/** * ADVANCED TUTORIAL: Production Pipeline * * Build a complete production-ready data generation pipeline with: * - Error handling and retry logic * - Monitoring and metrics * - Rate limiting and cost controls * - Batch processing and caching * - Quality validation * * What you'll learn: * - Production-grade error handling * - Performance monitoring * - Cost optimization * - Scalability patterns * - Deployment best practices * * Prerequisites: * - Complete previous tutorials * - Set GEMINI_API_KEY environment variable * - npm install @ruvector/agentic-synth * * Run: npx tsx examples/advanced/production-pipeline.ts */ import { GenerationResult } from '@ruvector/agentic-synth'; interface PipelineConfig { maxRetries: number; retryDelay: number; batchSize: number; maxConcurrency: number; qualityThreshold: number; costBudget: number; rateLimitPerMinute: number; enableCaching: boolean; outputDirectory: string; } interface PipelineMetrics { totalRequests: number; successfulRequests: number; failedRequests: number; totalDuration: number; totalCost: number; averageQuality: number; cacheHits: number; retries: number; errors: Array<{ timestamp: Date; error: string; context: any; }>; } interface QualityValidator { validate(data: any): { valid: boolean; score: number; issues: string[]; }; } declare class ProductionPipeline { private config; private synth; private metrics; private requestsThisMinute; private minuteStartTime; constructor(config?: Partial); private checkRateLimit; private checkCostBudget; private generateWithRetry; private processBatch; run(requests: any[], validator?: QualityValidator): Promise; private saveResults; private displayMetrics; getMetrics(): PipelineMetrics; } declare class ProductQualityValidator implements QualityValidator { validate(data: any[]): { valid: boolean; score: number; issues: string[]; }; } export { ProductionPipeline, ProductQualityValidator, PipelineConfig, PipelineMetrics }; //# sourceMappingURL=production-pipeline.d.ts.map