Implements Phase 1.5 (Comprehensive MIME Type Detection) and adds built-in image processing support to IntelligentImportAugmentation. **New Features:** - ImageHandler: Extracts image metadata (dimensions, format, color space) using sharp - EXIF extraction: Camera data, GPS, timestamps using exifr library - Support for JPEG, PNG, WebP, GIF, TIFF, BMP, SVG, HEIC, AVIF formats - MimeTypeDetector: Unified MIME type detection with magic byte support - FormatDetector: Enhanced with image format detection via MIME + magic bytes **Architecture Fixes:** - Fixed brain.import() augmentation pipeline integration (src/brainy.ts:3140-3154) - Added parameter spreading for ImportSource objects to enable augmentation access - Fixed metadata propagation through ImportCoordinator to final results - Added augmentation data check in ImportCoordinator.extract() **Integration:** - ImageHandler registered as built-in handler alongside CSV, Excel, PDF - Images import as 'media' entities with 'image' subtype - Full metadata preserved in knowledge graph entities - Configuration options: enableImage, extractEXIF, imageDefaults **Test Coverage:** - 15 integration tests (image-import.test.ts) - 100% passing - 27 unit tests (image-handler.test.ts) - 100% passing - Format detection tests for all supported image types - Error handling and resilience tests **Breaking Changes:** None - backward compatible Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
204 lines
5.6 KiB
TypeScript
204 lines
5.6 KiB
TypeScript
/**
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* Base Format Handler
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* Abstract class providing common functionality for all format handlers
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*
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* Uses MimeTypeDetector for comprehensive file type detection (2000+ types)
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*/
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import { FormatHandler, FormatHandlerOptions, ProcessedData } from '../types.js'
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import { mimeDetector } from '../../../vfs/MimeTypeDetector.js'
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export abstract class BaseFormatHandler implements FormatHandler {
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abstract readonly format: string
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abstract process(data: Buffer | string, options: FormatHandlerOptions): Promise<ProcessedData>
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abstract canHandle(data: Buffer | string | { filename?: string, ext?: string }): boolean
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/**
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* Detect file extension from various inputs
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*/
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protected detectExtension(data: Buffer | string | { filename?: string, ext?: string }): string | null {
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if (typeof data === 'object' && 'filename' in data && data.filename) {
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return this.getExtension(data.filename)
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}
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if (typeof data === 'object' && 'ext' in data && data.ext) {
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return data.ext.toLowerCase().replace(/^\./, '')
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}
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return null
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}
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/**
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* Extract extension from filename
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*/
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protected getExtension(filename: string): string {
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const match = filename.match(/\.([^.]+)$/)
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return match ? match[1].toLowerCase() : ''
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}
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/**
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* Get MIME type using MimeTypeDetector
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*
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* Supports 2000+ file types via mime library + custom developer types
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*/
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protected getMimeType(data: Buffer | string | { filename?: string }): string {
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if (typeof data === 'object' && 'filename' in data && data.filename) {
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return mimeDetector.detectMimeType(data.filename)
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}
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if (Buffer.isBuffer(data)) {
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// For buffers, we don't have a filename, so return generic
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return 'application/octet-stream'
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}
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return 'text/plain'
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}
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/**
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* Check if MIME type matches expected format
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*
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* @param mimeType - MIME type to check
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* @param patterns - Patterns to match (e.g., ['text/csv', 'application/vnd.ms-excel'])
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*/
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protected mimeTypeMatches(mimeType: string, patterns: string[]): boolean {
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return patterns.some(pattern => {
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if (pattern.endsWith('/*')) {
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const prefix = pattern.slice(0, -2)
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return mimeType.startsWith(prefix)
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}
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return mimeType === pattern
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})
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}
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/**
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* Infer field types from data
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* Analyzes multiple rows to determine the most appropriate type
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*/
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protected inferFieldTypes(data: Array<Record<string, any>>): Record<string, string> {
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if (data.length === 0) return {}
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const types: Record<string, string> = {}
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const firstRow = data[0]
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const sampleSize = Math.min(10, data.length)
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for (const key of Object.keys(firstRow)) {
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// Check first few rows to get more accurate type
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const sampleTypes = new Set<string>()
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for (let i = 0; i < sampleSize; i++) {
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const value = data[i][key]
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const type = this.inferType(value)
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sampleTypes.add(type)
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}
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// If we see both integer and float, use float
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if (sampleTypes.has('float') || (sampleTypes.has('integer') && sampleTypes.has('float'))) {
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types[key] = 'float'
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} else if (sampleTypes.has('integer')) {
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types[key] = 'integer'
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} else if (sampleTypes.has('date')) {
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types[key] = 'date'
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} else if (sampleTypes.has('boolean')) {
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types[key] = 'boolean'
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} else {
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types[key] = 'string'
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}
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}
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return types
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}
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/**
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* Infer type of a single value
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*/
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protected inferType(value: any): string {
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if (value === null || value === undefined || value === '') return 'string'
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if (typeof value === 'number') return 'number'
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if (typeof value === 'boolean') return 'boolean'
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if (typeof value === 'string') {
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// Check if it's a number
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if (/^-?\d+$/.test(value)) return 'integer'
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if (/^-?\d+\.\d+$/.test(value)) return 'float'
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// Check if it's a date
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if (this.isDateString(value)) return 'date'
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// Check if it's a boolean
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if (/^(true|false|yes|no|y|n)$/i.test(value)) return 'boolean'
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}
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return 'string'
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}
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/**
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* Check if string looks like a date
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*/
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protected isDateString(value: string): boolean {
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// ISO 8601
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if (/^\d{4}-\d{2}-\d{2}/.test(value)) return true
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// Common date formats
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if (/^\d{1,2}\/\d{1,2}\/\d{2,4}$/.test(value)) return true
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if (/^\d{1,2}-\d{1,2}-\d{2,4}$/.test(value)) return true
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return false
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}
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/**
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* Sanitize field names for use as object keys
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*/
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protected sanitizeFieldName(name: string): string {
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return name
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.trim()
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.replace(/[^a-zA-Z0-9_\s-]/g, '')
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.replace(/\s+/g, '_')
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.replace(/-+/g, '_')
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.replace(/_+/g, '_')
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.replace(/^_|_$/g, '')
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|| 'field'
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}
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/**
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* Convert value to appropriate type
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*/
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protected convertValue(value: any, type: string): any {
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if (value === null || value === undefined || value === '') return null
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switch (type) {
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case 'integer':
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return parseInt(String(value), 10)
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case 'float':
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case 'number':
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return parseFloat(String(value))
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case 'boolean':
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if (typeof value === 'boolean') return value
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const str = String(value).toLowerCase()
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return ['true', 'yes', 'y', '1'].includes(str)
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case 'date':
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return new Date(value)
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default:
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return value
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}
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}
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/**
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* Create metadata object with common fields
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*/
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protected createMetadata(
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rowCount: number,
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fields: string[],
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processingTime: number,
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extra: Record<string, any> = {}
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): ProcessedData['metadata'] {
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return {
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rowCount,
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fields,
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processingTime,
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...extra
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}
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}
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}
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