git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
40 lines
1.4 KiB
TypeScript
40 lines
1.4 KiB
TypeScript
/**
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* Self-Improving Data Generation with Feedback Loops
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*
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* This example demonstrates:
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* - Quality scoring and regeneration
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* - A/B testing data for model improvement
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* - Pattern learning from production data
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* - Adaptive schema evolution
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*/
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import type { GenerationResult } from '../../src/types.js';
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/**
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* Generate data with quality scores and regenerate low-quality samples
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*/
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export declare function qualityScoringLoop(): Promise<void>;
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/**
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* Generate A/B test data to improve model performance
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*/
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export declare function abTestingData(): Promise<GenerationResult<unknown>>;
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/**
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* Learn patterns from production data and generate similar synthetic data
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*/
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export declare function patternLearningLoop(): Promise<GenerationResult<unknown>>;
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/**
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* Evolve data schema based on feedback and changing requirements
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*/
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export declare function adaptiveSchemaEvolution(): Promise<{
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v1: GenerationResult<unknown>;
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v2: GenerationResult<unknown>;
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v3: GenerationResult<unknown>;
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}>;
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/**
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* Generate data for active learning - focus on uncertain/informative samples
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*/
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export declare function activeLearningData(): Promise<GenerationResult<unknown>>;
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/**
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* Generate evaluation data for continuous model monitoring
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*/
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export declare function continuousEvaluationData(): Promise<GenerationResult<unknown>>;
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export declare function runAllFeedbackLoopExamples(): Promise<void>;
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//# sourceMappingURL=feedback-loop.d.ts.map
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