettings).toHaveBeenCalled();
expect(mockLogger.debug).toHaveBeenCalledWith(
"AI render optimization applied",
expect.any(Object),
);
});
it("should handle AI service failures with graceful fallback", async () => {
// ARRANGE
const aiError = new Error("AI service unavailable");
mockAIEngine.enhancePrompt.mockRejectedValueOnce(aiError);
const videoRequest = MockFactory.createVideoGenerationRequest();
// ACT
const result = await veo3Generator.createProject(
"AI Fallback Test",
videoRequest,
);
// ASSERT - Should succeed without AI enhancement
expect(result.success).toBe(true);
expect(mockLogger.warn).toHaveBeenCalledWith(
"AI enhancement failed, using original prompt",
aiError,
);
});
});
// ==================== CONTRACT AND PERFORMANCE TESTING ====================
describe("Contract Validation and Performance Requirements", () => {
beforeEach(async () => {
await veo3Generator.initialize();
});
it("should maintain service response contracts for all operations", async () => {
// ARRANGE & ACT
const createResult = await veo3Generator.createProject(
"Contract Test",
MockFactory.createVideoGenerationRequest(),
);
const listResult = await veo3Generator.listProjects();
const metricsResult = await veo3Generator.getMetrics();
// ASSERT
ContractTester.validateServiceResponse(createResult);
ContractTester.validateServiceResponse(listResult);
ContractTester.validateServiceResponse(metricsResult);
});
it("should meet performance requirements for project operations", async () => {
// ARRANGE & ACT
const performanceTest = PerformanceTester.createPerformanceTest(
"project_creation",
() =>
veo3Generator.createProject(
"Perf Test",
MockFactory.createVideoGenerationRequest(),
),
200, // 200ms max
3, // 3 iterations
);
// ASSERT
await performanceTest();
});
it("should validate event emitter contract for project monitoring", async () => {
// ARRANGE
const expectedEvents = [
"project:created",
"project:started",
"project:progress",
"project:completed",
"project:failed",
"project:cancelled",
"worker:error",
"performance:degraded",
];
// ACT & ASSERT
ContractTester.validateEventEmitter(veo3Generator, expectedEvents);
});
});
// ==================== PROPERTY-BASED TESTING ====================
describe("Property-Based Testing for Video Generation Parameters", () => {
beforeEach(async () => {
await veo3Generator.initialize();
});
it("should handle various valid video generation configurations", async () => {
// ARRANGE
const validConfigs = PropertyGenerator.generateTestCases(
() => ({
prompt: TestDataGenerator.randomString(50),
duration: Math.floor(Math.random() * 300) + 1, // 1-300 seconds
frameRate: [24, 25, 30, 60][Math.floor(Math.random() * 4)],
resolution: {
width: [1280, 1920, 2560, 3840][Math.floor(Math.random() * 4)],
height: [720, 1080, 1440, 2160][Math.floor(Math.random() * 4)],
aspectRatio: "16:9",
},
style: {
type: ["realistic", "cartoon", "artistic"][
Math.floor(Math.random() * 3)
],
mood: ["peaceful", "dramatic", "energetic"][
Math.floor(Math.random() * 3)
],
},
}),
5,
);
// ACT & ASSERT
for (const config of validConfigs) {
const result = await veo3Generator.createProject(
`Test ${TestDataGenerator.randomString(6)}`,
config as any,
);
expect(result.success).toBe(true);
}
});
it("should properly reject invalid video generation parameters", async () => {
// ARRANGE
const invalidConfigs = [
{ prompt: "", duration: 10 }, // Empty prompt
{ prompt: "test", duration: 0 }, // Zero duration
{ prompt: "test", duration: 10, frameRate: 200 }, // Excessive frame rate
{
prompt: "test",
duration: 10,
resolution: { width: 10000, height: 10000 },
}, // Excessive resolution
];
// ACT & ASSERT
for (const config of invalidConfigs) {
const result = await veo3Generator.createProject(
"Invalid Test",
config as any,
);
expect(result.success).toBe(false);
}
});
});
// ==================== QUALITY ASSESSMENT INTEGRATION ====================
describe("Quality Assessment and Control Integration", () => {
let projectId: string;
beforeEach(async () => {
await veo3Generator.initialize();
const project = await veo3Generator.createProject(
"Quality Test",
MockFactory.createVideoGenerationRequest(),
);
projectId = project.data!.id;
});
it("should coordinate quality assessment during generation", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
// Mock quality assessment during postprocessing
mockQualityController.assessQuality.mockResolvedValue(0.75); // Below threshold
// ACT
const project = (await veo3Generator.getProject(projectId)).data!;
await (veo3Generator as any).executePostprocessingStage(
{ name: "postprocessing", type: "postprocessing" },
{ project },
);
// ASSERT
expect(mockQualityController.assessQuality).toHaveBeenCalledWith(
projectId,
);
expect(mockLogger.info).toHaveBeenCalledWith(
"Quality assessment completed",
expect.objectContaining({
projectId,
score: 0.75,
}),
);
});
it("should trigger quality improvement when assessment fails", async () => {
// ARRANGE
await veo3Generator.startGeneration(projectId);
// Mock low quality assessment
mockQualityController.assessQuality.mockResolvedValue(0.6); // Below acceptable threshold
mockQualityController.adjustQualitySettings.mockResolvedValue({
renderSamples: 96,
denoising: true,
});
// ACT
const project = (await veo3Generator.getProject(projectId)).data!;
await (veo3Generator as any).executePostprocessingStage(
{ name: "postprocessing", type: "postprocessing" },
{ project },
);
// ASSERT
expect(mockQualityController.adjustQualitySettings).toHaveBeenCalled();
expect(mockLogger.warn).toHaveBeenCalledWith(
"Quality below threshold, adjusting settings",
expect.objectContaining({ projectId }),
);
});
});
});
// ==================== HELPER FUNCTIONS ====================
/**
* Creates a mock worker for testing worker pool functionality
*/
function createMockWorker(id: string, type: "cpu" | "gpu" | "hybrid") {
return {
id,
type,
status: "idle" as const,
currentTask: undefined,
performance: {
tasksCompleted: Math.floor(Math.random() * 100),
averageTime: Math.random() * 10,
memoryUsage: Math.floor(Math.random() * 1024),
errors: Math.floor(Math.random() * 5),
},
};
}
/**
* RED-GREEN-REFACTOR CYCLE DOCUMENTATION FOR VEO3 VIDEO GENERATOR:
*
* This comprehensive test suite demonstrates London School TDD applied to
* complex video generation pipeline orchestration:
*
* 1. PIPELINE ORCHESTRATION TESTING:
* - Tests focus on HOW Veo3VideoGenerator coordinates rendering pipeline stages
* - Worker pool management, AI integration, quality control coordination
* - Storage management, performance monitoring, and error recovery
*
* 2. CONTRACT-DRIVEN DEVELOPMENT:
* - All external dependencies mocked to verify interaction contracts
* - Service response contracts validated across all operations
* - Event emitter contracts ensure proper monitoring and coordination
*
* 3. COMPLEX WORKFLOW TESTING:
* - Multi-stage video generation pipeline with checkpointing
* - Dynamic worker allocation based on project complexity
* - AI-enhanced content generation with fallback strategies
* - Real-time performance monitoring and adaptive quality control
*
* 4. LONDON SCHOOL PRINCIPLES APPLIED:
* - RED: Define expected coordination behavior through failing tests
* - GREEN: Implement minimal orchestration logic to satisfy contracts
* - REFACTOR: Improve coordination patterns while maintaining test contracts
*
* Key Collaboration Patterns Tested:
* - WorkerPool ↔ PipelineManager (resource allocation and task distribution)
* - AIEngine ↔ VideoGenerator (content analysis and optimization)
* - QualityController ↔ PerformanceMonitor (quality assessment and adaptation)
* - StorageManager ↔ CheckpointSystem (data persistence and recovery)
* - EventSystem ↔ MonitoringServices (real-time coordination and alerts)
*
* This design promotes high cohesion within the video generation pipeline
* while maintaining loose coupling between subsystems through well-defined contracts.
*/