dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
479 lines • 19 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const lodash_1 = require("lodash");
const unstructured_1 = require("@langchain/community/document_loaders/fs/unstructured");
const utils_1 = require("../../../src/utils");
class UnstructuredFolder_DocumentLoaders {
constructor() {
this.label = 'Unstructured Folder Loader';
this.name = 'unstructuredFolderLoader';
this.version = 3.0;
this.type = 'Document';
this.icon = 'unstructured-folder.svg';
this.category = 'Document Loaders';
this.description =
"Use Unstructured.io to load data from a folder. Note: Currently doesn't support .png and .heic until unstructured is updated.";
this.baseClasses = [this.type];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['unstructuredApi'],
optional: true
};
this.inputs = [
{
label: 'Folder Path',
name: 'folderPath',
type: 'string',
placeholder: ''
},
{
label: 'Unstructured API URL',
name: 'unstructuredAPIUrl',
description: 'Unstructured API URL. Read <a target="_blank" href="https://unstructured-io.github.io/unstructured/introduction.html#getting-started">more</a> 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. 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'
},
{
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'
},
{
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: '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, _, options) {
const folderPath = nodeData.inputs?.folderPath;
const unstructuredAPIUrl = nodeData.inputs?.unstructuredAPIUrl;
const strategy = nodeData.inputs?.strategy;
const encoding = nodeData.inputs?.encoding;
const coordinates = nodeData.inputs?.coordinates;
const skipInferTableTypes = nodeData.inputs?.skipInferTableTypes
? JSON.parse(nodeData.inputs?.skipInferTableTypes)
: [];
const hiResModelName = nodeData.inputs?.hiResModelName;
const includePageBreaks = nodeData.inputs?.includePageBreaks;
const chunkingStrategy = nodeData.inputs?.chunkingStrategy;
const metadata = nodeData.inputs?.metadata;
const sourceIdKey = nodeData.inputs?.sourceIdKey || 'source';
const ocrLanguages = nodeData.inputs?.ocrLanguages ? JSON.parse(nodeData.inputs?.ocrLanguages) : [];
const xmlKeepTags = nodeData.inputs?.xmlKeepTags;
const multiPageSections = nodeData.inputs?.multiPageSections;
const combineUnderNChars = nodeData.inputs?.combineUnderNChars;
const newAfterNChars = nodeData.inputs?.newAfterNChars;
const maxCharacters = nodeData.inputs?.maxCharacters;
const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys;
const output = nodeData.outputs?.output;
let omitMetadataKeys = [];
if (_omitMetadataKeys) {
omitMetadataKeys = _omitMetadataKeys.split(',').map((key) => key.trim());
}
const obj = {
apiUrl: unstructuredAPIUrl,
strategy,
encoding,
coordinates,
skipInferTableTypes,
hiResModelName,
includePageBreaks,
chunkingStrategy,
ocrLanguages,
xmlKeepTags,
multiPageSections,
combineUnderNChars,
newAfterNChars,
maxCharacters
};
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const unstructuredAPIKey = (0, utils_1.getCredentialParam)('unstructuredAPIKey', credentialData, nodeData);
if (unstructuredAPIKey)
obj.apiKey = unstructuredAPIKey;
const loader = new unstructured_1.UnstructuredDirectoryLoader(folderPath, obj);
let docs = await loader.load();
if (metadata) {
const parsedMetadata = typeof metadata === 'object' ? metadata : JSON.parse(metadata);
docs = docs.map((doc) => ({
...doc,
metadata: _omitMetadataKeys === '*'
? {
...parsedMetadata
}
: (0, lodash_1.omit)({
...doc.metadata,
...parsedMetadata,
[sourceIdKey]: doc.metadata[sourceIdKey] || sourceIdKey
}, omitMetadataKeys)
}));
}
else {
docs = docs.map((doc) => ({
...doc,
metadata: _omitMetadataKeys === '*'
? {}
: (0, lodash_1.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 (0, utils_1.handleEscapeCharacters)(finaltext, false);
}
}
}
module.exports = { nodeClass: UnstructuredFolder_DocumentLoaders };
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