607 lines
23 KiB
TypeScript
607 lines
23 KiB
TypeScript
import { omit } from 'lodash'
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import { ICommonObject, INode, INodeData, INodeOptionsValue, INodeParams } from '../../../src/Interface'
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import { S3Loader } from 'langchain/document_loaders/web/s3'
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import {
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UnstructuredLoader,
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UnstructuredLoaderOptions,
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UnstructuredLoaderStrategy,
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SkipInferTableTypes,
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HiResModelName
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} from 'langchain/document_loaders/fs/unstructured'
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import { getCredentialData, getCredentialParam } from '../../../src/utils'
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import { S3Client, GetObjectCommand, S3ClientConfig } from '@aws-sdk/client-s3'
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import { getRegions, MODEL_TYPE } from '../../../src/modelLoader'
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import { Readable } from 'node:stream'
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import * as fsDefault from 'node:fs'
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import * as path from 'node:path'
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import * as os from 'node:os'
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class S3_DocumentLoaders implements INode {
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label: string
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name: string
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version: number
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description: string
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type: string
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icon: string
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category: string
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baseClasses: string[]
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credential: INodeParams
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inputs?: INodeParams[]
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constructor() {
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this.label = 'S3'
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this.name = 'S3'
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this.version = 3.0
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this.type = 'Document'
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this.icon = 's3.svg'
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this.category = 'Document Loaders'
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this.description = 'Load Data from S3 Buckets'
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this.baseClasses = [this.type]
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this.credential = {
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label: 'AWS Credential',
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name: 'credential',
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type: 'credential',
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credentialNames: ['awsApi'],
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optional: true
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}
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this.inputs = [
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{
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label: 'Bucket',
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name: 'bucketName',
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type: 'string'
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},
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{
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label: 'Object Key',
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name: 'keyName',
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type: 'string',
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description: 'The object key (or key name) that uniquely identifies object in an Amazon S3 bucket',
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placeholder: 'AI-Paper.pdf'
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},
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{
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label: 'Region',
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name: 'region',
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type: 'asyncOptions',
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loadMethod: 'listRegions',
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default: 'us-east-1'
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},
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{
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label: 'Unstructured API URL',
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name: 'unstructuredAPIUrl',
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description:
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'Your Unstructured.io URL. Read <a target="_blank" href="https://unstructured-io.github.io/unstructured/introduction.html#getting-started">more</a> on how to get started',
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type: 'string',
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default: 'http://localhost:8000/general/v0/general'
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},
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{
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label: 'Unstructured API KEY',
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name: 'unstructuredAPIKey',
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type: 'password',
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optional: true
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},
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{
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label: 'Strategy',
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name: 'strategy',
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description: 'The strategy to use for partitioning PDF/image. Options are fast, hi_res, auto. Default: auto.',
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type: 'options',
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options: [
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{
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label: 'Hi-Res',
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name: 'hi_res'
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},
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{
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label: 'Fast',
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name: 'fast'
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},
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{
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label: 'OCR Only',
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name: 'ocr_only'
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},
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{
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label: 'Auto',
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name: 'auto'
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}
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],
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optional: true,
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additionalParams: true,
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default: 'auto'
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},
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{
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label: 'Encoding',
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name: 'encoding',
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description: 'The encoding method used to decode the text input. Default: utf-8.',
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type: 'string',
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optional: true,
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additionalParams: true,
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default: 'utf-8'
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},
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{
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label: 'Skip Infer Table Types',
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name: 'skipInferTableTypes',
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description: 'The document types that you want to skip table extraction with. Default: pdf, jpg, png.',
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type: 'multiOptions',
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options: [
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{
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label: 'doc',
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name: 'doc'
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},
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{
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label: 'docx',
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name: 'docx'
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},
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{
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label: 'eml',
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name: 'eml'
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},
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{
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label: 'epub',
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name: 'epub'
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},
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{
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label: 'heic',
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name: 'heic'
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},
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{
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label: 'htm',
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name: 'htm'
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},
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{
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label: 'html',
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name: 'html'
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},
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{
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label: 'jpeg',
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name: 'jpeg'
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},
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{
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label: 'jpg',
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name: 'jpg'
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},
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{
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label: 'md',
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name: 'md'
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},
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{
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label: 'msg',
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name: 'msg'
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},
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{
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label: 'odt',
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name: 'odt'
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},
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{
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label: 'pdf',
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name: 'pdf'
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},
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{
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label: 'png',
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name: 'png'
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},
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{
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label: 'ppt',
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name: 'ppt'
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},
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{
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label: 'pptx',
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name: 'pptx'
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},
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{
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label: 'rtf',
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name: 'rtf'
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},
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{
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label: 'text',
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name: 'text'
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},
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{
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label: 'txt',
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name: 'txt'
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},
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{
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label: 'xls',
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name: 'xls'
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},
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{
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label: 'xlsx',
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name: 'xlsx'
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}
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],
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optional: true,
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additionalParams: true,
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default: '["pdf", "jpg", "png"]'
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},
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{
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label: 'Hi-Res Model Name',
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name: 'hiResModelName',
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description: 'The name of the inference model used when strategy is hi_res. Default: detectron2_onnx.',
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type: 'options',
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options: [
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{
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label: 'chipper',
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name: 'chipper',
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description:
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'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.'
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},
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{
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label: 'detectron2_onnx',
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name: 'detectron2_onnx',
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description:
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'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.'
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},
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{
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label: 'yolox',
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name: 'yolox',
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description: 'A single-stage real-time object detector that modifies YOLOv3 with a DarkNet53 backbone.'
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},
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{
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label: 'yolox_quantized',
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name: 'yolox_quantized',
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description: 'Runs faster than YoloX and its speed is closer to Detectron2.'
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}
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],
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optional: true,
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additionalParams: true,
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default: 'detectron2_onnx'
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},
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{
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label: 'Chunking Strategy',
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name: 'chunkingStrategy',
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description:
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'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',
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type: 'options',
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options: [
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{
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label: 'None',
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name: 'None'
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},
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{
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label: 'By Title',
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name: 'by_title'
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}
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],
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optional: true,
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additionalParams: true,
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default: 'by_title'
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},
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{
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label: 'OCR Languages',
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name: 'ocrLanguages',
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description: 'The languages to use for OCR. Note: Being depricated as languages is the new type. Pending langchain update.',
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type: 'multiOptions',
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options: [
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{
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label: 'English',
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name: 'eng'
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},
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{
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label: 'Spanish (Español)',
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name: 'spa'
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},
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{
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label: 'Mandarin Chinese (普通话)',
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name: 'cmn'
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},
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{
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label: 'Hindi (हिन्दी)',
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name: 'hin'
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},
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{
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label: 'Arabic (اَلْعَرَبِيَّةُ)',
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name: 'ara'
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},
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{
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label: 'Portuguese (Português)',
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name: 'por'
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},
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{
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label: 'Bengali (বাংলা)',
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name: 'ben'
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},
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{
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label: 'Russian (Русский)',
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name: 'rus'
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},
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{
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label: 'Japanese (日本語)',
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name: 'jpn'
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},
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{
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label: 'Punjabi (ਪੰਜਾਬੀ)',
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name: 'pan'
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},
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{
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label: 'German (Deutsch)',
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name: 'deu'
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},
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{
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label: 'Korean (한국어)',
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name: 'kor'
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},
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{
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label: 'French (Français)',
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name: 'fra'
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},
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{
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label: 'Italian (Italiano)',
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name: 'ita'
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},
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{
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label: 'Vietnamese (Tiếng Việt)',
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name: 'vie'
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}
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],
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optional: true,
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additionalParams: true
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},
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{
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label: 'Source ID Key',
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name: 'sourceIdKey',
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type: 'string',
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description:
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'Key used to get the true source of document, to be compared against the record. Document metadata must contain the Source ID Key.',
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default: 'source',
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placeholder: 'source',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Coordinates',
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name: 'coordinates',
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type: 'boolean',
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description: 'If true, return coordinates for each element. Default: false.',
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optional: true,
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additionalParams: true,
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default: false
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},
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{
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label: 'XML Keep Tags',
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name: 'xmlKeepTags',
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description:
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'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.',
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type: 'boolean',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Include Page Breaks',
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name: 'includePageBreaks',
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description: 'When true, the output will include page break elements when the filetype supports it.',
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type: 'boolean',
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optional: true,
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additionalParams: true
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},
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{
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label: 'XML Keep Tags',
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name: 'xmlKeepTags',
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description: 'Whether to keep XML tags in the output.',
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type: 'boolean',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Multi-Page Sections',
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name: 'multiPageSections',
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description: 'Whether to treat multi-page documents as separate sections.',
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type: 'boolean',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Combine Under N Chars',
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name: 'combineUnderNChars',
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description:
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"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.",
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type: 'number',
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optional: true,
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additionalParams: true
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},
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{
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label: 'New After N Chars',
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name: 'newAfterNChars',
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description:
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"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.",
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type: 'number',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Max Characters',
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name: 'maxCharacters',
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description:
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'If chunking strategy is set, cut off new sections after reaching a length of n chars (hard max). Default: 500',
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type: 'number',
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optional: true,
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additionalParams: true,
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default: '500'
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},
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{
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label: 'Additional Metadata',
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name: 'metadata',
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type: 'json',
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description: 'Additional metadata to be added to the extracted documents',
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optional: true,
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additionalParams: true
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},
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{
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label: 'Omit Metadata Keys',
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name: 'omitMetadataKeys',
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type: 'string',
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rows: 4,
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description:
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'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',
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placeholder: 'key1, key2, key3.nestedKey1',
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optional: true,
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additionalParams: true
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}
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]
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}
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loadMethods = {
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async listRegions(): Promise<INodeOptionsValue[]> {
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return await getRegions(MODEL_TYPE.CHAT, 'awsChatBedrock')
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}
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}
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async init(nodeData: INodeData, _: string, options: ICommonObject): Promise<any> {
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const bucketName = nodeData.inputs?.bucketName as string
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const keyName = nodeData.inputs?.keyName as string
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const region = nodeData.inputs?.region as string
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const unstructuredAPIUrl = nodeData.inputs?.unstructuredAPIUrl as string
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const unstructuredAPIKey = nodeData.inputs?.unstructuredAPIKey as string
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const strategy = nodeData.inputs?.strategy as UnstructuredLoaderStrategy
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const encoding = nodeData.inputs?.encoding as string
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const coordinates = nodeData.inputs?.coordinates as boolean
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const skipInferTableTypes = nodeData.inputs?.skipInferTableTypes
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? JSON.parse(nodeData.inputs?.skipInferTableTypes as string)
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: ([] as SkipInferTableTypes[])
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const hiResModelName = nodeData.inputs?.hiResModelName as HiResModelName
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const includePageBreaks = nodeData.inputs?.includePageBreaks as boolean
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const chunkingStrategy = nodeData.inputs?.chunkingStrategy as 'None' | 'by_title'
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const metadata = nodeData.inputs?.metadata
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const sourceIdKey = (nodeData.inputs?.sourceIdKey as string) || 'source'
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const ocrLanguages = nodeData.inputs?.ocrLanguages ? JSON.parse(nodeData.inputs?.ocrLanguages as string) : ([] as string[])
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const xmlKeepTags = nodeData.inputs?.xmlKeepTags as boolean
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const multiPageSections = nodeData.inputs?.multiPageSections as boolean
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const combineUnderNChars = nodeData.inputs?.combineUnderNChars as number
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const newAfterNChars = nodeData.inputs?.newAfterNChars as number
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const maxCharacters = nodeData.inputs?.maxCharacters as number
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const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys as string
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let omitMetadataKeys: string[] = []
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if (_omitMetadataKeys) {
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omitMetadataKeys = _omitMetadataKeys.split(',').map((key) => key.trim())
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}
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let credentials: S3ClientConfig['credentials'] | undefined
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if (nodeData.credential) {
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const credentialData = await getCredentialData(nodeData.credential, options)
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const accessKeyId = getCredentialParam('awsKey', credentialData, nodeData)
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const secretAccessKey = getCredentialParam('awsSecret', credentialData, nodeData)
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if (accessKeyId && secretAccessKey) {
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credentials = {
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accessKeyId,
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secretAccessKey
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}
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}
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}
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const s3Config: S3ClientConfig = {
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region,
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credentials
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}
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const loader = new S3Loader({
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bucket: bucketName,
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key: keyName,
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s3Config,
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unstructuredAPIURL: unstructuredAPIUrl,
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unstructuredAPIKey: unstructuredAPIKey
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})
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loader.load = async () => {
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const tempDir = fsDefault.mkdtempSync(path.join(os.tmpdir(), 's3fileloader-'))
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const filePath = path.join(tempDir, keyName)
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try {
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const s3Client = new S3Client(s3Config)
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const getObjectCommand = new GetObjectCommand({
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Bucket: bucketName,
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Key: keyName
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})
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const response = await s3Client.send(getObjectCommand)
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const objectData = await new Promise<Buffer>((resolve, reject) => {
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const chunks: Buffer[] = []
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if (response.Body instanceof Readable) {
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response.Body.on('data', (chunk: Buffer) => chunks.push(chunk))
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response.Body.on('end', () => resolve(Buffer.concat(chunks)))
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response.Body.on('error', reject)
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} else {
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reject(new Error('Response body is not a readable stream.'))
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}
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})
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fsDefault.mkdirSync(path.dirname(filePath), { recursive: true })
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fsDefault.writeFileSync(filePath, objectData)
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} catch (e: any) {
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throw new Error(`Failed to download file ${keyName} from S3 bucket ${bucketName}: ${e.message}`)
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}
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try {
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const obj: UnstructuredLoaderOptions = {
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apiUrl: unstructuredAPIUrl,
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strategy,
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encoding,
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coordinates,
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skipInferTableTypes,
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hiResModelName,
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includePageBreaks,
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chunkingStrategy,
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ocrLanguages,
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xmlKeepTags,
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multiPageSections,
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combineUnderNChars,
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newAfterNChars,
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maxCharacters
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}
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if (unstructuredAPIKey) obj.apiKey = unstructuredAPIKey
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const unstructuredLoader = new UnstructuredLoader(filePath, obj)
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let docs = await unstructuredLoader.load()
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if (metadata) {
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const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
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docs = docs.map((doc) => ({
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...doc,
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metadata:
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_omitMetadataKeys === '*'
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? {
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...parsedMetadata
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}
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: omit(
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{
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...doc.metadata,
|
|
...parsedMetadata,
|
|
[sourceIdKey]: doc.metadata[sourceIdKey] || sourceIdKey
|
|
},
|
|
omitMetadataKeys
|
|
)
|
|
}))
|
|
} else {
|
|
docs = docs.map((doc) => ({
|
|
...doc,
|
|
metadata:
|
|
_omitMetadataKeys === '*'
|
|
? {}
|
|
: omit(
|
|
{
|
|
...doc.metadata,
|
|
[sourceIdKey]: doc.metadata[sourceIdKey] || sourceIdKey
|
|
},
|
|
omitMetadataKeys
|
|
)
|
|
}))
|
|
}
|
|
|
|
fsDefault.rmSync(path.dirname(filePath), { recursive: true })
|
|
|
|
return docs
|
|
} catch {
|
|
fsDefault.rmSync(path.dirname(filePath), { recursive: true })
|
|
throw new Error(`Failed to load file ${filePath} using unstructured loader.`)
|
|
}
|
|
}
|
|
|
|
return loader.load()
|
|
}
|
|
}
|
|
module.exports = { nodeClass: S3_DocumentLoaders }
|