import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeOutputsValue, INodeParams } from '../../../src/Interface' import { S3Loader } from '@langchain/community/document_loaders/web/s3' import { UnstructuredLoader, UnstructuredLoaderOptions, UnstructuredLoaderStrategy, SkipInferTableTypes, HiResModelName } from '@langchain/community/document_loaders/fs/unstructured' import { getCredentialData, getCredentialParam, handleDocumentLoaderDocuments, handleDocumentLoaderMetadata, handleDocumentLoaderOutput } from '../../../src/utils' import { S3Client, GetObjectCommand, HeadObjectCommand, S3ClientConfig } from '@aws-sdk/client-s3' import { getRegions, MODEL_TYPE } from '../../../src/modelLoader' import { Readable } from 'node:stream' import * as fsDefault from 'node:fs' import * as path from 'node:path' import * as os from 'node:os' import { PDFLoader } from '@langchain/community/document_loaders/fs/pdf' import { DocxLoader } from '@langchain/community/document_loaders/fs/docx' import { CSVLoader } from '@langchain/community/document_loaders/fs/csv' import { LoadOfSheet } from '../MicrosoftExcel/ExcelLoader' import { PowerpointLoader } from '../MicrosoftPowerpoint/PowerpointLoader' import { TextSplitter } from 'langchain/text_splitter' import { IDocument } from '../../../src/Interface' import { omit } from 'lodash' import { handleEscapeCharacters } from '../../../src' class S3_DocumentLoaders implements INode { label: string name: string version: number description: string type: string icon: string category: string baseClasses: string[] credential: INodeParams inputs?: INodeParams[] outputs: INodeOutputsValue[] constructor() { this.label = 'S3' this.name = 'S3' this.version = 5.0 this.type = 'Document' this.icon = 's3.svg' this.category = 'Document Loaders' this.description = 'Load Data from S3 Buckets' this.baseClasses = [this.type] this.credential = { label: 'AWS Credential', name: 'credential', type: 'credential', credentialNames: ['awsApi'], optional: true } this.inputs = [ { label: 'Bucket', name: 'bucketName', type: 'string' }, { label: 'Object Key', name: 'keyName', type: 'string', description: 'The object key (or key name) that uniquely identifies object in an Amazon S3 bucket', placeholder: 'AI-Paper.pdf' }, { label: 'Region', name: 'region', type: 'asyncOptions', loadMethod: 'listRegions', default: 'us-east-1' }, { label: 'File Processing Method', name: 'fileProcessingMethod', type: 'options', options: [ { label: 'Built In Loaders', name: 'builtIn', description: 'Use the built in loaders to process the file.' }, { label: 'Unstructured', name: 'unstructured', description: 'Use the Unstructured API to process the file.' } ], default: 'builtIn' }, { label: 'Text Splitter', name: 'textSplitter', type: 'TextSplitter', optional: true, show: { fileProcessingMethod: 'builtIn' } }, { label: 'Additional Metadata', name: 'metadata', type: 'json', description: 'Additional metadata to be added to the extracted documents', optional: true, additionalParams: true }, { label: 'Omit Metadata Keys', name: 'omitMetadataKeys', type: 'string', rows: 4, description: 'Each document loader comes with a default set of metadata keys that are extracted from the document. You can use this field to omit some of the default metadata keys. The value should be a list of keys, seperated by comma. Use * to omit all metadata keys execept the ones you specify in the Additional Metadata field', placeholder: 'key1, key2, key3.nestedKey1', optional: true, additionalParams: true }, { label: 'Unstructured API URL', name: 'unstructuredAPIUrl', description: 'Your Unstructured.io URL. Read more on how to get started', type: 'string', placeholder: process.env.UNSTRUCTURED_API_URL || 'http://localhost:8000/general/v0/general', optional: !!process.env.UNSTRUCTURED_API_URL, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Unstructured API KEY', name: 'unstructuredAPIKey', type: 'password', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Strategy', name: 'strategy', description: 'The strategy to use for partitioning PDF/image. Options are fast, hi_res, auto. Default: auto.', type: 'options', options: [ { label: 'Hi-Res', name: 'hi_res' }, { label: 'Fast', name: 'fast' }, { label: 'OCR Only', name: 'ocr_only' }, { label: 'Auto', name: 'auto' } ], optional: true, additionalParams: true, default: 'auto', show: { fileProcessingMethod: 'unstructured' } }, { label: 'Encoding', name: 'encoding', description: 'The encoding method used to decode the text input. Default: utf-8.', type: 'string', optional: true, additionalParams: true, default: 'utf-8', show: { fileProcessingMethod: 'unstructured' } }, { label: 'Skip Infer Table Types', name: 'skipInferTableTypes', description: 'The document types that you want to skip table extraction with. Default: pdf, jpg, png.', type: 'multiOptions', options: [ { label: 'doc', name: 'doc' }, { label: 'docx', name: 'docx' }, { label: 'eml', name: 'eml' }, { label: 'epub', name: 'epub' }, { label: 'heic', name: 'heic' }, { label: 'htm', name: 'htm' }, { label: 'html', name: 'html' }, { label: 'jpeg', name: 'jpeg' }, { label: 'jpg', name: 'jpg' }, { label: 'md', name: 'md' }, { label: 'msg', name: 'msg' }, { label: 'odt', name: 'odt' }, { label: 'pdf', name: 'pdf' }, { label: 'png', name: 'png' }, { label: 'ppt', name: 'ppt' }, { label: 'pptx', name: 'pptx' }, { label: 'rtf', name: 'rtf' }, { label: 'text', name: 'text' }, { label: 'txt', name: 'txt' }, { label: 'xls', name: 'xls' }, { label: 'xlsx', name: 'xlsx' } ], optional: true, additionalParams: true, default: '["pdf", "jpg", "png"]', show: { fileProcessingMethod: 'unstructured' } }, { label: 'Hi-Res Model Name', name: 'hiResModelName', description: 'The name of the inference model used when strategy is hi_res. Default: detectron2_onnx.', type: 'options', options: [ { label: 'chipper', name: 'chipper', description: 'Exlusive to Unstructured hosted API. The Chipper model is Unstructured in-house image-to-text model based on transformer-based Visual Document Understanding (VDU) models.' }, { label: 'detectron2_onnx', name: 'detectron2_onnx', description: 'A Computer Vision model by Facebook AI that provides object detection and segmentation algorithms with ONNX Runtime. It is the fastest model with the hi_res strategy.' }, { label: 'yolox', name: 'yolox', description: 'A single-stage real-time object detector that modifies YOLOv3 with a DarkNet53 backbone.' }, { label: 'yolox_quantized', name: 'yolox_quantized', description: 'Runs faster than YoloX and its speed is closer to Detectron2.' } ], optional: true, additionalParams: true, default: 'detectron2_onnx', show: { fileProcessingMethod: 'unstructured' } }, { label: 'Chunking Strategy', name: 'chunkingStrategy', description: 'Use one of the supported strategies to chunk the returned elements. When omitted, no chunking is performed and any other chunking parameters provided are ignored. Default: by_title', type: 'options', options: [ { label: 'None', name: 'None' }, { label: 'By Title', name: 'by_title' } ], optional: true, additionalParams: true, default: 'by_title', show: { fileProcessingMethod: 'unstructured' } }, { label: 'OCR Languages', name: 'ocrLanguages', description: 'The languages to use for OCR. Note: Being depricated as languages is the new type. Pending langchain update.', type: 'multiOptions', options: [ { label: 'English', name: 'eng' }, { label: 'Spanish (Español)', name: 'spa' }, { label: 'Mandarin Chinese (普通话)', name: 'cmn' }, { label: 'Hindi (हिन्दी)', name: 'hin' }, { label: 'Arabic (اَلْعَرَبِيَّةُ)', name: 'ara' }, { label: 'Portuguese (Português)', name: 'por' }, { label: 'Bengali (বাংলা)', name: 'ben' }, { label: 'Russian (Русский)', name: 'rus' }, { label: 'Japanese (日本語)', name: 'jpn' }, { label: 'Punjabi (ਪੰਜਾਬੀ)', name: 'pan' }, { label: 'German (Deutsch)', name: 'deu' }, { label: 'Korean (한국어)', name: 'kor' }, { label: 'French (Français)', name: 'fra' }, { label: 'Italian (Italiano)', name: 'ita' }, { label: 'Vietnamese (Tiếng Việt)', name: 'vie' } ], optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Source ID Key', name: 'sourceIdKey', type: 'string', description: 'Key used to get the true source of document, to be compared against the record. Document metadata must contain the Source ID Key.', default: 'source', placeholder: 'source', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Coordinates', name: 'coordinates', type: 'boolean', description: 'If true, return coordinates for each element. Default: false.', optional: true, additionalParams: true, default: false, show: { fileProcessingMethod: 'unstructured' } }, { label: 'XML Keep Tags', name: 'xmlKeepTags', description: 'If True, will retain the XML tags in the output. Otherwise it will simply extract the text from within the tags. Only applies to partition_xml.', type: 'boolean', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Include Page Breaks', name: 'includePageBreaks', description: 'When true, the output will include page break elements when the filetype supports it.', type: 'boolean', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Multi-Page Sections', name: 'multiPageSections', description: 'Whether to treat multi-page documents as separate sections.', type: 'boolean', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Combine Under N Chars', name: 'combineUnderNChars', description: "If chunking strategy is set, combine elements until a section reaches a length of n chars. Default: value of max_characters. Can't exceed value of max_characters.", type: 'number', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'New After N Chars', name: 'newAfterNChars', description: "If chunking strategy is set, cut off new sections after reaching a length of n chars (soft max). value of max_characters. Can't exceed value of max_characters.", type: 'number', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Max Characters', name: 'maxCharacters', description: 'If chunking strategy is set, cut off new sections after reaching a length of n chars (hard max). Default: 500', type: 'number', optional: true, additionalParams: true, default: '500', show: { fileProcessingMethod: 'unstructured' } }, { label: 'Additional Metadata', name: 'metadata', type: 'json', description: 'Additional metadata to be added to the extracted documents', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } }, { label: 'Omit Metadata Keys', name: 'omitMetadataKeys', type: 'string', rows: 4, description: 'Each document loader comes with a default set of metadata keys that are extracted from the document. You can use this field to omit some of the default metadata keys. The value should be a list of keys, seperated by comma. Use * to omit all metadata keys execept the ones you specify in the Additional Metadata field', placeholder: 'key1, key2, key3.nestedKey1', optional: true, additionalParams: true, show: { fileProcessingMethod: 'unstructured' } } ] this.outputs = [ { label: 'Document', name: 'document', description: 'Array of document objects containing metadata and pageContent', baseClasses: [...this.baseClasses, 'json'] }, { label: 'Text', name: 'text', description: 'Concatenated string from pageContent of documents', baseClasses: ['string', 'json'] } ] } loadMethods = { async listRegions(): Promise { return await getRegions(MODEL_TYPE.CHAT, 'awsChatBedrock') } } async init(nodeData: INodeData, _: string, options: ICommonObject): Promise { const bucketName = nodeData.inputs?.bucketName as string const keyName = nodeData.inputs?.keyName as string const region = nodeData.inputs?.region as string const fileProcessingMethod = nodeData.inputs?.fileProcessingMethod as string const textSplitter = nodeData.inputs?.textSplitter as TextSplitter const metadata = nodeData.inputs?.metadata const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string const output = nodeData.outputs?.output as string let omitMetadataKeys: string[] = [] if (_omitMetadataKeys) { omitMetadataKeys = _omitMetadataKeys.split(',').map((key) => key.trim()) } let credentials: S3ClientConfig['credentials'] | undefined if (nodeData.credential) { const credentialData = await getCredentialData(nodeData.credential, options) const accessKeyId = getCredentialParam('awsKey', credentialData, nodeData) const secretAccessKey = getCredentialParam('awsSecret', credentialData, nodeData) if (accessKeyId && secretAccessKey) { credentials = { accessKeyId, secretAccessKey } } } const s3Config: S3ClientConfig = { region, credentials } if (fileProcessingMethod === 'builtIn') { return await this.processWithBuiltInLoaders( bucketName, keyName, s3Config, textSplitter, metadata, omitMetadataKeys, _omitMetadataKeys, output ) } else { return await this.processWithUnstructured(nodeData, options, bucketName, keyName, s3Config) } } private async processWithBuiltInLoaders( bucketName: string, keyName: string, s3Config: S3ClientConfig, textSplitter: TextSplitter, metadata: any, omitMetadataKeys: string[], _omitMetadataKeys: string, output: string ): Promise { let docs: IDocument[] = [] try { const s3Client = new S3Client(s3Config) // Get file metadata to determine content type const headCommand = new HeadObjectCommand({ Bucket: bucketName, Key: keyName }) const headResponse = await s3Client.send(headCommand) const contentType = headResponse.ContentType || this.getMimeTypeFromExtension(keyName) // Download the file const getObjectCommand = new GetObjectCommand({ Bucket: bucketName, Key: keyName }) const response = await s3Client.send(getObjectCommand) const objectData = await new Promise((resolve, reject) => { const chunks: Buffer[] = [] if (response.Body instanceof Readable) { response.Body.on('data', (chunk: Buffer) => chunks.push(chunk)) response.Body.on('end', () => resolve(Buffer.concat(chunks))) response.Body.on('error', reject) } else { reject(new Error('Response body is not a readable stream.')) } }) // Process the file based on content type const fileInfo = { id: keyName, name: path.basename(keyName), mimeType: contentType, size: objectData.length, webViewLink: `s3://${bucketName}/${keyName}`, bucketName: bucketName, key: keyName, lastModified: headResponse.LastModified, etag: headResponse.ETag } docs = await this.processFile(fileInfo, objectData) // Apply text splitter if provided if (textSplitter && docs.length > 0) { docs = await textSplitter.splitDocuments(docs) } // Apply metadata transformations if (metadata) { const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata) docs = docs.map((doc) => ({ ...doc, metadata: _omitMetadataKeys === '*' ? { ...parsedMetadata } : omit( { ...doc.metadata, ...parsedMetadata }, omitMetadataKeys ) })) } else { docs = docs.map((doc) => ({ ...doc, metadata: _omitMetadataKeys === '*' ? {} : omit( { ...doc.metadata }, omitMetadataKeys ) })) } } catch (error) { throw new Error(`Failed to load S3 document: ${error.message}`) } if (output === 'document') { return docs } else { let finaltext = '' for (const doc of docs) { finaltext += `${doc.pageContent}\n` } return handleEscapeCharacters(finaltext, false) } } private async processWithUnstructured( nodeData: INodeData, options: ICommonObject, bucketName: string, keyName: string, s3Config: S3ClientConfig ): Promise { const unstructuredAPIUrl = nodeData.inputs?.unstructuredAPIUrl as string const unstructuredAPIKey = nodeData.inputs?.unstructuredAPIKey as string const strategy = nodeData.inputs?.strategy as UnstructuredLoaderStrategy const encoding = nodeData.inputs?.encoding as string const coordinates = nodeData.inputs?.coordinates as boolean const skipInferTableTypes = nodeData.inputs?.skipInferTableTypes ? JSON.parse(nodeData.inputs?.skipInferTableTypes as string) : ([] as SkipInferTableTypes[]) const hiResModelName = nodeData.inputs?.hiResModelName as HiResModelName const includePageBreaks = nodeData.inputs?.includePageBreaks as boolean const chunkingStrategy = nodeData.inputs?.chunkingStrategy as 'None' | 'by_title' const metadata = nodeData.inputs?.metadata const sourceIdKey = (nodeData.inputs?.sourceIdKey as string) || 'source' const ocrLanguages = nodeData.inputs?.ocrLanguages ? JSON.parse(nodeData.inputs?.ocrLanguages as string) : ([] as string[]) const xmlKeepTags = nodeData.inputs?.xmlKeepTags as boolean const multiPageSections = nodeData.inputs?.multiPageSections as boolean const combineUnderNChars = nodeData.inputs?.combineUnderNChars as number const newAfterNChars = nodeData.inputs?.newAfterNChars as number const maxCharacters = nodeData.inputs?.maxCharacters as number const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string const output = nodeData.outputs?.output as string const loader = new S3Loader({ bucket: bucketName, key: keyName, s3Config, unstructuredAPIURL: unstructuredAPIUrl, unstructuredAPIKey: unstructuredAPIKey }) loader.load = async () => { const tempDir = fsDefault.mkdtempSync(path.join(os.tmpdir(), 's3fileloader-')) const filePath = path.join(tempDir, keyName) try { const s3Client = new S3Client(s3Config) const getObjectCommand = new GetObjectCommand({ Bucket: bucketName, Key: keyName }) const response = await s3Client.send(getObjectCommand) const objectData = await new Promise((resolve, reject) => { const chunks: Buffer[] = [] if (response.Body instanceof Readable) { response.Body.on('data', (chunk: Buffer) => chunks.push(chunk)) response.Body.on('end', () => resolve(Buffer.concat(chunks))) response.Body.on('error', reject) } else { reject(new Error('Response body is not a readable stream.')) } }) fsDefault.mkdirSync(path.dirname(filePath), { recursive: true }) fsDefault.writeFileSync(filePath, objectData) } catch (e: any) { throw new Error(`Failed to download file ${keyName} from S3 bucket ${bucketName}: ${e.message}`) } try { const obj: UnstructuredLoaderOptions = { apiUrl: unstructuredAPIUrl, strategy, encoding, coordinates, skipInferTableTypes, hiResModelName, includePageBreaks, chunkingStrategy, ocrLanguages, xmlKeepTags, multiPageSections, combineUnderNChars, newAfterNChars, maxCharacters } if (unstructuredAPIKey) obj.apiKey = unstructuredAPIKey const unstructuredLoader = new UnstructuredLoader(filePath, obj) let docs = await handleDocumentLoaderDocuments(unstructuredLoader) docs = handleDocumentLoaderMetadata(docs, _omitMetadataKeys, metadata, sourceIdKey) return handleDocumentLoaderOutput(docs, output) } catch { throw new Error(`Failed to load file ${filePath} using unstructured loader.`) } finally { fsDefault.rmSync(path.dirname(filePath), { recursive: true }) } } return loader.load() } private getMimeTypeFromExtension(fileName: string): string { const extension = path.extname(fileName).toLowerCase() const mimeTypeMap: { [key: string]: string } = { '.pdf': 'application/pdf', '.docx': 'application/vnd.openxmlformats-officedocument.wordprocessingml.document', '.doc': 'application/msword', '.xlsx': 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', '.xls': 'application/vnd.ms-excel', '.pptx': 'application/vnd.openxmlformats-officedocument.presentationml.presentation', '.ppt': 'application/vnd.ms-powerpoint', '.txt': 'text/plain', '.csv': 'text/csv', '.html': 'text/html', '.htm': 'text/html', '.json': 'application/json', '.xml': 'application/xml', '.md': 'text/markdown' } return mimeTypeMap[extension] || 'application/octet-stream' } private async processFile(fileInfo: any, buffer: Buffer): Promise { try { // Handle different file types if (this.isTextBasedFile(fileInfo.mimeType)) { // Process text files directly from buffer const content = buffer.toString('utf-8') // Create document with metadata return [ { pageContent: content, metadata: { source: fileInfo.webViewLink, fileId: fileInfo.key, fileName: fileInfo.name, mimeType: fileInfo.mimeType, size: fileInfo.size, lastModified: fileInfo.lastModified, etag: fileInfo.etag, bucketName: fileInfo.bucketName } } ] } else if (this.isSupportedBinaryFile(fileInfo.mimeType)) { // Process binary files using loaders return await this.processBinaryFile(fileInfo, buffer) } else { console.warn(`Unsupported file type ${fileInfo.mimeType} for file ${fileInfo.name}`) return [] } } catch (error) { console.warn(`Failed to process file ${fileInfo.name}: ${error.message}`) return [] } } private isTextBasedFile(mimeType: string): boolean { const textBasedMimeTypes = [ 'text/plain', 'text/html', 'text/css', 'text/javascript', 'text/csv', 'text/xml', 'application/json', 'application/xml', 'text/markdown', 'text/x-markdown' ] return textBasedMimeTypes.includes(mimeType) } private isSupportedBinaryFile(mimeType: string): boolean { const supportedBinaryTypes = [ 'application/pdf', 'application/vnd.openxmlformats-officedocument.wordprocessingml.document', 'application/msword', 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet', 'application/vnd.ms-excel', 'application/vnd.openxmlformats-officedocument.presentationml.presentation', 'application/vnd.ms-powerpoint' ] return supportedBinaryTypes.includes(mimeType) } private async processBinaryFile(fileInfo: any, buffer: Buffer): Promise { let tempFilePath: string | null = null try { // Create temporary file tempFilePath = await this.createTempFile(buffer, fileInfo.name, fileInfo.mimeType) let docs: IDocument[] = [] const mimeType = fileInfo.mimeType.toLowerCase() switch (mimeType) { case 'application/pdf': { const pdfLoader = new PDFLoader(tempFilePath, { // @ts-ignore pdfjs: () => import('pdf-parse/lib/pdf.js/v1.10.100/build/pdf.js') }) docs = await pdfLoader.load() break } case 'application/vnd.openxmlformats-officedocument.wordprocessingml.document': case 'application/msword': { const docxLoader = new DocxLoader(tempFilePath) docs = await docxLoader.load() break } case 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': case 'application/vnd.ms-excel': { const excelLoader = new LoadOfSheet(tempFilePath) docs = await excelLoader.load() break } case 'application/vnd.openxmlformats-officedocument.presentationml.presentation': case 'application/vnd.ms-powerpoint': { const pptxLoader = new PowerpointLoader(tempFilePath) docs = await pptxLoader.load() break } case 'text/csv': { const csvLoader = new CSVLoader(tempFilePath) docs = await csvLoader.load() break } default: throw new Error(`Unsupported binary file type: ${mimeType}`) } // Add S3 metadata to each document if (docs.length > 0) { const s3Metadata = { source: fileInfo.webViewLink, fileId: fileInfo.key, fileName: fileInfo.name, mimeType: fileInfo.mimeType, size: fileInfo.size, lastModified: fileInfo.lastModified, etag: fileInfo.etag, bucketName: fileInfo.bucketName, totalPages: docs.length // Total number of pages/sheets in the file } return docs.map((doc, index) => ({ ...doc, metadata: { ...doc.metadata, // Keep original loader metadata (page numbers, etc.) ...s3Metadata, // Add S3 metadata pageIndex: index // Add page/sheet index } })) } return [] } catch (error) { throw new Error(`Failed to process binary file: ${error.message}`) } finally { // Clean up temporary file if (tempFilePath && fsDefault.existsSync(tempFilePath)) { try { fsDefault.unlinkSync(tempFilePath) } catch (e) { console.warn(`Failed to delete temporary file: ${tempFilePath}`) } } } } private async createTempFile(buffer: Buffer, fileName: string, mimeType: string): Promise { // Get appropriate file extension let extension = path.extname(fileName) if (!extension) { const extensionMap: { [key: string]: string } = { 'application/pdf': '.pdf', 'application/vnd.openxmlformats-officedocument.wordprocessingml.document': '.docx', 'application/msword': '.doc', 'application/vnd.openxmlformats-officedocument.spreadsheetml.sheet': '.xlsx', 'application/vnd.ms-excel': '.xls', 'application/vnd.openxmlformats-officedocument.presentationml.presentation': '.pptx', 'application/vnd.ms-powerpoint': '.ppt', 'text/csv': '.csv' } extension = extensionMap[mimeType] || '.tmp' } // Create temporary file const tempDir = os.tmpdir() const tempFileName = `s3_${Date.now()}_${Math.random().toString(36).substring(7)}${extension}` const tempFilePath = path.join(tempDir, tempFileName) fsDefault.writeFileSync(tempFilePath, buffer) return tempFilePath } } module.exports = { nodeClass: S3_DocumentLoaders }