claude-playwright/dist/core/smart-normalizer.cjs.map

Seamless integration between Claude Code and Playwright MCP for efficient browser automation and testing

{"version":3,"sources":["../../src/core/smart-normalizer.ts"],"sourcesContent":["import crypto from 'crypto';\n\ninterface PositionalKeyword {\n  word: string;\n  position: number;\n  context?: string;\n}\n\ninterface InputFeatures {\n  hasId: boolean;\n  hasClass: boolean;\n  hasQuoted: boolean;\n  numbers: string[];\n  positions: PositionalKeyword[];\n  attributes: string[];\n  wordCount: number;\n  hasImperative: boolean;\n  casePattern: 'lower' | 'upper' | 'mixed' | 'title';\n  isNavigation: boolean;\n  isFormAction: boolean;\n  hasDataTestId: boolean;\n}\n\nexport interface NormalizationResult {\n  normalized: string;\n  tokens: string[];\n  positions: PositionalKeyword[];\n  features: InputFeatures;\n  hash: string;\n}\n\nexport class SmartNormalizer {\n  private readonly POSITION_KEYWORDS = [\n    'before', 'after', 'first', 'last', 'next', 'previous', \n    'above', 'below', 'top', 'bottom', 'left', 'right'\n  ];\n  \n  private readonly RELATION_KEYWORDS = [\n    'in', 'of', 'from', 'to', 'with', 'by', 'for'\n  ];\n  \n  private readonly STOP_WORDS = [\n    'the', 'a', 'an', 'and', 'or', 'but', 'at', 'on'\n  ];\n  \n  private readonly ACTION_SYNONYMS = {\n    'click': ['click', 'press', 'tap', 'hit', 'select', 'choose'],\n    'type': ['type', 'enter', 'input', 'fill', 'write'],\n    'navigate': ['go', 'navigate', 'open', 'visit', 'load'],\n    'hover': ['hover', 'mouseover', 'move']\n  };\n\n  normalize(input: string): NormalizationResult {\n    const original = input.trim();\n    const features = this.extractFeatures(original);\n    \n    // Step 1: Basic cleanup\n    let text = original.toLowerCase();\n    \n    // Step 2: Extract and preserve quoted strings\n    const quotedStrings: string[] = [];\n    text = text.replace(/([\"'])((?:(?!\\1)[^\\\\]|\\\\.)*)(\\1)/g, (match, quote, content) => {\n      quotedStrings.push(content);\n      return `QUOTED_${quotedStrings.length - 1}`;\n    });\n    \n    // Step 3: Extract positional information\n    const positions = this.extractPositions(text);\n    \n    // Step 4: Normalize actions to canonical forms\n    text = this.normalizeActions(text);\n    \n    // Step 5: Remove common patterns\n    text = this.removeCommonPatterns(text);\n    \n    // Step 6: Tokenize and filter\n    const words = text.split(/\\s+/).filter(word => word.length > 0);\n    const tokens = [];\n    const preserved = [];\n    \n    for (let i = 0; i < words.length; i++) {\n      const word = words[i];\n      \n      if (this.POSITION_KEYWORDS.includes(word)) {\n        // Preserve positional keywords with context\n        preserved.push({\n          word,\n          position: i,\n          context: words[i + 1] || null\n        });\n      } else if (!this.STOP_WORDS.includes(word) && \n                 !this.RELATION_KEYWORDS.includes(word) &&\n                 !['button', 'field', 'element'].includes(word)) {\n        tokens.push(word);\n      }\n    }\n    \n    // Step 7: Sort tokens for order-invariance (except preserved)\n    tokens.sort();\n    \n    // Step 8: Build normalized string\n    let normalized = tokens.join(' ');\n    \n    // Step 9: Add positional information\n    if (preserved.length > 0) {\n      const posInfo = preserved.map(p => \n        `${p.word}${p.context ? '-' + p.context : ''}`\n      ).join(',');\n      normalized += ` _pos:${posInfo}`;\n    }\n    \n    // Step 10: Add quoted content back\n    if (quotedStrings.length > 0) {\n      normalized += ` _quoted:${quotedStrings.join(',')}`;\n    }\n    \n    const hash = crypto.createHash('md5').update(normalized).digest('hex');\n    \n    return {\n      normalized,\n      tokens,\n      positions,\n      features,\n      hash\n    };\n  }\n\n  extractFeatures(input: string): InputFeatures {\n    const text = input.toLowerCase();\n    \n    return {\n      hasId: /#[\\w-]+/.test(input),\n      hasClass: /\\.[\\w-]+/.test(input),\n      hasQuoted: /\"[^\"]+\"|'[^']+'/.test(input),\n      numbers: (input.match(/\\d+/g) || []),\n      positions: this.extractPositions(text),\n      attributes: this.extractAttributes(input),\n      wordCount: input.split(/\\s+/).length,\n      hasImperative: /^(click|press|tap|select|enter|type|fill)/i.test(input),\n      casePattern: this.detectCasePattern(input),\n      isNavigation: /^(go|navigate|open|visit)/i.test(input),\n      isFormAction: /(submit|enter|fill|type|input)/i.test(input),\n      hasDataTestId: /data-test|testid|data-cy/i.test(input)\n    };\n  }\n\n  private extractPositions(text: string): PositionalKeyword[] {\n    const positions: PositionalKeyword[] = [];\n    const words = text.split(/\\s+/);\n    \n    for (let i = 0; i < words.length; i++) {\n      const word = words[i];\n      if (this.POSITION_KEYWORDS.includes(word)) {\n        positions.push({\n          word,\n          position: i,\n          context: words[i + 1] || words[i - 1] || undefined\n        });\n      }\n    }\n    \n    return positions;\n  }\n\n  private extractAttributes(input: string): string[] {\n    const attributes = [];\n    \n    // Extract common attribute patterns\n    const patterns = [\n      /\\[([^\\]]+)\\]/g,  // [attribute=value]\n      /data-[\\w-]+/g,   // data-testid\n      /aria-[\\w-]+/g,   // aria-label\n      /role=\"[\\w-]+\"/g, // role=\"button\"\n      /type=\"[\\w-]+\"/g, // type=\"submit\"\n      /placeholder=\"[^\"]+\"/g // placeholder=\"text\"\n    ];\n    \n    for (const pattern of patterns) {\n      const matches = input.match(pattern);\n      if (matches) {\n        attributes.push(...matches);\n      }\n    }\n    \n    return attributes;\n  }\n\n  private detectCasePattern(input: string): 'lower' | 'upper' | 'mixed' | 'title' {\n    const hasLower = /[a-z]/.test(input);\n    const hasUpper = /[A-Z]/.test(input);\n    \n    if (!hasLower && hasUpper) return 'upper';\n    if (hasLower && !hasUpper) return 'lower';\n    \n    // Check if it's title case\n    const words = input.split(/\\s+/);\n    const isTitleCase = words.every(word => \n      /^[A-Z][a-z]*$/.test(word) || /^[a-z]+$/.test(word)\n    );\n    \n    return isTitleCase ? 'title' : 'mixed';\n  }\n\n  private normalizeActions(text: string): string {\n    for (const [canonical, synonyms] of Object.entries(this.ACTION_SYNONYMS)) {\n      for (const synonym of synonyms) {\n        const regex = new RegExp(`\\\\b${synonym}\\\\b`, 'g');\n        text = text.replace(regex, canonical);\n      }\n    }\n    return text;\n  }\n\n  private removeCommonPatterns(text: string): string {\n    // Remove common prefixes and suffixes\n    text = text.replace(/^(click|press|tap)(\\s+on)?(\\s+the)?/i, 'click');\n    text = text.replace(/\\s+(button|element|field)$/i, '');\n    text = text.replace(/button\\s+/i, '');\n    \n    // Remove articles and common words\n    text = text.replace(/\\b(the|a|an)\\b/g, '');\n    \n    // Clean up punctuation\n    text = text.replace(/[^\\w\\s#._-]/g, ' ');\n    \n    // Normalize whitespace\n    text = text.replace(/\\s+/g, ' ').trim();\n    \n    return text;\n  }\n\n  // Utility methods for similarity\n  calculateSimilarity(result1: NormalizationResult, result2: NormalizationResult): number {\n    // Token-based Jaccard similarity\n    const set1 = new Set(result1.tokens);\n    const set2 = new Set(result2.tokens);\n    const intersection = new Set([...set1].filter(x => set2.has(x)));\n    const union = new Set([...set1, ...set2]);\n    \n    let similarity = intersection.size / union.size;\n    \n    // Boost for matching quoted strings\n    const quoted1 = result1.normalized.match(/_quoted:([^_]*)/)?.[1] || '';\n    const quoted2 = result2.normalized.match(/_quoted:([^_]*)/)?.[1] || '';\n    if (quoted1 === quoted2 && quoted1.length > 0) {\n      similarity += 0.2;\n    }\n    \n    // Penalty for mismatched positions\n    const pos1 = result1.normalized.match(/_pos:([^_]*)/)?.[1] || '';\n    const pos2 = result2.normalized.match(/_pos:([^_]*)/)?.[1] || '';\n    if (pos1 !== pos2 && (pos1.length > 0 || pos2.length > 0)) {\n      similarity -= 0.3;\n    }\n    \n    return Math.max(0, Math.min(1, similarity));\n  }\n\n  // Fuzzy matching for typo tolerance\n  damerauLevenshtein(a: string, b: string): number {\n    const da: { [key: string]: number } = {};\n    const maxdist = a.length + b.length;\n    const H: number[][] = [];\n    \n    H[-1] = [];\n    H[-1][-1] = maxdist;\n    \n    for (let i = 0; i <= a.length; i++) {\n      H[i] = [];\n      H[i][-1] = maxdist;\n      H[i][0] = i;\n    }\n    \n    for (let j = 0; j <= b.length; j++) {\n      H[-1][j] = maxdist;\n      H[0][j] = j;\n    }\n    \n    for (let i = 1; i <= a.length; i++) {\n      let db = 0;\n      for (let j = 1; j <= b.length; j++) {\n        const k = da[b[j - 1]] || 0;\n        const l = db;\n        let cost = 1;\n        if (a[i - 1] === b[j - 1]) {\n          cost = 0;\n          db = j;\n        }\n        \n        H[i][j] = Math.min(\n          H[i - 1][j] + 1,     // insertion\n          H[i][j - 1] + 1,     // deletion\n          H[i - 1][j - 1] + cost, // substitution\n          H[k - 1][l - 1] + (i - k - 1) + 1 + (j - l - 1) // transposition\n        );\n      }\n      da[a[i - 1]] = i;\n    }\n    \n    return H[a.length][b.length];\n  }\n\n  // Create fuzzy variations for learning\n  generateVariations(input: string): string[] {\n    const variations = [input];\n    const normalized = this.normalize(input);\n    \n    // Generate common variations\n    variations.push(input.toLowerCase());\n    variations.push(input.replace(/\\s+/g, ' ').trim());\n    variations.push(input.replace(/^(click|press)\\s+/i, 'tap '));\n    variations.push(input.replace(/\\s+button$/i, ''));\n    \n    // Token permutations (limited)\n    if (normalized.tokens.length <= 4) {\n      const permutations = this.generateTokenPermutations(normalized.tokens);\n      variations.push(...permutations.slice(0, 3)); // Limit to 3 permutations\n    }\n    \n    return [...new Set(variations)];\n  }\n\n  private generateTokenPermutations(tokens: string[]): string[] {\n    if (tokens.length <= 1) return tokens;\n    if (tokens.length > 4) return []; // Too many combinations\n    \n    const result: string[] = [];\n    const permute = (arr: string[], start = 0) => {\n      if (start === arr.length) {\n        result.push(arr.join(' '));\n        return;\n      }\n      \n      for (let i = start; i < arr.length; i++) {\n        [arr[start], arr[i]] = [arr[i], arr[start]];\n        permute(arr, start + 1);\n        [arr[start], arr[i]] = [arr[i], arr[start]]; // backtrack\n      }\n    };\n    \n    permute([...tokens]);\n    return result;\n  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