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Trilium/apps/server/src/services/search/utils/text_utils.ts

334 lines
13 KiB
TypeScript

"use strict";
import { normalize } from "../../utils.js";
/**
* Shared text processing utilities for search functionality
*/
// Configuration constants for fuzzy matching
export const FUZZY_SEARCH_CONFIG = {
// Minimum token length for fuzzy operators to prevent false positives
MIN_FUZZY_TOKEN_LENGTH: 3,
// Maximum edit distance for fuzzy matching
MAX_EDIT_DISTANCE: 2,
// Maximum proximity distance for phrase matching (in words)
MAX_PHRASE_PROXIMITY: 10,
// Absolute hard limits for extreme cases - only to prevent system crashes
ABSOLUTE_MAX_CONTENT_SIZE: 100 * 1024 * 1024, // 100MB - extreme upper limit to prevent OOM
ABSOLUTE_MAX_WORD_COUNT: 2000000, // 2M words - extreme upper limit for word processing
// Performance warning thresholds - inform user but still attempt search
PERFORMANCE_WARNING_SIZE: 5 * 1024 * 1024, // 5MB - warn about potential performance impact
PERFORMANCE_WARNING_WORDS: 100000, // 100K words - warn about word count impact
// Progressive processing thresholds for very large content
PROGRESSIVE_PROCESSING_SIZE: 10 * 1024 * 1024, // 10MB - use progressive processing
PROGRESSIVE_PROCESSING_WORDS: 500000, // 500K words - use progressive processing
// Performance thresholds
EARLY_TERMINATION_THRESHOLD: 3,
} as const;
/**
* Normalizes text by removing diacritics and converting to lowercase.
* This is the centralized text normalization function used across all search components.
* Uses the shared normalize function from utils for consistency.
*
* Examples:
* - "café" -> "cafe"
* - "naïve" -> "naive"
* - "HELLO WORLD" -> "hello world"
*
* @param text The text to normalize
* @returns The normalized text
*/
export function normalizeSearchText(text: string): string {
if (!text || typeof text !== 'string') {
return '';
}
// Use shared normalize function for consistency across the codebase
return normalize(text);
}
/**
* Optimized edit distance calculation using single array and early termination.
* This is significantly more memory efficient than the 2D matrix approach and includes
* early termination optimizations for better performance.
*
* @param str1 First string
* @param str2 Second string
* @param maxDistance Maximum allowed distance (for early termination)
* @returns The edit distance between the strings, or maxDistance + 1 if exceeded
*/
export function calculateOptimizedEditDistance(str1: string, str2: string, maxDistance: number = FUZZY_SEARCH_CONFIG.MAX_EDIT_DISTANCE): number {
// Input validation
if (typeof str1 !== 'string' || typeof str2 !== 'string') {
throw new Error('Both arguments must be strings');
}
if (maxDistance < 0 || !Number.isInteger(maxDistance)) {
throw new Error('maxDistance must be a non-negative integer');
}
const len1 = str1.length;
const len2 = str2.length;
// Performance guard: if strings are too long, limit processing
const maxStringLength = 1000;
if (len1 > maxStringLength || len2 > maxStringLength) {
// For very long strings, fall back to simple length-based heuristic
return Math.abs(len1 - len2) <= maxDistance ? Math.abs(len1 - len2) : maxDistance + 1;
}
// Early termination: if length difference exceeds max distance
if (Math.abs(len1 - len2) > maxDistance) {
return maxDistance + 1;
}
// Handle edge cases
if (len1 === 0) return len2 <= maxDistance ? len2 : maxDistance + 1;
if (len2 === 0) return len1 <= maxDistance ? len1 : maxDistance + 1;
// Use single array optimization for better memory usage
let previousRow = Array.from({ length: len2 + 1 }, (_, i) => i);
let currentRow = new Array(len2 + 1);
for (let i = 1; i <= len1; i++) {
currentRow[0] = i;
let minInRow = i;
for (let j = 1; j <= len2; j++) {
const cost = str1[i - 1] === str2[j - 1] ? 0 : 1;
currentRow[j] = Math.min(
previousRow[j] + 1, // deletion
currentRow[j - 1] + 1, // insertion
previousRow[j - 1] + cost // substitution
);
// Track minimum value in current row for early termination
if (currentRow[j] < minInRow) {
minInRow = currentRow[j];
}
}
// Early termination: if minimum distance in row exceeds threshold
if (minInRow > maxDistance) {
return maxDistance + 1;
}
// Swap arrays for next iteration
[previousRow, currentRow] = [currentRow, previousRow];
}
const result = previousRow[len2];
return result <= maxDistance ? result : maxDistance + 1;
}
/**
* Validates that tokens meet minimum requirements for fuzzy operators.
*
* @param tokens Array of search tokens
* @param operator The search operator being used
* @returns Validation result with success status and error message
*/
export function validateFuzzySearchTokens(tokens: string[], operator: string): { isValid: boolean; error?: string } {
if (!operator || typeof operator !== 'string') {
return {
isValid: false,
error: 'Invalid operator: operator must be a non-empty string'
};
}
if (!Array.isArray(tokens)) {
return {
isValid: false,
error: 'Invalid tokens: tokens must be an array'
};
}
if (tokens.length === 0) {
return {
isValid: false,
error: 'Invalid tokens: at least one token is required'
};
}
// Check for null, undefined, or non-string tokens
const invalidTypeTokens = tokens.filter(token =>
token == null || typeof token !== 'string'
);
if (invalidTypeTokens.length > 0) {
return {
isValid: false,
error: 'Invalid tokens: all tokens must be non-null strings'
};
}
// Check for empty string tokens
const emptyTokens = tokens.filter(token => token.trim().length === 0);
if (emptyTokens.length > 0) {
return {
isValid: false,
error: 'Invalid tokens: empty or whitespace-only tokens are not allowed'
};
}
if (operator !== '~=' && operator !== '~*') {
return { isValid: true };
}
// Check minimum token length for fuzzy operators
const shortTokens = tokens.filter(token => token.length < FUZZY_SEARCH_CONFIG.MIN_FUZZY_TOKEN_LENGTH);
if (shortTokens.length > 0) {
return {
isValid: false,
error: `Fuzzy search operators (~=, ~*) require tokens of at least ${FUZZY_SEARCH_CONFIG.MIN_FUZZY_TOKEN_LENGTH} characters. Invalid tokens: ${shortTokens.join(', ')}`
};
}
// Check for excessively long tokens that could cause performance issues
const maxTokenLength = 100; // Reasonable limit for search tokens
const longTokens = tokens.filter(token => token.length > maxTokenLength);
if (longTokens.length > 0) {
return {
isValid: false,
error: `Tokens are too long (max ${maxTokenLength} characters). Long tokens: ${longTokens.map(t => t.substring(0, 20) + '...').join(', ')}`
};
}
return { isValid: true };
}
/**
* Validates and preprocesses content for search operations.
* Philosophy: Try to search everything! Only block truly extreme cases that could crash the system.
*
* @param content The content to validate and preprocess
* @param noteId The note ID (for logging purposes)
* @returns Processed content, only null for truly extreme cases that could cause system instability
*/
export function validateAndPreprocessContent(content: string, noteId?: string): string | null {
if (!content || typeof content !== 'string') {
return null;
}
// Only block content that could actually crash the system (100MB+)
if (content.length > FUZZY_SEARCH_CONFIG.ABSOLUTE_MAX_CONTENT_SIZE) {
console.error(`Content size exceeds absolute system limit for note ${noteId || 'unknown'}: ${content.length} bytes - this could cause system instability`);
// Only in truly extreme cases, truncate to prevent system crash
return content.substring(0, FUZZY_SEARCH_CONFIG.ABSOLUTE_MAX_CONTENT_SIZE);
}
// Warn about very large content but still process it
if (content.length > FUZZY_SEARCH_CONFIG.PERFORMANCE_WARNING_SIZE) {
console.info(`Large content for note ${noteId || 'unknown'}: ${content.length} bytes - processing may take time but will attempt full search`);
}
// For word count, be even more permissive - only block truly extreme cases
const wordCount = content.split(/\s+/).length;
if (wordCount > FUZZY_SEARCH_CONFIG.ABSOLUTE_MAX_WORD_COUNT) {
console.error(`Word count exceeds absolute system limit for note ${noteId || 'unknown'}: ${wordCount} words - this could cause system instability`);
// Only in truly extreme cases, truncate to prevent system crash
return content.split(/\s+/).slice(0, FUZZY_SEARCH_CONFIG.ABSOLUTE_MAX_WORD_COUNT).join(' ');
}
// Warn about high word counts but still process them
if (wordCount > FUZZY_SEARCH_CONFIG.PERFORMANCE_WARNING_WORDS) {
console.info(`High word count for note ${noteId || 'unknown'}: ${wordCount} words - phrase matching may take time but will attempt full search`);
}
// Progressive processing warning for very large content
if (content.length > FUZZY_SEARCH_CONFIG.PROGRESSIVE_PROCESSING_SIZE || wordCount > FUZZY_SEARCH_CONFIG.PROGRESSIVE_PROCESSING_WORDS) {
console.info(`Very large content for note ${noteId || 'unknown'} - using progressive processing to maintain responsiveness`);
}
return content;
}
/**
* Escapes special regex characters in a string for use in RegExp constructor
*/
function escapeRegExp(string: string): string {
return string.replace(/[.*+?^${}()|[\]\\]/g, '\\$&');
}
/**
* Checks if a word matches a token with fuzzy matching and returns the matched word.
* Optimized for common case where distances are small.
*
* @param token The search token (should be normalized)
* @param text The text to match against (should be normalized)
* @param maxDistance Maximum allowed edit distance
* @returns The matched word if found, null otherwise
*/
export function fuzzyMatchWordWithResult(token: string, text: string, maxDistance: number = FUZZY_SEARCH_CONFIG.MAX_EDIT_DISTANCE): string | null {
// Input validation
if (typeof token !== 'string' || typeof text !== 'string') {
return null;
}
if (token.length === 0 || text.length === 0) {
return null;
}
try {
// Normalize both strings for comparison
const normalizedToken = token.toLowerCase();
const normalizedText = text.toLowerCase();
// Exact match check first (most common case)
if (normalizedText.includes(normalizedToken)) {
// Find the exact match in the original text to preserve case
const exactMatch = text.match(new RegExp(escapeRegExp(token), 'i'));
return exactMatch ? exactMatch[0] : token;
}
// For fuzzy matching, we need to check individual words in the text
// Split the text into words and check each word against the token
const words = normalizedText.split(/\s+/).filter(word => word.length > 0);
const originalWords = text.split(/\s+/).filter(word => word.length > 0);
for (let i = 0; i < words.length; i++) {
const word = words[i];
const originalWord = originalWords[i];
// Skip if word is too different in length for fuzzy matching
if (Math.abs(word.length - normalizedToken.length) > maxDistance) {
continue;
}
// For very short tokens or very different lengths, be more strict
if (normalizedToken.length < 4 || Math.abs(word.length - normalizedToken.length) > 2) {
continue;
}
// Use optimized edit distance calculation
const distance = calculateOptimizedEditDistance(normalizedToken, word, maxDistance);
if (distance <= maxDistance) {
return originalWord; // Return the original word with case preserved
}
}
return null;
} catch (error) {
// Log error and return null for safety
console.warn('Error in fuzzy word matching:', error);
return null;
}
}
/**
* Checks if a word matches a token with fuzzy matching.
* Optimized for common case where distances are small.
*
* @param token The search token (should be normalized)
* @param word The word to match against (should be normalized)
* @param maxDistance Maximum allowed edit distance
* @returns True if the word matches the token within the distance threshold
*/
export function fuzzyMatchWord(token: string, text: string, maxDistance: number = FUZZY_SEARCH_CONFIG.MAX_EDIT_DISTANCE): boolean {
return fuzzyMatchWordWithResult(token, text, maxDistance) !== null;
}