Feature/Indexing (#1802)

* indexing

* fix for multiple files upsert

* fix default Postgres port

* fix SQLite node description

* add MySQLRecordManager node

* fix MySQL unique index

* add upsert history

* update jsx ui

* lint-fix

* update dialog details

* update llamaindex pinecone

---------

Co-authored-by: chungyau97 <chungyau97@gmail.com>

packages/components/nodes/vectorstores/Faiss/Faiss.ts

@@ -2,7 +2,7 @@ import { flatten } from 'lodash'
 import { Document } from '@langchain/core/documents'
 import { FaissStore } from '@langchain/community/vectorstores/faiss'
 import { Embeddings } from '@langchain/core/embeddings'
-import { INode, INodeData, INodeOutputsValue, INodeParams } from '../../../src/Interface'
+import { INode, INodeData, INodeOutputsValue, INodeParams, IndexingResult } from '../../../src/Interface'
 import { getBaseClasses } from '../../../src/utils'
 
 class Faiss_VectorStores implements INode {
@@ -74,7 +74,7 @@ class Faiss_VectorStores implements INode {
 
     //@ts-ignore
     vectorStoreMethods = {
-        async upsert(nodeData: INodeData): Promise<void> {
+        async upsert(nodeData: INodeData): Promise<Partial<IndexingResult>> {
             const docs = nodeData.inputs?.document as Document[]
             const embeddings = nodeData.inputs?.embeddings as Embeddings
             const basePath = nodeData.inputs?.basePath as string
@@ -95,6 +95,8 @@ class Faiss_VectorStores implements INode {
                 vectorStore.similaritySearchVectorWithScore = async (query: number[], k: number) => {
                     return await similaritySearchVectorWithScore(query, k, vectorStore)
                 }
+
+                return { numAdded: finalDocs.length, addedDocs: finalDocs }
             } catch (e) {
                 throw new Error(e)
             }