This workflow corresponds to n8n.io template #2753 — we link there as the canonical source.
This workflow follows the Agent → Chat Trigger 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": "7cXvgkl9170QXzT2",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "RAG Workflow For Company Documents stored in Google Drive",
"tags": [],
"nodes": [
{
"id": "753455a3-ddc8-4a74-b043-70a0af38ff9e",
"name": "Pinecone Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
680,
0
],
"parameters": {
"mode": "insert",
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "company-files",
"cachedResultName": "company-files"
}
},
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "a7c8fa7f-cad2-4497-a295-30aa2e98cacc",
"name": "Embeddings Google Gemini",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
640,
280
],
"parameters": {
"modelName": "models/text-embedding-004"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "215f0519-4359-4e4b-a90c-7e54b1cc52b5",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
840,
220
],
"parameters": {
"options": {},
"dataType": "binary",
"binaryMode": "specificField"
},
"typeVersion": 1
},
{
"id": "863d3d1d-1621-406e-8320-688f64b07b09",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
820,
420
],
"parameters": {
"options": {},
"chunkOverlap": 100
},
"typeVersion": 1
},
{
"id": "5af1efb1-ea69-466e-bb3b-2b7e6b1ceef7",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
420,
840
],
"parameters": {
"options": {
"systemMessage": "You are a helpful HR assistant designed to answer employee questions based on company policies.\n\nRetrieve relevant information from the provided internal documents and provide a concise, accurate, and informative answer to the employee's question.\n\nUse the tool called \"company_documents_tool\" to retrieve any information from the company's documents.\n\nIf the answer cannot be found in the provided documents, respond with \"I cannot find the answer in the available resources.\""
}
},
"typeVersion": 1.7
},
{
"id": "825632ac-1edf-4e63-948d-b1a498b2b962",
"name": "Vector Store Tool",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"position": [
820,
1060
],
"parameters": {
"name": "company_documents_tool",
"description": "Retrieve information from any company documents"
},
"typeVersion": 1
},
{
"id": "72d2f685-bcc3-4e62-a5e3-72c0fe65f8e8",
"name": "Pinecone Vector Store (Retrieval)",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
720,
1240
],
"parameters": {
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "company-files",
"cachedResultName": "company-files"
}
},
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "eeff81cb-6aec-4e7f-afe0-432d87085fb2",
"name": "Embeddings Google Gemini (retrieval)",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
700,
1400
],
"parameters": {
"modelName": "models/text-embedding-004"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "8bb6ebb1-1deb-498b-8da4-b809a736e097",
"name": "Download File From Google Drive",
"type": "n8n-nodes-base.googleDrive",
"position": [
460,
0
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {
"fileName": "={{ $json.name }}"
},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "bd83bacf-dff1-4b7c-af5c-b249fb16c113",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
420,
660
],
"parameters": {
"content": "## Chat with company documents"
},
"typeVersion": 1
},
{
"id": "7b90daab-0fb2-4c8a-93e6-b138bb04f282",
"name": "Google Drive File Updated",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
140,
140
],
"parameters": {
"event": "fileUpdated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "list",
"value": "1evDIoHePhjw_LgVFZXSZyK1sZm2GHp9W",
"cachedResultUrl": "https://drive.google.com/drive/folders/1evDIoHePhjw_LgVFZXSZyK1sZm2GHp9W",
"cachedResultName": "INNOVI PRO"
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "3a6c6cef-7a19-42ef-8092-eaf57dae4cdd",
"name": "Google Drive File Created",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
140,
-120
],
"parameters": {
"event": "fileCreated",
"options": {
"fileType": "all"
},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "list",
"value": "1evDIoHePhjw_LgVFZXSZyK1sZm2GHp9W",
"cachedResultUrl": "https://drive.google.com/drive/folders/1evDIoHePhjw_LgVFZXSZyK1sZm2GHp9W",
"cachedResultName": "INNOVI PRO"
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "1e38f1c8-7bd0-4eeb-addc-62339582d350",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
500,
1140
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "4b0ab858-99b1-4337-8c5c-a223519e3662",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
80,
840
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "bfb684d1-e5c1-41da-8305-b2606a2eade6",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
440,
-240
],
"parameters": {
"width": 320,
"content": "## Add docuemnts to vector store when updating or creating new documents in Google Drive"
},
"typeVersion": 1
},
{
"id": "8f627ec6-4b3f-43ad-a4a3-e2b199a7fe58",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
320,
1140
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "f2133a06-0088-46de-9f74-a3f9fe478f98",
"name": "Google Gemini Chat Model (retrieval)",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1080,
1240
],
"parameters": {
"options": {},
"modelName": "models/gemini-2.0-flash-exp"
},
"credentials": {
"googlePalmApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "578deb96-8393-4850-9757-fa97b2bc9992",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-540,
220
],
"parameters": {
"width": 420,
"height": 720,
"content": "## Set up steps\n\n1. Google Cloud Project and Vertex AI API:\n* Create a Google Cloud project.\n* Enable the Vertex AI API for your project.\n2. Google AI API Key:\n* Obtain a Google AI API key from Google AI Studio.\n3. Pinecone Account:\n* Create a free account on the Pinecone website.\nObtain your API key from your Pinecone dashboard.\n* Create an index named company-files in your Pinecone project.\n4. Google Drive:\n* Create a dedicated folder in your Google Drive where company documents will be stored.\n5. Credentials in n8n: Configure credentials in your n8n environment for:\n* Google Drive OAuth2\n* Google Gemini(PaLM) Api (using your Google AI API key)\n* Pinecone API (using your Pinecone API key)\n5. Import the Workflow:\n* Import this workflow into your n8n instance.\n6. Configure the Workflow:\n* Update both Google Drive Trigger nodes to watch the specific folder you created in your Google Drive.\n* Configure the Pinecone Vector Store nodes to use your company-files index."
},
"typeVersion": 1
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "33b252fb-5d87-4a29-a0a7-97308140699c",
"connections": {
"AI Agent": {
"main": [
[]
]
},
"Vector Store Tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Window Buffer Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Pinecone Vector Store": {
"main": [
[]
]
},
"Embeddings Google Gemini": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Google Drive File Created": {
"main": [
[
{
"node": "Download File From Google Drive",
"type": "main",
"index": 0
}
]
]
},
"Google Drive File Updated": {
"main": [
[
{
"node": "Download File From Google Drive",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Download File From Google Drive": {
"main": [
[
{
"node": "Pinecone Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Pinecone Vector Store (Retrieval)": {
"ai_vectorStore": [
[
{
"node": "Vector Store Tool",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings Google Gemini (retrieval)": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store (Retrieval)",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Google Gemini Chat Model (retrieval)": {
"ai_languageModel": [
[
{
"node": "Vector Store Tool",
"type": "ai_languageModel",
"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.
googleDriveOAuth2ApigooglePalmApipineconeApi
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About this workflow
This workflow implements a Retrieval Augmented Generation (RAG) chatbot that answers employee questions based on company documents stored in Google Drive. It automatically indexes new or updated documents in a Pinecone vector database, allowing the chatbot to provide accurate…
Source: https://n8n.io/workflows/2753/ — original creator credit. Request a take-down →
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