dtamind-components
Version:
DTAmindai Components
205 lines • 8.79 kB
JavaScript
;
Object.defineProperty(exports, "__esModule", { value: true });
const lodash_1 = require("lodash");
const documents_1 = require("@langchain/core/documents");
const couchbase_1 = require("@langchain/community/vectorstores/couchbase");
const couchbase_2 = require("couchbase");
const utils_1 = require("../../../src/utils");
const VectorStoreUtils_1 = require("../VectorStoreUtils");
class Couchbase_VectorStores {
constructor() {
//@ts-ignore
this.vectorStoreMethods = {
async upsert(nodeData, options) {
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const bucketName = nodeData.inputs?.bucketName;
const scopeName = nodeData.inputs?.scopeName;
const collectionName = nodeData.inputs?.collectionName;
const indexName = nodeData.inputs?.indexName;
let textKey = nodeData.inputs?.textKey;
let embeddingKey = nodeData.inputs?.embeddingKey;
const embeddings = nodeData.inputs?.embeddings;
let connectionString = (0, utils_1.getCredentialParam)('connectionString', credentialData, nodeData);
let databaseUsername = (0, utils_1.getCredentialParam)('username', credentialData, nodeData);
let databasePassword = (0, utils_1.getCredentialParam)('password', credentialData, nodeData);
const docs = nodeData.inputs?.document;
const flattenDocs = docs && docs.length ? (0, lodash_1.flatten)(docs) : [];
const finalDocs = [];
for (let i = 0; i < flattenDocs.length; i += 1) {
if (flattenDocs[i] && flattenDocs[i].pageContent) {
const document = new documents_1.Document(flattenDocs[i]);
finalDocs.push(document);
}
}
const couchbaseClient = await couchbase_2.Cluster.connect(connectionString, {
username: databaseUsername,
password: databasePassword,
configProfile: 'wanDevelopment'
});
const couchbaseConfig = {
cluster: couchbaseClient,
bucketName: bucketName,
scopeName: scopeName,
collectionName: collectionName,
indexName: indexName,
textKey: textKey,
embeddingKey: embeddingKey
};
try {
if (!textKey || textKey === '')
couchbaseConfig.textKey = 'text';
if (!embeddingKey || embeddingKey === '')
couchbaseConfig.embeddingKey = 'embedding';
await couchbase_1.CouchbaseVectorStore.fromDocuments(finalDocs, embeddings, couchbaseConfig);
return { numAdded: finalDocs.length, addedDocs: finalDocs };
}
catch (e) {
throw new Error(e);
}
}
};
this.label = 'Couchbase';
this.name = 'couchbase';
this.version = 1.0;
this.type = 'Couchbase';
this.icon = 'couchbase.svg';
this.category = 'Vector Stores';
this.description = `Upsert embedded data and load existing index using Couchbase, a award-winning distributed NoSQL database`;
this.baseClasses = [this.type, 'VectorStoreRetriever', 'BaseRetriever'];
this.credential = {
label: 'Connect Credential',
name: 'credential',
type: 'credential',
credentialNames: ['couchbaseApi']
};
this.inputs = [
{
label: 'Document',
name: 'document',
type: 'Document',
list: true,
optional: true
},
{
label: 'Embeddings',
name: 'embeddings',
type: 'Embeddings'
},
{
label: 'Bucket Name',
name: 'bucketName',
placeholder: '<DB_BUCKET_NAME>',
type: 'string'
},
{
label: 'Scope Name',
name: 'scopeName',
placeholder: '<SCOPE_NAME>',
type: 'string'
},
{
label: 'Collection Name',
name: 'collectionName',
placeholder: '<COLLECTION_NAME>',
type: 'string'
},
{
label: 'Index Name',
name: 'indexName',
placeholder: '<VECTOR_INDEX_NAME>',
type: 'string'
},
{
label: 'Content Field',
name: 'textKey',
description: 'Name of the field (column) that contains the actual content',
type: 'string',
default: 'text',
additionalParams: true,
optional: true
},
{
label: 'Embedded Field',
name: 'embeddingKey',
description: 'Name of the field (column) that contains the Embedding',
type: 'string',
default: 'embedding',
additionalParams: true,
optional: true
},
{
label: 'Couchbase Metadata Filter',
name: 'couchbaseMetadataFilter',
type: 'json',
optional: true,
additionalParams: true
},
{
label: 'Top K',
name: 'topK',
description: 'Number of top results to fetch. Default to 4',
placeholder: '4',
type: 'number',
additionalParams: true,
optional: true
}
];
this.outputs = [
{
label: 'Couchbase Retriever',
name: 'retriever',
baseClasses: this.baseClasses
},
{
label: 'Couchbase Vector Store',
name: 'vectorStore',
baseClasses: [this.type, ...(0, utils_1.getBaseClasses)(couchbase_1.CouchbaseVectorStore)]
}
];
}
async init(nodeData, _, options) {
const credentialData = await (0, utils_1.getCredentialData)(nodeData.credential ?? '', options);
const bucketName = nodeData.inputs?.bucketName;
const scopeName = nodeData.inputs?.scopeName;
const collectionName = nodeData.inputs?.collectionName;
const indexName = nodeData.inputs?.indexName;
let textKey = nodeData.inputs?.textKey;
let embeddingKey = nodeData.inputs?.embeddingKey;
const embeddings = nodeData.inputs?.embeddings;
const couchbaseMetadataFilter = nodeData.inputs?.couchbaseMetadataFilter;
let connectionString = (0, utils_1.getCredentialParam)('connectionString', credentialData, nodeData);
let databaseUsername = (0, utils_1.getCredentialParam)('username', credentialData, nodeData);
let databasePassword = (0, utils_1.getCredentialParam)('password', credentialData, nodeData);
let metadatafilter;
const couchbaseClient = await couchbase_2.Cluster.connect(connectionString, {
username: databaseUsername,
password: databasePassword,
configProfile: 'wanDevelopment'
});
const couchbaseConfig = {
cluster: couchbaseClient,
bucketName: bucketName,
scopeName: scopeName,
collectionName: collectionName,
indexName: indexName,
textKey: textKey,
embeddingKey: embeddingKey
};
try {
if (!textKey || textKey === '')
couchbaseConfig.textKey = 'text';
if (!embeddingKey || embeddingKey === '')
couchbaseConfig.embeddingKey = 'embedding';
if (couchbaseMetadataFilter) {
metadatafilter = typeof couchbaseMetadataFilter === 'object' ? couchbaseMetadataFilter : JSON.parse(couchbaseMetadataFilter);
}
const vectorStore = await couchbase_1.CouchbaseVectorStore.initialize(embeddings, couchbaseConfig);
return (0, VectorStoreUtils_1.resolveVectorStoreOrRetriever)(nodeData, vectorStore, metadatafilter);
}
catch (e) {
throw new Error(e);
}
}
}
module.exports = { nodeClass: Couchbase_VectorStores };
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