@clduab11/gemini-flow/src/services/google-services/veo3-video-generator.ts

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.

/**
 * Veo3 Video Generator with Advanced Rendering Pipeline
 *
 * Production-ready video generation service with AI-powered content creation,
 * real-time rendering, and comprehensive media processing capabilities.
 */

import { EventEmitter } from "events";
import { Logger } from "../../utils/logger.js";
import {
  VideoGenerationRequest,
  VideoStyle,
  RenderingPipeline,
  RenderStage,
  ServiceResponse,
  ServiceError,
  PerformanceMetrics,
} from "./interfaces.js";

export interface Veo3Config {
  rendering: RenderingConfig;
  ai: AIConfig;
  storage: StorageConfig;
  optimization: OptimizationConfig;
  pipeline: PipelineConfig;
}

export interface RenderingConfig {
  engine: "cuda" | "opencl" | "metal" | "cpu";
  maxConcurrentRenders: number;
  memoryLimit: number; // MB
  timeoutMinutes: number;
  quality: QualityPresets;
}

export interface QualityPresets {
  draft: QualitySettings;
  preview: QualitySettings;
  standard: QualitySettings;
  high: QualitySettings;
  ultra: QualitySettings;
}

export interface QualitySettings {
  renderSamples: number;
  denoising: boolean;
  motionBlur: boolean;
  antiAliasing: string;
  compression: CompressionSettings;
}

export interface CompressionSettings {
  codec: string;
  bitrate: number;
  quality: number;
  preset: string;
}

export interface AIConfig {
  model: string;
  promptEnhancement: boolean;
  styleTransfer: boolean;
  contentAnalysis: boolean;
  qualityAssessment: boolean;
}

export interface StorageConfig {
  inputPath: string;
  outputPath: string;
  tempPath: string;
  cleanup: boolean;
  retention: number; // days
}

export interface OptimizationConfig {
  gpu: GPUOptimization;
  memory: MemoryOptimization;
  disk: DiskOptimization;
  network: NetworkOptimization;
}

export interface GPUOptimization {
  enabled: boolean;
  multiGPU: boolean;
  memoryFraction: number;
  cudaGraphs: boolean;
}

export interface MemoryOptimization {
  streaming: boolean;
  tiling: boolean;
  compression: boolean;
  maxFramesInMemory: number;
}

export interface DiskOptimization {
  ssdCache: boolean;
  compression: boolean;
  prefetching: boolean;
  parallelIO: boolean;
}

export interface NetworkOptimization {
  distributedRendering: boolean;
  loadBalancing: boolean;
  caching: boolean;
  cdn: boolean;
}

export interface PipelineConfig {
  stages: PipelineStageConfig[];
  parallelization: ParallelizationConfig;
  monitoring: MonitoringConfig;
  recovery: RecoveryConfig;
}

export interface PipelineStageConfig {
  name: string;
  enabled: boolean;
  priority: number;
  resources: ResourceRequirements;
  timeout: number;
}

export interface ResourceRequirements {
  cpu: number;
  memory: number;
  gpu: number;
  disk: number;
}

export interface ParallelizationConfig {
  maxWorkers: number;
  loadBalancing: "round_robin" | "least_loaded" | "resource_based";
  affinity: boolean;
}

export interface MonitoringConfig {
  progress: boolean;
  performance: boolean;
  quality: boolean;
  errors: boolean;
}

export interface RecoveryConfig {
  checkpoints: boolean;
  retryFailedFrames: boolean;
  fallbackQuality: string;
  maxRetries: number;
}

export interface VideoProject {
  id: string;
  name: string;
  request: VideoGenerationRequest;
  status:
    | "pending"
    | "processing"
    | "rendering"
    | "completed"
    | "failed"
    | "cancelled";
  progress: number; // 0-100
  startTime?: Date;
  endTime?: Date;
  estimatedCompletion?: Date;
  outputFiles: OutputFile[];
  metrics: ProjectMetrics;
  error?: string;
}

export interface OutputFile {
  type: "video" | "thumbnail" | "preview" | "metadata";
  path: string;
  size: number;
  format: string;
  duration?: number;
  resolution?: { width: number; height: number };
}

export interface ProjectMetrics {
  framesRendered: number;
  totalFrames: number;
  renderingSpeed: number; // FPS
  memoryUsed: number; // MB
  gpuUtilization: number; // percentage
  errors: number;
  warnings: number;
}

export interface RenderingContext {
  project: VideoProject;
  pipeline: RenderingPipeline;
  workers: Worker[];
  checkpoint?: Checkpoint;
}

export interface Worker {
  id: string;
  type: "cpu" | "gpu" | "hybrid";
  status: "idle" | "busy" | "error";
  currentTask?: RenderTask;
  performance: WorkerPerformance;
}

export interface RenderTask {
  id: string;
  type: "frame" | "sequence" | "effect" | "composite";
  data: any;
  priority: number;
  dependencies: string[];
}

export interface WorkerPerformance {
  tasksCompleted: number;
  averageTime: number;
  memoryUsage: number;
  errors: number;
}

export interface Checkpoint {
  frameIndex: number;
  timestamp: Date;
  data: any;
  metadata: CheckpointMetadata;
}

export interface CheckpointMetadata {
  version: string;
  quality: string;
  settings: any;
  progress: number;
}

export class Veo3VideoGenerator extends EventEmitter {
  private logger: Logger;
  private config: Veo3Config;
  private projects: Map<string, VideoProject> = new Map();
  private renderingContexts: Map<string, RenderingContext> = new Map();
  private workerPool: WorkerPool;
  private pipelineManager: PipelineManager;
  private aiEngine: VideoAIEngine;
  private storageManager: VideoStorageManager;
  private performanceMonitor: PerformanceMonitor;
  private qualityController: QualityController;

  constructor(config: Veo3Config) {
    super();
    this.config = config;
    this.logger = new Logger("Veo3VideoGenerator");

    this.initializeComponents();
    this.setupEventHandlers();
  }

  /**
   * Initializes the video generation engine
   */
  async initialize(): Promise<void> {
    try {
      this.logger.info("Initializing Veo3 Video Generator");

      // Initialize AI engine
      await this.aiEngine.initialize();

      // Initialize worker pool
      await this.workerPool.initialize();

      // Initialize pipeline manager
      await this.pipelineManager.initialize();

      // Initialize storage
      await this.storageManager.initialize();

      // Start performance monitoring
      await this.performanceMonitor.start();

      this.emit("initialized");
    } catch (error) {
      this.logger.error("Failed to initialize video generator", error);
      throw error;
    }
  }

  /**
   * Creates a new video generation project
   */
  async createProject(
    name: string,
    request: VideoGenerationRequest,
  ): Promise<ServiceResponse<VideoProject>> {
    try {
      this.logger.info("Creating video project", {
        name,
        duration: request.duration,
      });

      // Validate request
      await this.validateRequest(request);

      // Enhance prompt using AI
      if (this.config.ai.promptEnhancement) {
        request.prompt = await this.aiEngine.enhancePrompt(
          request.prompt,
          request.style,
        );
      }

      // Create project
      const project: VideoProject = {
        id: this.generateProjectId(),
        name,
        request,
        status: "pending",
        progress: 0,
        outputFiles: [],
        metrics: {
          framesRendered: 0,
          totalFrames: this.calculateTotalFrames(request),
          renderingSpeed: 0,
          memoryUsed: 0,
          gpuUtilization: 0,
          errors: 0,
          warnings: 0,
        },
      };

      // Register project
      this.projects.set(project.id, project);

      this.emit("project:created", project);

      return {
        success: true,
        data: project,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to create project", { name, error });
      return this.createErrorResponse("PROJECT_CREATION_FAILED", error.message);
    }
  }

  /**
   * Starts video generation for a project
   */
  async startGeneration(projectId: string): Promise<ServiceResponse<void>> {
    try {
      this.logger.info("Starting video generation", { projectId });

      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      if (project.status !== "pending") {
        throw new Error(`Project is not in pending state: ${project.status}`);
      }

      // Create rendering context
      const context = await this.createRenderingContext(project);
      this.renderingContexts.set(projectId, context);

      // Start generation process
      project.status = "processing";
      project.startTime = new Date();

      // Generate video asynchronously
      this.generateVideoAsync(context).catch((error) => {
        this.logger.error("Generation failed", { projectId, error });
        project.status = "failed";
        project.error = error.message;
        this.emit("project:failed", { projectId, error });
      });

      this.emit("project:started", { projectId });

      return {
        success: true,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to start generation", { projectId, error });
      return this.createErrorResponse("GENERATION_START_FAILED", error.message);
    }
  }

  /**
   * Gets project status and progress
   */
  async getProject(projectId: string): Promise<ServiceResponse<VideoProject>> {
    try {
      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      return {
        success: true,
        data: project,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to get project", { projectId, error });
      return this.createErrorResponse("PROJECT_GET_FAILED", error.message);
    }
  }

  /**
   * Cancels a video generation project
   */
  async cancelProject(projectId: string): Promise<ServiceResponse<void>> {
    try {
      this.logger.info("Cancelling project", { projectId });

      const project = this.projects.get(projectId);
      if (!project) {
        throw new Error(`Project not found: ${projectId}`);
      }

      const context = this.renderingContexts.get(projectId);
      if (context) {
        await this.cancelRenderingContext(context);
        this.renderingContexts.delete(projectId);
      }

      project.status = "cancelled";
      project.endTime = new Date();

      this.emit("project:cancelled", { projectId });

      return {
        success: true,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to cancel project", { projectId, error });
      return this.createErrorResponse(
        "PROJECT_CANCELLATION_FAILED",
        error.message,
      );
    }
  }

  /**
   * Lists all projects
   */
  async listProjects(): Promise<ServiceResponse<VideoProject[]>> {
    try {
      const projects = Array.from(this.projects.values());

      return {
        success: true,
        data: projects,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to list projects", error);
      return this.createErrorResponse("PROJECT_LIST_FAILED", error.message);
    }
  }

  /**
   * Gets performance metrics
   */
  async getMetrics(): Promise<ServiceResponse<PerformanceMetrics>> {
    try {
      const metrics = await this.performanceMonitor.getMetrics();

      return {
        success: true,
        data: metrics,
        metadata: {
          requestId: this.generateRequestId(),
          timestamp: new Date(),
          processingTime: 0,
          region: "local",
        },
      };
    } catch (error) {
      this.logger.error("Failed to get metrics", error);
      return this.createErrorResponse("METRICS_GET_FAILED", error.message);
    }
  }

  // ==================== Private Helper Methods ====================

  private initializeComponents(): void {
    this.workerPool = new WorkerPool(this.config.rendering);
    this.pipelineManager = new PipelineManager(this.config.pipeline);
    this.aiEngine = new VideoAIEngine(this.config.ai);
    this.storageManager = new VideoStorageManager(this.config.storage);
    this.performanceMonitor = new PerformanceMonitor(this.config.optimization);
    this.qualityController = new QualityController(
      this.config.rendering.quality,
    );
  }

  private setupEventHandlers(): void {
    this.workerPool.on("worker:error", this.handleWorkerError.bind(this));
    this.performanceMonitor.on(
      "performance:degraded",
      this.handlePerformanceDegradation.bind(this),
    );
    this.pipelineManager.on(
      "stage:completed",
      this.handleStageCompleted.bind(this),
    );
  }

  private async validateRequest(
    request: VideoGenerationRequest,
  ): Promise<void> {
    if (!request.prompt || request.prompt.trim().length === 0) {
      throw new Error("Prompt is required");
    }

    if (request.duration <= 0 || request.duration > 300) {
      throw new Error("Duration must be between 0 and 300 seconds");
    }

    if (request.frameRate <= 0 || request.frameRate > 120) {
      throw new Error("Frame rate must be between 0 and 120 FPS");
    }

    // Validate resolution
    const maxPixels = 3840 * 2160; // 4K
    const pixels = request.resolution.width * request.resolution.height;
    if (pixels > maxPixels) {
      throw new Error("Resolution exceeds maximum supported size");
    }
  }

  private calculateTotalFrames(request: VideoGenerationRequest): number {
    return Math.ceil(request.duration * request.frameRate);
  }

  private async createRenderingContext(
    project: VideoProject,
  ): Promise<RenderingContext> {
    // Create rendering pipeline
    const pipeline = await this.pipelineManager.createPipeline(project.request);

    // Allocate workers
    const workers = await this.workerPool.allocateWorkers(project.request);

    return {
      project,
      pipeline,
      workers,
      checkpoint: undefined,
    };
  }

  private async generateVideoAsync(context: RenderingContext): Promise<void> {
    const { project, pipeline } = context;

    try {
      project.status = "processing";

      // Execute pipeline stages
      for (const stage of pipeline.stages) {
        await this.executeStage(stage, context);

        if (project.status === "cancelled") {
          throw new Error("Generation cancelled");
        }
      }

      // Finalize project
      project.status = "completed";
      project.endTime = new Date();
      project.progress = 100;

      this.emit("project:completed", { projectId: project.id });
    } catch (error) {
      project.status = "failed";
      project.error = error.message;
      project.endTime = new Date();

      this.emit("project:failed", { projectId: project.id, error });
      throw error;
    } finally {
      // Cleanup rendering context
      await this.cleanupRenderingContext(context);
      this.renderingContexts.delete(project.id);
    }
  }

  private async executeStage(
    stage: RenderStage,
    context: RenderingContext,
  ): Promise<void> {
    this.logger.debug("Executing pipeline stage", {
      stage: stage.name,
      type: stage.type,
      projectId: context.project.id,
    });

    const startTime = Date.now();

    try {
      switch (stage.type) {
        case "preprocessing":
          await this.executePreprocessingStage(stage, context);
          break;

        case "generation":
          await this.executeGenerationStage(stage, context);
          break;

        case "postprocessing":
          await this.executePostprocessingStage(stage, context);
          break;

        case "encoding":
          await this.executeEncodingStage(stage, context);
          break;

        default:
          throw new Error(`Unknown stage type: ${stage.type}`);
      }

      const duration = Date.now() - startTime;
      this.logger.debug("Stage completed", {
        stage: stage.name,
        duration,
        projectId: context.project.id,
      });
    } catch (error) {
      this.logger.error("Stage failed", {
        stage: stage.name,
        error,
        projectId: context.project.id,
      });
      throw error;
    }
  }

  private async executePreprocessingStage(
    stage: RenderStage,
    context: RenderingContext,
  ): Promise<void> {
    // Preprocessing implementation
    const { project } = context;

    // Analyze prompt and style
    if (this.config.ai.contentAnalysis) {
      await this.aiEngine.analyzeContent(
        project.request.prompt,
        project.request.style,
      );
    }

    // Prepare assets
    await this.storageManager.prepareAssets(project.id);

    // Update progress
    project.progress = 10;
    this.emit("project:progress", {
      projectId: project.id,
      progress: project.progress,
    });
  }

  private async executeGenerationStage(
    stage: RenderStage,
    context: RenderingContext,
  ): Promise<void> {
    // Video generation implementation
    const { project, workers } = context;

    const totalFrames = project.metrics.totalFrames;
    const framesPerWorker = Math.ceil(totalFrames / workers.length);

    // Distribute work among workers
    const tasks: Promise<void>[] = [];

    for (let i = 0; i < workers.length; i++) {
      const startFrame = i * framesPerWorker;
      const endFrame = Math.min(startFrame + framesPerWorker, totalFrames);

      if (startFrame < totalFrames) {
        tasks.push(
          this.generateFrames(workers[i], startFrame, endFrame, context),
        );
      }
    }

    // Wait for all workers to complete
    await Promise.all(tasks);

    // Update progress
    project.progress = 80;
    this.emit("project:progress", {
      projectId: project.id,
      progress: project.progress,
    });
  }

  private async executePostprocessingStage(
    stage: RenderStage,
    context: RenderingContext,
  ): Promise<void> {
    // Postprocessing implementation
    const { project } = context;

    // Apply effects
    await this.applyEffects(project.request.effects, context);

    // Quality assessment
    if (this.config.ai.qualityAssessment) {
      await this.qualityController.assessQuality(project.id);
    }

    // Update progress
    project.progress = 90;
    this.emit("project:progress", {
      projectId: project.id,
      progress: project.progress,
    });
  }

  private async executeEncodingStage(
    stage: RenderStage,
    context: RenderingContext,
  ): Promise<void> {
    // Encoding implementation
    const { project } = context;

    // Encode video
    const outputFile = await this.encodeVideo(project);
    project.outputFiles.push(outputFile);

    // Generate thumbnails
    const thumbnails = await this.generateThumbnails(project);
    project.outputFiles.push(...thumbnails);

    // Update progress
    project.progress = 95;
    this.emit("project:progress", {
      projectId: project.id,
      progress: project.progress,
    });
  }

  private async generateFrames(
    worker: Worker,
    startFrame: number,
    endFrame: number,
    context: RenderingContext,
  ): Promise<void> {
    // Frame generation implementation
    for (let frame = startFrame; frame < endFrame; frame++) {
      if (context.project.status === "cancelled") {
        break;
      }

      await this.generateFrame(worker, frame, context);

      // Update metrics
      context.project.metrics.framesRendered++;

      // Update progress periodically
      if (frame % 10 === 0) {
        const progress = Math.min(
          70,
          (context.project.metrics.framesRendered /
            context.project.metrics.totalFrames) *
            70,
        );
        context.project.progress = 10 + progress; // Base 10% from preprocessing
        this.emit("project:progress", {
          projectId: context.project.id,
          progress: context.project.progress,
        });
      }
    }
  }

  private async generateFrame(
    worker: Worker,
    frameIndex: number,
    context: RenderingContext,
  ): Promise<void> {
    // Individual frame generation
    const { project } = context;

    // Create render task
    const task: RenderTask = {
      id: `${project.id}_frame_${frameIndex}`,
      type: "frame",
      data: {
        frameIndex,
        prompt: project.request.prompt,
        style: project.request.style,
        resolution: project.request.resolution,
      },
      priority: 1,
      dependencies: [],
    };

    // Execute task on worker
    await this.executeTask(worker, task);
  }

  private async executeTask(worker: Worker, task: RenderTask): Promise<void> {
    // Task execution implementation
    worker.status = "busy";
    worker.currentTask = task;

    try {
      // Simulate frame rendering
      await this.delay(100); // Placeholder for actual rendering

      worker.performance.tasksCompleted++;
      worker.status = "idle";
      worker.currentTask = undefined;
    } catch (error) {
      worker.status = "error";
      worker.performance.errors++;
      throw error;
    }
  }

  private async applyEffects(
    effects: any[],
    context: RenderingContext,
  ): Promise<void> {
    // Effects application implementation
    for (const effect of effects) {
      await this.applyEffect(effect, context);
    }
  }

  private async applyEffect(
    effect: any,
    context: RenderingContext,
  ): Promise<void> {
    // Individual effect application
  }

  private async encodeVideo(project: VideoProject): Promise<OutputFile> {
    // Video encoding implementation
    return {
      type: "video",
      path: `/output/${project.id}/video.mp4`,
      size: 50 * 1024 * 1024, // 50MB placeholder
      format: project.request.format.container,
      duration: project.request.duration,
      resolution: project.request.resolution,
    };
  }

  private async generateThumbnails(
    project: VideoProject,
  ): Promise<OutputFile[]> {
    // Thumbnail generation implementation
    return [
      {
        type: "thumbnail",
        path: `/output/${project.id}/thumbnail.jpg`,
        size: 100 * 1024, // 100KB
        format: "jpeg",
      },
    ];
  }

  private async cancelRenderingContext(
    context: RenderingContext,
  ): Promise<void> {
    // Cancel all workers
    for (const worker of context.workers) {
      worker.status = "idle";
      worker.currentTask = undefined;
    }

    // Release workers
    await this.workerPool.releaseWorkers(context.workers);
  }

  private async cleanupRenderingContext(
    context: RenderingContext,
  ): Promise<void> {
    // Cleanup temporary files
    await this.storageManager.cleanup(context.project.id);

    // Release workers
    await this.workerPool.releaseWorkers(context.workers);
  }

  private delay(ms: number): Promise<void> {
    return new Promise((resolve) => setTimeout(resolve, ms));
  }

  private generateProjectId(): string {
    return `veo3_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
  }

  private generateRequestId(): string {
    return `req_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`;
  }

  private createErrorResponse(
    code: string,
    message: string,
  ): ServiceResponse<any> {
    return {
      success: false,
      error: {
        code,
        message,
        retryable: false,
        timestamp: new Date(),
      },
      metadata: {
        requestId: this.generateRequestId(),
        timestamp: new Date(),
        processingTime: 0,
        region: "local",
      },
    };
  }

  private handleWorkerError(event: any): void {
    this.logger.error("Worker error", event);
    this.emit("worker:error", event);
  }

  private handlePerformanceDegradation(event: any): void {
    this.logger.warn("Performance degradation detected", event);
    this.emit("performance:degraded", event);
  }

  private handleStageCompleted(event: any): void {
    this.logger.debug("Pipeline stage completed", event);
  }
}

// ==================== Supporting Classes ====================

class WorkerPool {
  private config: RenderingConfig;
  private workers: Map<string, Worker> = new Map();
  private availableWorkers: Worker[] = [];
  private logger: Logger;

  constructor(config: RenderingConfig) {
    this.config = config;
    this.logger = new Logger("WorkerPool");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing worker pool");

    // Create workers based on configuration
    for (let i = 0; i < this.config.maxConcurrentRenders; i++) {
      const worker = this.createWorker(i);
      this.workers.set(worker.id, worker);
      this.availableWorkers.push(worker);
    }
  }

  async allocateWorkers(request: VideoGenerationRequest): Promise<Worker[]> {
    const requiredWorkers = Math.min(
      this.calculateRequiredWorkers(request),
      this.availableWorkers.length,
    );

    const allocated = this.availableWorkers.splice(0, requiredWorkers);
    return allocated;
  }

  async releaseWorkers(workers: Worker[]): Promise<void> {
    for (const worker of workers) {
      worker.status = "idle";
      worker.currentTask = undefined;
      this.availableWorkers.push(worker);
    }
  }

  private createWorker(index: number): Worker {
    return {
      id: `worker_${index}`,
      type: this.config.engine === "cpu" ? "cpu" : "gpu",
      status: "idle",
      performance: {
        tasksCompleted: 0,
        averageTime: 0,
        memoryUsage: 0,
        errors: 0,
      },
    };
  }

  private calculateRequiredWorkers(request: VideoGenerationRequest): number {
    // Calculate based on complexity
    const baseWorkers = 1;
    const complexityFactor = this.calculateComplexity(request);
    return Math.min(
      baseWorkers * complexityFactor,
      this.config.maxConcurrentRenders,
    );
  }

  private calculateComplexity(request: VideoGenerationRequest): number {
    let complexity = 1;

    // Duration factor
    if (request.duration > 30) complexity += 1;
    if (request.duration > 60) complexity += 1;

    // Resolution factor
    const pixels = request.resolution.width * request.resolution.height;
    if (pixels > 1920 * 1080) complexity += 1; // Above 1080p
    if (pixels > 3840 * 2160) complexity += 2; // Above 4K

    // Effects factor
    complexity += Math.min(request.effects.length, 2);

    return complexity;
  }
}

class PipelineManager {
  private config: PipelineConfig;
  private logger: Logger;

  constructor(config: PipelineConfig) {
    this.config = config;
    this.logger = new Logger("PipelineManager");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing pipeline manager");
  }

  async createPipeline(
    request: VideoGenerationRequest,
  ): Promise<RenderingPipeline> {
    return {
      stages: [
        {
          name: "preprocessing",
          type: "preprocessing",
          processor: "ai_preprocessor",
          parameters: { request },
          dependencies: [],
        },
        {
          name: "generation",
          type: "generation",
          processor: "veo3_generator",
          parameters: { request },
          dependencies: ["preprocessing"],
        },
        {
          name: "postprocessing",
          type: "postprocessing",
          processor: "effects_processor",
          parameters: { effects: request.effects },
          dependencies: ["generation"],
        },
        {
          name: "encoding",
          type: "encoding",
          processor: "video_encoder",
          parameters: { format: request.format },
          dependencies: ["postprocessing"],
        },
      ],
      parallelization: this.config.parallelization.maxWorkers,
      optimization: {
        gpu: true,
        multicore: true,
        memory: {
          tiling: true,
          streaming: true,
          compression: true,
          maxUsage:
            this.config.stages.find((s) => s.name === "generation")?.resources
              ?.memory || 8192,
        },
        caching: {
          enabled: true,
          size: 1024,
          strategy: "lru",
          persistence: false,
        },
      },
      output: {
        location: "/output",
        format: request.format,
        metadata: {
          title: "Generated Video",
          timestamp: true,
        },
        delivery: {
          method: "download",
          compression: true,
          encryption: false,
        },
      },
    };
  }
}

class VideoAIEngine {
  private config: AIConfig;
  private logger: Logger;

  constructor(config: AIConfig) {
    this.config = config;
    this.logger = new Logger("VideoAIEngine");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing video AI engine");
  }

  async enhancePrompt(prompt: string, style: VideoStyle): Promise<string> {
    // AI prompt enhancement
    return prompt + " (enhanced)";
  }

  async analyzeContent(prompt: string, style: VideoStyle): Promise<any> {
    // Content analysis
    return {};
  }
}

class VideoStorageManager {
  private config: StorageConfig;
  private logger: Logger;

  constructor(config: StorageConfig) {
    this.config = config;
    this.logger = new Logger("VideoStorageManager");
  }

  async initialize(): Promise<void> {
    this.logger.info("Initializing video storage manager");
  }

  async prepareAssets(projectId: string): Promise<void> {
    // Asset preparation
  }

  async cleanup(projectId: string): Promise<void> {
    // Cleanup temporary files
  }
}

class PerformanceMonitor extends EventEmitter {
  private config: OptimizationConfig;
  private logger: Logger;

  constructor(config: OptimizationConfig) {
    super();
    this.config = config;
    this.logger = new Logger("PerformanceMonitor");
  }

  async start(): Promise<void> {
    this.logger.info("Starting performance monitor");
  }

  async getMetrics(): Promise<PerformanceMetrics> {
    return {
      latency: { mean: 0, p50: 0, p95: 0, p99: 0, max: 0 },
      throughput: {
        requestsPerSecond: 0,
        bytesPerSecond: 0,
        operationsPerSecond: 0,
      },
      utilization: { cpu: 0, memory: 0, disk: 0, network: 0 },
      errors: { rate: 0, percentage: 0, types: {} },
    };
  }
}

class QualityController {
  private config: QualityPresets;
  private logger: Logger;

  constructor(config: QualityPresets) {
    this.config = config;
    this.logger = new Logger("QualityController");
  }

  async assessQuality(projectId: string): Promise<number> {
    // Quality assessment
    return 0.95; // 95% quality score
  }
}