Automate With Marc This workflow corresponds to n8n.io template #4552 — we link there as the canonical source.
This workflow follows the Documentdefaultdataloader → OpenAI Embeddings recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "OceYxCmiuf5W2X4y",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Bundle RAG Upload",
"tags": [],
"nodes": [
{
"id": "e72ec6be-08f3-4195-b429-34c0870ee1bc",
"name": "Google Drive",
"type": "n8n-nodes-base.googleDrive",
"position": [
180,
0
],
"parameters": {
"filter": {
"folderId": {
"__rl": true,
"mode": "list",
"value": "17cefWWyf-yKZVpCLHFVOlpfuqQpLl8QW",
"cachedResultUrl": "https://drive.google.com/drive/folders/17cefWWyf-yKZVpCLHFVOlpfuqQpLl8QW",
"cachedResultName": "Folder for n8n"
}
},
"options": {},
"resource": "fileFolder",
"returnAll": true
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "82a0bcb2-35e0-4897-b2a5-2e8d22fdec43",
"name": "Get Docs",
"type": "n8n-nodes-base.googleDrive",
"position": [
440,
0
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "61fc1b10-4a5e-4f12-82c1-c1c7d64c7901",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
660,
0
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "95a8e03c-bd70-4742-b4ad-6bf3a9b484a2",
"name": "Pinecone Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
900,
20
],
"parameters": {
"mode": "insert",
"options": {
"pineconeNamespace": "Redacted"
},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "Redacted",
"cachedResultName": "Redacted"
}
},
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "8d762bd6-d64f-4e01-bf9d-8183b7cd7555",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
920,
160
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "80c20301-9fdd-455a-85eb-f0f5b12091be",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1060,
240
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "Type",
"value": "Redacted"
}
]
}
},
"dataType": "binary"
},
"typeVersion": 1
},
{
"id": "9b849c85-fa99-4f2d-bdd5-02fababbc361",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1140,
380
],
"parameters": {
"options": {},
"chunkSize": 600,
"chunkOverlap": 60
},
"typeVersion": 1
},
{
"id": "a18e5576-6e16-487f-9347-2de39ecd7708",
"name": "Google Drive Trigger",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
-60,
0
],
"parameters": {
"event": "fileCreated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": ""
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "b82cc00a-56f9-41e9-9257-9a054c971db7",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-140,
-120
],
"parameters": {
"color": 4,
"width": 260,
"height": 400,
"content": "Google Folder Upload Trigger"
},
"typeVersion": 1
},
{
"id": "aca97112-2f76-44ab-b5ae-aa232bd1242c",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
140,
-120
],
"parameters": {
"color": 6,
"width": 220,
"height": 400,
"content": "Google Search File from Folder"
},
"typeVersion": 1
},
{
"id": "7cf71e7a-db76-43b5-a8fd-c377ac4187aa",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
380,
-120
],
"parameters": {
"color": 2,
"width": 220,
"height": 400,
"content": "Get File"
},
"typeVersion": 1
},
{
"id": "ee27b02f-4d74-49f7-a3fd-5d0e928ac556",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
860,
-120
],
"parameters": {
"color": 3,
"width": 500,
"height": 680,
"content": "Upload to Pinecone Vector"
},
"typeVersion": 1
},
{
"id": "ec38ac32-c4a8-47fb-9312-c8804590a891",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
620,
-120
],
"parameters": {
"color": 7,
"width": 220,
"height": 400,
"content": "Loop for multiple files"
},
"typeVersion": 1
},
{
"id": "4db0ce4b-77d2-4875-963c-10f61438128e",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-740,
-120
],
"parameters": {
"color": 3,
"width": 580,
"height": 1300,
"content": "\ud83e\udde0 Google Drive Upload Trigger \u2192 Pinecone Vector Upsert for Document Indexing\n\n\ud83d\udcc4 What This Workflow Does\nThis workflow watches a specific Google Drive folder and automatically uploads any newly added document to a Pinecone vector database \u2014 complete with OpenAI-generated embeddings.\n\nPerfect for setting up retrieval-augmented generation (RAG) pipelines, semantic search, or document Q&A systems. Once configured, your knowledge base stays up-to-date with zero manual effort.\n\nWatch Full Video Step-by-step guide here:\nhttps://www.youtube.com/@Automatewithmarc\n\n\ud83d\udd27 How It Works\n\ud83d\udcc1 Google Drive Trigger\nWatches a specific folder and triggers when new documents are uploaded.\n\n\ud83d\udd0d Google Drive File Search & Download\nFinds and fetches all files in the folder.\n\n\ud83d\udd04 Loop Over Each File\nHandles batch processing for multiple files.\n\n\ud83d\udcc3 Document Loader\nParses each file as binary and applies custom metadata like document type.\n\n\u2702\ufe0f Text Splitter\nBreaks content into manageable chunks for embedding (e.g., 600 characters, 60 overlap).\n\n\ud83e\udde0 OpenAI Embeddings\nGenerates vector embeddings using OpenAI.\n\n\ud83d\udce6 Pinecone Vector Store\nInserts/upserts documents into a specific Pinecone namespace for search-ready indexing.\n\n\ud83e\udde0 Why This is Useful\nThis is a production-grade setup for:\n\nBuilding vector search tools over internal docs\n\nFeeding up-to-date data into RAG agents or chatbots\n\nAuto-tagging and chunking files for scalable AI workflows\n\nWhether you\u2019re indexing document outlines, SOPs, or technical docs \u2014 this automation keeps your vector store fresh and organized.\n\n\ud83e\ude9c Setup Instructions\nConnect your Google Drive, OpenAI, and Pinecone accounts.\n\nSpecify the Google Drive folder to monitor.\n\nCustomize metadata, chunk size, or vector namespace as needed.\n\nActivate the workflow and drop a file into the folder \u2014 magic happens behind the scenes.\n\n\ud83d\udccc Notes\nWorks best with PDFs or text-based documents.\n\nYou can swap out OpenAI with other embedding models if needed.\n\nConsider adding notifications or logging (e.g., via Slack or email) for better observability."
},
"typeVersion": 1
}
],
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "f3a17075-083e-42bc-acfb-c4480b2fe716",
"connections": {
"Get Docs": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Google Drive": {
"main": [
[
{
"node": "Get Docs",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "Pinecone Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Google Drive Trigger": {
"main": [
[
{
"node": "Google Drive",
"type": "main",
"index": 0
}
]
]
},
"Pinecone Vector Store": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleDriveOAuth2ApiopenAiApipineconeApi
Pro
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About this workflow
🧠 Google Drive Upload Trigger → Pinecone Vector Upsert for Document Indexing Category: AI & LLM / Document Indexing Level: Intermediate Tags: Google Drive, Pinecone, OpenAI, Embeddings, Vector Store, LangChain, RAG
Source: https://n8n.io/workflows/4552/ — original creator credit. Request a take-down →
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