upate AJ assistant from master and fix some lint errors

1 files changed, 8 insertions, 5 deletions

diff --git a/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts b/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts
index 07a2b73bc..9575277f7 100644
--- a/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts
+++ b/src/client/views/nodes/chatbot/vectorstore/Vectorstore.ts
@@ -1,11 +1,11 @@
-import { Pinecone, Index, IndexList, PineconeRecord, RecordMetadata, QueryResponse } from '@pinecone-database/pinecone';
+import { Index, IndexList, Pinecone, PineconeRecord, QueryResponse, RecordMetadata } from '@pinecone-database/pinecone';
 import { CohereClient } from 'cohere-ai';
 import { EmbedResponse } from 'cohere-ai/api';
 import dotenv from 'dotenv';
-import { RAGChunk, AI_Document, CHUNK_TYPE } from '../types/types';
 import { Doc } from '../../../../../fields/Doc';
 import { CsvCast, PDFCast, StrCast } from '../../../../../fields/Types';
 import { Networking } from '../../../../Network';
+import { AI_Document, CHUNK_TYPE, RAGChunk } from '../types/types';
 
 dotenv.config();
 
@@ -103,8 +103,8 @@ export class Vectorstore {
                 const { jobId } = await Networking.PostToServer('/createDocument', { file_path: local_file_path });
 
                 // Poll the server for progress updates.
-                let inProgress: boolean = true;
-                let result: any = null;
+                const inProgress = true;
+                let result: (AI_Document & { doc_id: string }) | null = null; // bcz: is this the correct type??
                 while (inProgress) {
                     // Polling interval for status updates.
                     await new Promise(resolve => setTimeout(resolve, 2000));
@@ -127,6 +127,9 @@ export class Vectorstore {
                         progressCallback(progress, step);
                     }
                 }
+                if (!result) {
+                    throw new Error('no result received...'); // bcz: is this an Error?
+                }
 
                 // Once completed, process the document and add it to the vectorstore.
                 console.log('Document JSON:', result);
@@ -175,7 +178,7 @@ export class Vectorstore {
      * Indexes the processed document by uploading the document's vector chunks to the Pinecone index.
      * @param document The processed document containing its chunks and metadata.
      */
-    private async indexDocument(document: any) {
+    private async indexDocument(document: AI_Document) {
         console.log('Uploading vectors to content namespace...');
 
         // Prepare Pinecone records for each chunk in the document.