Muhammad Asadullah This workflow corresponds to n8n.io template #3199 — 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 →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "d4e5b3fc-0ab5-4900-b551-0bdac8f6b3e7",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1340,
1020
],
"parameters": {
"options": {
"temperature": 0.2
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "7cacd167-0172-4032-bf93-6184fb4edca9",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1220,
1760
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "=file_id",
"value": "={{ $('Loop Over Items').item.json.file_id}}"
},
{
"name": "file_name",
"value": "={{ $('Loop Over Items').item.json.file_name}}"
}
]
}
},
"jsonData": "={{ $json.data || $json.text || $json.appended_data }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "f3ce8818-db70-45ce-8ca4-9407ccc684e6",
"name": "Embeddings OpenAI1",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1060,
1820
],
"parameters": {
"model": "text-embedding-3-small",
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "7e10f8fb-8d93-46c9-9c02-f78f026b112e",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-740,
940
],
"parameters": {
"color": 4,
"width": 343,
"height": 489,
"content": "## Agent Tools for RAG"
},
"typeVersion": 1
},
{
"id": "ccc7b130-0fb3-4a4e-8858-34afcaf566a9",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1960,
1520
],
"parameters": {
"color": 5,
"width": 533,
"height": 507,
"content": "## Tool to Add a Google Drive File to Vector DB"
},
"typeVersion": 1
},
{
"id": "aaabdc32-0009-4076-8e90-f94dea0be81e",
"name": "Download File",
"type": "n8n-nodes-base.googleDrive",
"position": [
-780,
1720
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Loop Over Items').item.json.file_id }}"
},
"options": {
"googleFileConversion": {
"conversion": {
"docsToFormat": "text/plain",
"sheetsToFormat": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
}
}
},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"executeOnce": true,
"typeVersion": 3
},
{
"id": "6a57ed28-c1b6-4f8c-9d60-d8004dd0717f",
"name": "File Created",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
-1880,
1620
],
"parameters": {
"event": "fileCreated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "list",
"value": "16kHzSvQlrYZdpy2FcvInOAGMpWZGj1ai",
"cachedResultUrl": "https://drive.google.com/drive/folders/16kHzSvQlrYZdpy2FcvInOAGMpWZGj1ai",
"cachedResultName": "product-car-lease-docs"
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "9db93b4a-870e-46f9-a08f-921e72c548a5",
"name": "File Updated",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
-1880,
1840
],
"parameters": {
"event": "fileUpdated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "list",
"value": "16kHzSvQlrYZdpy2FcvInOAGMpWZGj1ai",
"cachedResultUrl": "https://drive.google.com/drive/folders/16kHzSvQlrYZdpy2FcvInOAGMpWZGj1ai",
"cachedResultName": "product-car-lease-docs"
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "ad0b03de-8305-4393-a920-4bcaa082c681",
"name": "Extract Document Text",
"type": "n8n-nodes-base.extractFromFile",
"position": [
120,
1980
],
"parameters": {
"options": {},
"operation": "text"
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "9d5fee3d-b6af-4e3f-9e7f-257a87292c88",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
-700,
1260
],
"parameters": {
"model": "text-embedding-3-small",
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "75af40d5-62b0-4faf-b1fd-37dab8feb143",
"name": "Delete Old Doc Rows",
"type": "n8n-nodes-base.supabase",
"onError": "continueRegularOutput",
"position": [
-940,
1800
],
"parameters": {
"tableId": "documents",
"operation": "delete",
"filterType": "string",
"filterString": "=metadata->>file_id=like.*{{ $json.file_id }}*"
},
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "20d282f6-ea7b-48a6-a0aa-b864a4d85396",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1800,
680
],
"parameters": {
"width": 1036,
"height": 485,
"content": "## RAG AI Agent with Chat Interface"
},
"typeVersion": 1
},
{
"id": "35e28ac3-4fd8-4179-9526-b6d15c87eaa6",
"name": "Respond to Webhook",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
-940,
720
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "7261cb7a-d3a6-4d20-8e5c-d4176e0b1dd7",
"name": "Edit Fields",
"type": "n8n-nodes-base.set",
"position": [
-1460,
800
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "9a9a245e-f1a1-4282-bb02-a81ffe629f0f",
"name": "chatInput",
"type": "string",
"value": "={{ $json?.chatInput || $json.body.chatInput || $json.body.query }} "
},
{
"id": "b80831d8-c653-4203-8706-adedfdb98f77",
"name": "sessionId",
"type": "string",
"value": "={{ $json?.sessionId || $json.body.sessionId}}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "a4dae2ba-f596-499a-a2cf-040501efaa7d",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-1720,
800
],
"parameters": {
"public": true,
"options": {}
},
"typeVersion": 1.1
},
{
"id": "c695b449-4624-468e-9cd7-605da16b7915",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
-1720,
1000
],
"parameters": {
"path": "9ba11544-5c4e-4f91-818a-08a4ecb596c5",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2
},
{
"id": "d300d76a-47e0-49df-9a21-5d334e68162c",
"name": "Extract PDF Text",
"type": "n8n-nodes-base.extractFromFile",
"position": [
60,
1200
],
"parameters": {
"options": {},
"operation": "pdf"
},
"typeVersion": 1
},
{
"id": "1f625839-c8f9-4eca-8616-eeaa0c3bd96c",
"name": "Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
"position": [
1220,
1980
],
"parameters": {
"chunkSize": 2000,
"chunkOverlap": 50
},
"typeVersion": 1
},
{
"id": "6064bfd7-eda9-4ab5-9c5c-59c197e5e3cf",
"name": "Summarize",
"type": "n8n-nodes-base.summarize",
"position": [
140,
1600
],
"parameters": {
"options": {
"outputFormat": "singleItem",
"disableDotNotation": true
},
"fieldsToSummarize": {
"values": [
{
"field": "data",
"aggregation": "append",
"includeEmpty": true
}
]
}
},
"typeVersion": 1
},
{
"id": "438dd4b2-81af-4ddc-a7b7-0d8509c57fc3",
"name": "RAG AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-1240,
800
],
"parameters": {
"text": "=user: {{ $json.chatInput }}\n\nAlways use ' Vector Store' tool to get correct iinformation.\nAlways ask questions and only provide limited information which exactly matches user's needs. \nAsk for each detail first, each need and requirement of the user.",
"options": {
"systemMessage": "=You are a helpful assistant."
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "bda5d65a-608b-41a5-8884-d85558020a27",
"name": "Switch",
"type": "n8n-nodes-base.switch",
"position": [
-580,
1720
],
"parameters": {
"rules": {
"values": [
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fa3c1e8c-3e54-423e-849d-390cf842870d",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Loop Over Items').item.json.file_type}}",
"rightValue": "application/pdf"
}
]
}
},
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "2ae7faa7-a936-4621-a680-60c512163034",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Loop Over Items').item.json.file_type}}",
"rightValue": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
}
]
}
},
{
"conditions": {
"options": {
"version": 1,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fc193b06-363b-4699-a97d-e5a850138b0e",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Loop Over Items').item.json.file_type}}",
"rightValue": "application/vnd.google-apps.document"
}
]
}
}
]
},
"options": {
"fallbackOutput": 2
}
},
"typeVersion": 3
},
{
"id": "de305c39-ce48-4e04-9167-db00a78d8e6d",
"name": "Insert into Supabase Vectorstore",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
1080,
1540
],
"parameters": {
"mode": "insert",
"options": {
"queryName": "match_documents"
},
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
}
},
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "69e46f85-77c3-45f6-96bc-4fff02b733d5",
"name": "Extract from Excel",
"type": "n8n-nodes-base.extractFromFile",
"position": [
-220,
1600
],
"parameters": {
"options": {
"headerRow": true
},
"operation": "xlsx"
},
"typeVersion": 1
},
{
"id": "049cfd79-66a0-4def-9034-fcb2f054b480",
"name": "Calculator",
"type": "@n8n/n8n-nodes-langchain.toolCalculator",
"position": [
-1040,
1040
],
"parameters": {},
"typeVersion": 1
},
{
"id": "dbe03d9d-e526-40ea-8737-85e11bb44359",
"name": "Loop Over Items",
"type": "n8n-nodes-base.splitInBatches",
"position": [
-1140,
1640
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "d94daf22-e6e6-423d-8def-4c4f4301229b",
"name": "FinishNode",
"type": "n8n-nodes-base.set",
"position": [
-820,
1540
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "78ef64a9-7023-40c3-9a4b-f6a33fc33d55",
"name": "response",
"type": "string",
"value": "done"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "6dc86b42-0b0b-44c1-9978-d558c3ef890b",
"name": "Wait",
"type": "n8n-nodes-base.wait",
"position": [
1660,
1980
],
"parameters": {
"amount": 1
},
"typeVersion": 1.1
},
{
"id": "736594be-6e78-43d8-826f-ed024f85c9fb",
"name": "Set File ID1",
"type": "n8n-nodes-base.set",
"position": [
-1580,
1760
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "10646eae-ae46-4327-a4dc-9987c2d76173",
"name": "file_id",
"type": "string",
"value": "={{ $json.id }}"
},
{
"id": "f4536df5-d0b1-4392-bf17-b8137fb31a44",
"name": "file_type",
"type": "string",
"value": "={{ $json.mimeType }}"
},
{
"id": "ee8b4d04-665b-40a7-8542-981a2b224c9c",
"name": "file_name",
"type": "string",
"value": "={{ $json.name }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9eebfa64-24ba-4df4-911a-722827c0c7f3",
"name": "Split Out1",
"type": "n8n-nodes-base.splitOut",
"position": [
-1380,
1640
],
"parameters": {
"options": {},
"fieldToSplitOut": "file_id, file_type, file_name"
},
"typeVersion": 1
},
{
"id": "9c02b8fd-ca9a-49d5-99d0-e26d0dc685b7",
"name": "Code1",
"type": "n8n-nodes-base.code",
"position": [
-20,
1600
],
"parameters": {
"jsCode": "// This function processes each Excel row individually\nfor (const item of items) {\n // Create a formatted string representation of the complete row\n const rowData = {};\n \n // Copy all fields from the Excel row\n for (const key in item.json) {\n rowData[key] = item.json[key];\n }\n \n // Create a single JSON object for the entire row\n item.json = {\n data: JSON.stringify(rowData),\n rowData: rowData // Keep the original data structure too\n };\n}\n\nreturn items;"
},
"typeVersion": 2
},
{
"id": "b67017fe-f12e-4456-b578-46ea97a5ec6c",
"name": "Split Out",
"type": "n8n-nodes-base.splitOut",
"position": [
300,
1600
],
"parameters": {
"options": {},
"fieldToSplitOut": "appended_data"
},
"typeVersion": 1
},
{
"id": "6b194d3c-d184-4426-862d-9f6df8a9cf70",
"name": "Loop Over Items1",
"type": "n8n-nodes-base.splitInBatches",
"position": [
500,
1620
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "88707cf6-10f6-4154-bd12-3d519afc8584",
"name": "FinishNode1",
"type": "n8n-nodes-base.set",
"position": [
820,
1400
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "78ef64a9-7023-40c3-9a4b-f6a33fc33d55",
"name": "response",
"type": "string",
"value": "done"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "b2643480-0ac3-42b2-960c-03d8d5dcb4f6",
"name": "Cars Data Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
"position": [
-720,
1100
],
"parameters": {
"mode": "retrieve-as-tool",
"topK": 10,
"options": {},
"toolName": "cars_data",
"tableName": {
"__rl": true,
"mode": "list",
"value": "documents",
"cachedResultName": "documents"
},
"toolDescription": "Use this tool to Get the cars related data to answer the query."
},
"credentials": {
"supabaseApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "45e7cd38-667b-4080-9da7-f1f07e3913aa",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-1160,
1020
],
"parameters": {},
"typeVersion": 1.3
}
],
"connections": {
"Wait": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
},
{
"node": "Loop Over Items1",
"type": "main",
"index": 0
}
]
]
},
"Code1": {
"main": [
[
{
"node": "Summarize",
"type": "main",
"index": 0
}
]
]
},
"Switch": {
"main": [
[
{
"node": "Extract PDF Text",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract from Excel",
"type": "main",
"index": 0
}
],
[
{
"node": "Extract Document Text",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "Loop Over Items1",
"type": "main",
"index": 0
}
]
]
},
"Summarize": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"Calculator": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Split Out1": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "RAG AI Agent",
"type": "main",
"index": 0
}
]
]
},
"File Created": {
"main": [
[
{
"node": "Set File ID1",
"type": "main",
"index": 0
}
]
]
},
"File Updated": {
"main": [
[
{
"node": "Set File ID1",
"type": "main",
"index": 0
}
]
]
},
"RAG AI Agent": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
}
]
]
},
"Set File ID1": {
"main": [
[
{
"node": "Split Out1",
"type": "main",
"index": 0
}
]
]
},
"Download File": {
"main": [
[
{
"node": "Switch",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "RAG AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[
{
"node": "FinishNode",
"type": "main",
"index": 0
}
],
[
{
"node": "Delete Old Doc Rows",
"type": "main",
"index": 0
}
]
]
},
"Extract PDF Text": {
"main": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items1": {
"main": [
[
{
"node": "FinishNode1",
"type": "main",
"index": 0
}
],
[
{
"node": "Insert into Supabase Vectorstore",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Cars Data Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "RAG AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings OpenAI1": {
"ai_embedding": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Extract from Excel": {
"main": [
[
{
"node": "Code1",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "ai_document",
"index": 0
}
]
]
},
"Delete Old Doc Rows": {
"main": [
[
{
"node": "Download File",
"type": "main",
"index": 0
}
]
]
},
"Extract Document Text": {
"main": [
[
{
"node": "Insert into Supabase Vectorstore",
"type": "main",
"index": 0
}
]
]
},
"Cars Data Vector Store": {
"ai_tool": [
[
{
"node": "RAG AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Insert into Supabase Vectorstore": {
"main": [
[
{
"node": "Wait",
"type": "main",
"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.
googleDriveOAuth2ApiopenAiApisupabaseApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This workflow creates a conversational assistant that can answer questions based on your Google Drive documents. It automatically processes various file types and uses Retrieval-Augmented Generation (RAG) to provide accurate answers based on your document content. Monitors…
Source: https://n8n.io/workflows/3199/ — original creator credit. Request a take-down →
Related workflows
Workflows that share integrations, category, or trigger type with this one. All free to copy and import.
Your AI workforce is ready. Are you?
Google Sheets Tool, Mcp Trigger, Google Drive +29
This comprehensive workflow bundle is designed as a powerful starter kit, enabling you to build a multi-functional AI assistant on Telegram. It seamlessly integrates AI-powered voice interactions, an
Telegram Trigger, Telegram, OpenAI +19
This n8n template automatically classifies incoming emails (Sales, Support, Internal, Finance, Promotions) and routes them to a dedicated OpenAI LLM Agent for processing. Depending on the category, th
OpenAI, Gmail, Text Classifier +16
Automate Outreach Prospect automates finding, enriching, and messaging potential partners (like restaurants, malls, and bars) using Apify Google Maps scraping, Perplexity enrichment, OpenAI LLMs, Goog
@Devlikeapro/N8N Nodes Waha, Google Drive Trigger, @Apify/N8N Nodes Apify +14
Chat with docs - 5minAI New version. Uses httpRequest, documentDefaultDataLoader, textSplitterRecursiveCharacterTextSplitter, embeddingsOpenAi. Event-driven trigger; 62 nodes.
HTTP Request, Document Default Data Loader, Text Splitter Recursive Character Text Splitter +10