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 →
{
"name": "google-drive-rag",
"nodes": [
{
"parameters": {
"mode": "insert",
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "company-files",
"cachedResultName": "company-files"
},
"options": {}
},
"id": "8b0181f1-72d3-4c90-8cee-926ee3db7768",
"name": "Pinecone Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
-60,
220
],
"typeVersion": 1
},
{
"parameters": {
"modelName": "models/text-embedding-004"
},
"id": "43ae538f-f209-4eb1-b9ca-ba6a011cffef",
"name": "Embeddings Google Gemini",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
-100,
500
],
"typeVersion": 1
},
{
"parameters": {
"dataType": "binary",
"binaryMode": "specificField",
"options": {}
},
"id": "2df18c6c-ef4b-4f0c-8dfd-449e8c80dd2f",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
100,
440
],
"typeVersion": 1
},
{
"parameters": {
"chunkOverlap": 100,
"options": {}
},
"id": "4e03201b-ed7f-43c4-9c45-b541512833a3",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
80,
640
],
"typeVersion": 1
},
{
"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.\""
}
},
"id": "374ef2f9-4618-4527-96fc-8c875d44b5c7",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-320,
1060
],
"typeVersion": 1.7
},
{
"parameters": {
"name": "company_documents_tool",
"description": "Retrieve information from any company documents"
},
"id": "6e3fb396-c514-4739-bc10-f85d4fbbddbf",
"name": "Vector Store Tool",
"type": "@n8n/n8n-nodes-langchain.toolVectorStore",
"position": [
80,
1280
],
"typeVersion": 1
},
{
"parameters": {
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "company-files",
"cachedResultName": "company-files"
},
"options": {}
},
"id": "e72f6d38-789e-47b6-8e16-6331bc43b370",
"name": "Pinecone Vector Store (Retrieval)",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
-20,
1460
],
"typeVersion": 1
},
{
"parameters": {
"modelName": "models/text-embedding-004"
},
"id": "f2a77824-10ed-45f3-96a4-fc38bdb1a71c",
"name": "Embeddings Google Gemini (retrieval)",
"type": "@n8n/n8n-nodes-langchain.embeddingsGoogleGemini",
"position": [
-40,
1620
],
"typeVersion": 1
},
{
"parameters": {
"operation": "download",
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {
"fileName": "={{ $json.name }}"
}
},
"id": "70bce54a-1de2-4465-878d-0c8b70976c59",
"name": "Download File From Google Drive",
"type": "n8n-nodes-base.googleDrive",
"position": [
-280,
220
],
"typeVersion": 3
},
{
"parameters": {
"content": "## Chat with company documents"
},
"id": "eb1a156b-9dd7-46b9-8b85-d565f04cab08",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-320,
880
],
"typeVersion": 1
},
{
"parameters": {
"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"
},
"event": "fileUpdated",
"options": {}
},
"id": "74655a16-d630-48b2-bca8-ad018d67fbb8",
"name": "Google Drive File Updated",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
-600,
360
],
"typeVersion": 1
},
{
"parameters": {
"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"
},
"event": "fileCreated",
"options": {
"fileType": "all"
}
},
"id": "e1b2681b-ac9c-4c70-9099-6ce916146233",
"name": "Google Drive File Created",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
-600,
100
],
"typeVersion": 1
},
{
"parameters": {},
"id": "006576ee-6670-41b7-bbae-fc3c87796219",
"name": "Window Buffer Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-240,
1360
],
"typeVersion": 1.3
},
{
"parameters": {
"options": {}
},
"id": "f75d6256-3e5d-47e3-b551-91c2a6906627",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-660,
1060
],
"typeVersion": 1.1
},
{
"parameters": {
"content": "## Add docuemnts to vector store when updating or creating new documents in Google Drive",
"width": 320
},
"id": "96051dd0-ec5b-4275-bce1-31dead8ef740",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-300,
-20
],
"typeVersion": 1
},
{
"parameters": {
"modelName": "models/gemini-2.0-flash-exp",
"options": {}
},
"id": "c1912957-2132-445d-b537-1d68dcfafd27",
"name": "Google Gemini Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
-420,
1360
],
"typeVersion": 1
},
{
"parameters": {
"modelName": "models/gemini-2.0-flash-exp",
"options": {}
},
"id": "ed406930-dcd6-4eec-ab63-1643cc5e7155",
"name": "Google Gemini Chat Model (retrieval)",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
340,
1460
],
"typeVersion": 1
},
{
"parameters": {
"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.",
"height": 720,
"width": 420
},
"id": "8d9ce86e-dbb1-4b47-bc61-80ada00ad3c8",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1280,
440
],
"typeVersion": 1
}
],
"connections": {
"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
}
]
]
},
"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
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "0f576ed6-57bf-4a26-a54d-623148c38bda",
"id": "oaUiP1piK9Ih9T4I",
"tags": []
}
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About this workflow
google-drive-rag. Uses vectorStorePinecone, embeddingsGoogleGemini, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter. Event-driven trigger; 18 nodes.
Source: https://github.com/senaiapy/IA/blob/dee2e863a92473b40c171ee414b750d4a652f9ce/Templates/N8N/google_drive_rag.json — original creator credit. Request a take-down →
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