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@craftapit/tester

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A focused, LLM-powered testing framework for natural language test scenarios

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/** * A simple embedding utility that converts text to vector embeddings * This is a lightweight alternative to using full ML-based embedding models * Note: This produces lower quality embeddings than specialized models but works without external dependencies */ export declare class SimpleEmbedding { private dimension; private seed; /** * Create a new SimpleEmbedding instance * @param dimension The dimension of the embedding vectors (default: 1536) * @param seed Random seed for reproducibility (default: 42) */ constructor(dimension?: number, seed?: number); /** * Generate an embedding vector for the given text * @param text The text to embed * @returns Embedding vector */ embed(text: string): number[]; /** * Normalize and clean text for embedding */ private normalizeText; /** * Generate a deterministic vector based on text content * Uses a simple hashing approach to create vectors that preserve some semantic similarity */ private generateVector; /** * Simple seeded string hash function */ private seededHash; /** * Normalize vector to unit length */ private normalizeVector; }