const { createClient } = require('redis'); class CacheManagerRedis { /** * @param {object} options - Options for the Redis client. * Example: { url: 'redis://localhost:6379' } */ constructor(options) { this.client = createClient(options); this.client.on('error', (err) => console.error('Redis Client Error', err)); this.client.connect(); } // Normalize input for consistent comparison normalize(input) { return input.trim().toLowerCase(); } // Compute the Levenshtein distance between two strings levenshtein(a, b) { const matrix = []; for (let i = 0; i <= b.length; i++) { matrix[i] = [i]; } for (let j = 0; j <= a.length; j++) { matrix[0][j] = j; } for (let i = 1; i <= b.length; i++) { for (let j = 1; j <= a.length; j++) { if (b.charAt(i - 1) === a.charAt(j - 1)) { matrix[i][j] = matrix[i - 1][j - 1]; } else { matrix[i][j] = Math.min( matrix[i - 1][j - 1] + 1, matrix[i][j - 1] + 1, matrix[i - 1][j] + 1 ); } } } return matrix[b.length][a.length]; } // Calculate similarity between two strings (1 means identical, 0 means completely different) similarity(a, b) { const distance = this.levenshtein(a, b); const maxLen = Math.max(a.length, b.length); if (maxLen === 0) return 1; return 1 - distance / maxLen; } // Check the cache for a result that is at least 80% similar to the new input. async getCachedResult(input) { const normalizedInput = this.normalize(input); const keys = await this.client.keys('cache:*'); for (const key of keys) { const storedNormalizedInput = key.slice(6); // remove "cache:" prefix const sim = this.similarity(normalizedInput, storedNormalizedInput); if (sim >= 0.8) { const cachedOutput = await this.client.get(key); return cachedOutput; } } return null; } // Store the result in cache with key as normalized input async setCache(input, output) { const normalizedInput = this.normalize(input); await this.client.set(`cache:${normalizedInput}`, output, { EX: 3600 }); } } module.exports = CacheManagerRedis;