dtamind-components
Version:
Apps integration for Dtamind. Contain Nodes and Credentials.
119 lines • 4.79 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const WordLoader_1 = require("./WordLoader");
const src_1 = require("../../../src");
class MicrosoftWord_DocumentLoaders {
constructor() {
this.label = 'Microsoft Word';
this.name = 'microsoftWord';
this.version = 1.0;
this.type = 'Document';
this.icon = 'word.svg';
this.category = 'Document Loaders';
this.description = `Load data from Microsoft Word files`;
this.baseClasses = [this.type];
this.inputs = [
{
label: 'Word File',
name: 'docxFile',
type: 'file',
fileType: '.docx, .doc'
},
{
label: 'Text Splitter',
name: 'textSplitter',
type: 'TextSplitter',
optional: true
},
{
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']
}
];
}
getFiles(nodeData) {
const docxFileBase64 = nodeData.inputs?.docxFile;
let files = [];
let fromStorage = true;
if (docxFileBase64.startsWith('FILE-STORAGE::')) {
const fileName = docxFileBase64.replace('FILE-STORAGE::', '');
if (fileName.startsWith('[') && fileName.endsWith(']')) {
files = JSON.parse(fileName);
}
else {
files = [fileName];
}
}
else {
if (docxFileBase64.startsWith('[') && docxFileBase64.endsWith(']')) {
files = JSON.parse(docxFileBase64);
}
else {
files = [docxFileBase64];
}
fromStorage = false;
}
return { files, fromStorage };
}
async getFileData(file, { orgId, chatflowid }, fromStorage) {
if (fromStorage) {
return (0, src_1.getFileFromStorage)(file, orgId, chatflowid);
}
else {
const splitDataURI = file.split(',');
splitDataURI.pop();
return Buffer.from(splitDataURI.pop() || '', 'base64');
}
}
async init(nodeData, _, options) {
const textSplitter = nodeData.inputs?.textSplitter;
const metadata = nodeData.inputs?.metadata;
const output = nodeData.outputs?.output;
const _omitMetadataKeys = nodeData.inputs?.omitMetadataKeys;
let docs = [];
const orgId = options.orgId;
const chatflowid = options.chatflowid;
const { files, fromStorage } = this.getFiles(nodeData);
for (const file of files) {
if (!file)
continue;
const fileData = await this.getFileData(file, { orgId, chatflowid }, fromStorage);
const blob = new Blob([fileData]);
const loader = new WordLoader_1.WordLoader(blob);
// use spread instead of push, because it raises RangeError: Maximum call stack size exceeded when too many docs
docs = [...docs, ...(await (0, src_1.handleDocumentLoaderDocuments)(loader, textSplitter))];
}
docs = (0, src_1.handleDocumentLoaderMetadata)(docs, _omitMetadataKeys, metadata);
return (0, src_1.handleDocumentLoaderOutput)(docs, output);
}
}
module.exports = { nodeClass: MicrosoftWord_DocumentLoaders };
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