import { omit } from 'lodash'
import { ICommonObject, IDocument, INode, INodeData, INodeParams } from '../../../src/Interface'
import {
UnstructuredLoaderOptions,
UnstructuredLoaderStrategy,
SkipInferTableTypes,
HiResModelName
} from '@langchain/community/document_loaders/fs/unstructured'
import { getCredentialData, getCredentialParam, handleEscapeCharacters } from '../../../src/utils'
import { getFileFromStorage, INodeOutputsValue } from '../../../src'
import { UnstructuredLoader } from './Unstructured'
class UnstructuredFile_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 = 'Unstructured File Loader'
this.name = 'unstructuredFileLoader'
this.version = 4.0
this.type = 'Document'
this.icon = 'unstructured-file.svg'
this.category = 'Document Loaders'
this.description = 'Use Unstructured.io to load data from a file path'
this.baseClasses = [this.type]
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['unstructuredApi'],
optional: true
}
this.inputs = [
{
label: 'Files Upload',
name: 'fileObject',
type: 'file',
description: 'Files to be processed. Multiple files can be uploaded.',
fileType:
'.txt, .text, .pdf, .docx, .doc, .jpg, .jpeg, .eml, .html, .htm, .md, .pptx, .ppt, .msg, .rtf, .xlsx, .xls, .odt, .epub'
},
{
label: 'Unstructured API URL',
name: 'unstructuredAPIUrl',
description:
'Unstructured API 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
},
{
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'
},
{
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'
},
{
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"]'
},
{
label: 'Hi-Res Model Name',
name: 'hiResModelName',
description: 'The name of the inference model used when strategy is hi_res',
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
},
{
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: 'Basic',
name: 'basic'
},
{
label: 'By Title',
name: 'by_title'
},
{
label: 'By Page',
name: 'by_page'
},
{
label: 'By Similarity',
name: 'by_similarity'
}
],
optional: true,
additionalParams: true,
default: 'by_title'
},
{
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
},
{
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
},
{
label: 'Coordinates',
name: 'coordinates',
type: 'boolean',
description: 'If true, return coordinates for each element. Default: false.',
optional: true,
additionalParams: true,
default: false
},
{
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
},
{
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
},
{
label: 'XML Keep Tags',
name: 'xmlKeepTags',
description: 'Whether to keep XML tags in the output.',
type: 'boolean',
optional: true,
additionalParams: true
},
{
label: 'Multi-Page Sections',
name: 'multiPageSections',
description: 'Whether to treat multi-page documents as separate sections.',
type: 'boolean',
optional: true,
additionalParams: true
},
{
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
},
{
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
},
{
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'
},
{
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
}
]
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']
}
]
}
async init(nodeData: INodeData, _: string, options: ICommonObject): Promise {
const unstructuredAPIUrl = nodeData.inputs?.unstructuredAPIUrl 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 string
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 string
const newAfterNChars = nodeData.inputs?.newAfterNChars as string
const maxCharacters = nodeData.inputs?.maxCharacters as string
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())
}
// give priority to upload with upsert then to fileObject (upload from UI component)
const fileBase64 =
nodeData.inputs?.pdfFile ||
nodeData.inputs?.txtFile ||
nodeData.inputs?.yamlFile ||
nodeData.inputs?.docxFile ||
nodeData.inputs?.jsonlinesFile ||
nodeData.inputs?.csvFile ||
nodeData.inputs?.jsonFile ||
(nodeData.inputs?.fileObject as string)
const obj: UnstructuredLoaderOptions = {
apiUrl: unstructuredAPIUrl,
strategy,
encoding,
coordinates,
skipInferTableTypes,
hiResModelName,
includePageBreaks,
chunkingStrategy,
ocrLanguages,
xmlKeepTags,
multiPageSections
}
if (combineUnderNChars) {
obj.combineUnderNChars = parseInt(combineUnderNChars, 10)
}
if (newAfterNChars) {
obj.newAfterNChars = parseInt(newAfterNChars, 10)
}
if (maxCharacters) {
obj.maxCharacters = parseInt(maxCharacters, 10)
}
const credentialData = await getCredentialData(nodeData.credential ?? '', options)
const unstructuredAPIKey = getCredentialParam('unstructuredAPIKey', credentialData, nodeData)
if (unstructuredAPIKey) obj.apiKey = unstructuredAPIKey
let docs: IDocument[] = []
let files: string[] = []
if (fileBase64) {
const loader = new UnstructuredLoader(obj)
//FILE-STORAGE::["CONTRIBUTING.md","LICENSE.md","README.md"]
if (fileBase64.startsWith('FILE-STORAGE::')) {
const fileName = fileBase64.replace('FILE-STORAGE::', '')
if (fileName.startsWith('[') && fileName.endsWith(']')) {
files = JSON.parse(fileName)
} else {
files = [fileName]
}
const orgId = options.orgId
const chatflowid = options.chatflowid
for (const file of files) {
if (!file) continue
const fileData = await getFileFromStorage(file, orgId, chatflowid)
const loaderDocs = await loader.loadAndSplitBuffer(fileData, file)
docs.push(...loaderDocs)
}
} else {
if (fileBase64.startsWith('[') && fileBase64.endsWith(']')) {
files = JSON.parse(fileBase64)
} else {
files = [fileBase64]
}
for (const file of files) {
if (!file) continue
const splitDataURI = file.split(',')
const filename = splitDataURI.pop()?.split(':')[1] ?? ''
const bf = Buffer.from(splitDataURI.pop() || '', 'base64')
const loaderDocs = await loader.loadAndSplitBuffer(bf, filename)
docs.push(...loaderDocs)
}
}
} else {
throw new Error('File upload is required')
}
if (metadata) {
const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata)
docs = docs.map((doc) => ({
...doc,
metadata:
_omitMetadataKeys === '*'
? {
...parsedMetadata
}
: omit(
{
...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
)
}))
}
if (output === 'document') {
return docs
} else {
let finaltext = ''
for (const doc of docs) {
finaltext += `${doc.pageContent}\n`
}
return handleEscapeCharacters(finaltext, false)
}
}
}
module.exports = { nodeClass: UnstructuredFile_DocumentLoaders }