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arela

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AI-powered CTO with multi-agent orchestration, code summarization, visual testing (web + mobile) for blazing fast development.

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import type { MemoryItem, ScoredItem } from "./types.js"; /** * RelevanceScorer - Scores memory items by relevance to query * * Scoring factors: * 1. Semantic similarity (40%) - Using simple text similarity * 2. Keyword overlap (30%) - Direct word matches * 3. Layer confidence weight (20%) - From classifier * 4. Recency (10%) - Newer items preferred for Session/Project */ export declare class RelevanceScorer { /** * Score multiple items by relevance to query */ score(query: string, items: MemoryItem[]): ScoredItem[]; /** * Calculate relevance score for a single item */ private calculateScore; /** * Extract content from item (handles various formats) */ private getItemContent; /** * Calculate text similarity using character n-grams * Returns score between 0 and 1 */ private textSimilarity; /** * Generate character n-grams from text */ private getNgrams; /** * Calculate keyword overlap score * Returns score between 0 and 1 */ private keywordOverlap; /** * Calculate recency score based on timestamp * Returns score between 0 and 1 */ private recencyScore; /** * Tokenize text into words */ private tokenize; /** * Calculate cosine similarity between two texts * Alternative to textSimilarity using TF-IDF-like approach */ cosineSimilarity(text1: string, text2: string): number; /** * Calculate term frequency */ private termFrequency; } //# sourceMappingURL=scorer.d.ts.map