d803bfe2b1
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
72 lines
2.2 KiB
TypeScript
72 lines
2.2 KiB
TypeScript
/**
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* ADVANCED TUTORIAL: Custom Learning System
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*
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* Extend the self-learning system with custom optimization strategies,
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* domain-specific learning, and advanced evaluation metrics. Perfect for
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* building production-grade adaptive AI systems.
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*
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* What you'll learn:
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* - Creating custom evaluators
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* - Domain-specific optimization
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* - Advanced feedback loops
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* - Multi-objective optimization
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* - Transfer learning patterns
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*
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* Prerequisites:
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* - Complete intermediate tutorials first
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* - Set GEMINI_API_KEY environment variable
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* - npm install dspy.ts @ruvector/agentic-synth
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*
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* Run: npx tsx examples/advanced/custom-learning-system.ts
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*/
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import { Prediction } from 'dspy.ts';
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interface EvaluationMetrics {
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accuracy: number;
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creativity: number;
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relevance: number;
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engagement: number;
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technicalQuality: number;
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overall: number;
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}
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interface AdvancedLearningConfig {
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domain: string;
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objectives: string[];
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weights: Record<string, number>;
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learningStrategy: 'aggressive' | 'conservative' | 'adaptive';
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convergenceThreshold: number;
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diversityBonus: boolean;
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transferLearning: boolean;
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}
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interface TrainingExample {
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input: any;
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expectedOutput: any;
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quality: number;
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metadata: {
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domain: string;
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difficulty: 'easy' | 'medium' | 'hard';
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tags: string[];
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};
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}
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interface Evaluator {
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evaluate(output: Prediction, context: any): Promise<EvaluationMetrics>;
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}
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declare class EcommerceEvaluator implements Evaluator {
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evaluate(output: Prediction, context: any): Promise<EvaluationMetrics>;
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}
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declare class AdvancedLearningSystem {
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private lm;
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private config;
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private evaluator;
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private knowledgeBase;
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private promptStrategies;
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constructor(config: AdvancedLearningConfig, evaluator: Evaluator);
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private getTemperatureForStrategy;
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learnFromExample(example: TrainingExample): Promise<void>;
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train(examples: TrainingExample[]): Promise<void>;
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private generate;
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private findSimilarExamples;
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private displayTrainingResults;
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test(testCases: any[]): Promise<void>;
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}
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export { AdvancedLearningSystem, EcommerceEvaluator, AdvancedLearningConfig };
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//# sourceMappingURL=custom-learning-system.d.ts.map
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