Rahul Joshi 
This workflow corresponds to n8n.io template #10828 — 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": "zncb3ZRHYeJMrDYv",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "AI Chat Response Generation with Google Sheets Context and Pinecone RAG Memory",
"tags": [],
"nodes": [
{
"id": "33071869-c1ec-4cde-9cac-9e654b609658",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
-32
],
"parameters": {
"width": 419,
"height": 544,
"content": "## \ud83e\udd16 AI Chat Assistant with RAG & Auto-Logging\n\n### How it works\nThis workflow powers an intelligent chat assistant that retrieves context from a Pinecone knowledge base and Google Sheets, responds naturally using OpenAI GPT-5, and logs all conversations automatically. It also includes a weekly email export feature that sends chat history summaries via Gmail.\n\n### Setup steps\n1. **Connect credentials**: OpenAI API, Google Sheets OAuth2, Pinecone API, Google Drive OAuth2, Gmail OAuth2\n2. **Configure Google Sheet**: Update the document ID to point to your conversation log sheet\n3. **Set Pinecone index**: Replace `whatsappchatbot` with your vector database index name\n4. **Test the chat**: Use the chat trigger URL to send a test message\n5. **Upload knowledge**: Add files to the Google Drive folder to auto-index into Pinecone"
},
"typeVersion": 1
},
{
"id": "41cffb83-bd63-44cb-8504-a04315ce6025",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
560
],
"parameters": {
"color": 2,
"width": 331,
"height": 354,
"content": "## \ud83d\udcac Chat Interface & Pre-Processing\nReceives user messages via webhook, enriches them with intent/topic metadata, then routes to the AI agent for context-aware responses."
},
"typeVersion": 1
},
{
"id": "0318e95a-3c1d-404d-8610-20ce2dd360dd",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1312,
560
],
"parameters": {
"color": 2,
"width": 668,
"height": 579,
"content": "## \ud83e\udde0 AI Agent Core\nGPT-5 agent with memory, JSON output enforcement, and dual tools: retrieves context from Google Sheets (structured data) and Pinecone (semantic knowledge base)."
},
"typeVersion": 1
},
{
"id": "29cffe39-e931-4389-8c80-cf83dabc1a89",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1984,
560
],
"parameters": {
"color": 2,
"width": 314,
"height": 434,
"content": "## \ud83d\udcca Conversation Logging\nEvery chat interaction is logged to Google Sheets with timestamp, user input, detected intent, and AI response for analytics and audit trails."
},
"typeVersion": 1
},
{
"id": "7a5c8124-a076-423a-b351-d33a9a127395",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1168,
2080
],
"parameters": {
"color": 2,
"width": 827,
"height": 705,
"content": "## \ud83d\udcc2 Knowledge Base Auto-Indexing\nMonitors a Google Drive folder for new files (PDFs, docs), downloads them, splits into chunks, generates embeddings, and stores in Pinecone for RAG retrieval."
},
"typeVersion": 1
},
{
"id": "ac997af3-8cd9-4ffc-92b9-71a9837cb367",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1184,
1440
],
"parameters": {
"color": 2,
"width": 1457,
"height": 465,
"content": "## \ud83d\udce7 Weekly Chat History Export\nRuns every Monday at 10 PM, aggregates all logged conversations from Google Sheets, converts to a text file, and emails it as an attachment for record-keeping."
},
"typeVersion": 1
},
{
"id": "3acb4a69-4716-4afb-9d23-48e61f4a1896",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
2432,
2576
],
"parameters": {
"color": 3,
"width": 340.45801526717554,
"height": 184.88549618320613,
"content": "## \ud83d\udd10 Credentials & Security\nRequires OAuth2 for Google services, API keys for OpenAI and Pinecone. Replace all credential IDs and document/folder IDs with your own. Never share API keys publicly."
},
"typeVersion": 1
},
{
"id": "b3752497-5f33-4afb-88f9-7dcb1670f364",
"name": "Short-Term Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
1568,
960
],
"parameters": {
"sessionKey": "chat-rag-session",
"sessionIdType": "customKey",
"contextWindowLength": 7
},
"typeVersion": 1.3
},
{
"id": "07e78867-bb70-43d4-9229-636f9a8d6193",
"name": "AI Agent (Chat Composer)",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1600,
752
],
"parameters": {
"text": "=User message: {{ $json.content }}\nIntent: {{ $json.intent }}\nTopic: {{ $json.topic || \"general\" }}\nContext (from Google Sheets or memory): {{ $json.context || $memory || \"No context retrieved\" }}\n",
"options": {
"systemMessage": "=You are \"Content Agent Chat Responder\", a professional AI assistant inside an n8n automation system.\n\nYour role:\n- Communicate naturally, professionally, and concisely.\n- Use provided context from Google Sheets or memory when available.\n- If the user greets you (like \"hi\", \"hello\", \"hey\"), respond politely and ask how you can help.\n- If the user asks about SEO, content drafts, briefs, optimization, or publishing, respond specifically based on context or ask clarifying questions if missing.\n- If the intent is \"chat\" but the content clearly mentions a topic, treat it as a mixed chat + content query.\n- If context is missing, ask the user for more information. \n\n\n### Behavior Rules:\n- Always greet politely and warmly.\n- If the user asks about our company, products, or projects, **use the context retrieved from Pinecone (knowledge base) as your source of truth**.\n- Give clear, structured, and easy-to-understand answers \u2014 avoid long walls of text.\n- When appropriate, format answers into short paragraphs, bullet points, or step-by-step explanations.\n- Sound confident, approachable, and \"sales-ready\" \u2014 as if you are introducing the company to a client.\n- If the knowledge base does not contain the answer, respond naturally but say you will get back with more details.\n- Maintain a human-like flow: use follow-up questions, confirmations, and conversational phrases (e.g., \"That's a great question!\" or \"Let me explain in simple terms\u2026\").\n\n### Example Scenarios:\n- If a client asks: \"What is this project about?\" \u2192 Provide a short overview from Pinecone, structured like a pitch.\n- If they ask: \"Can you explain in detail?\" \u2192 Give a more thorough breakdown in a clear format.\n- If they greet or ask something general \u2192 continue the chat naturally, like a real human. \n\n- Always output concise structured JSON in the format:\n{\n \"reply\": \"Your full response text\",\n \"context_used\": [\"list of any context used or none\"]\n}\n"
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 2.1
},
{
"id": "2e25a1fd-88b8-44e8-bde1-17acd49729cd",
"name": "Output Parser (JSON Enforcement)",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1856,
896
],
"parameters": {
"jsonSchemaExample": "{\n \"reply\": \"string\",\n \"context_used\": [\"string\"]\n}\n"
},
"typeVersion": 1.3
},
{
"id": "68c48bd8-ff0b-4c94-b9f7-2c3fb9def1d5",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
1408,
976
],
"parameters": {
"model": {
"__rl": true,
"mode": "id",
"value": "="
},
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "6cc6c210-636a-46ad-8e1a-cc3292639d6e",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
1120,
752
],
"parameters": {
"options": {}
},
"typeVersion": 1.3
},
{
"id": "d686aa69-9e35-43b7-9f89-64690528db5b",
"name": "Google Drive Trigger",
"type": "n8n-nodes-base.googleDriveTrigger",
"position": [
1200,
2224
],
"parameters": {
"event": "fileCreated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyMinute"
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "id",
"value": "="
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "954d129c-2d36-4ff1-8474-3b2f3384c8d5",
"name": "Download file",
"type": "n8n-nodes-base.googleDrive",
"position": [
1408,
2224
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "c763f13b-0e7f-4abe-ae0d-f029ab45c8e2",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1696,
2448
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "file-name",
"value": "={{ $('Download file').item.json.name }}"
}
]
}
},
"dataType": "binary",
"textSplittingMode": "custom"
},
"typeVersion": 1.1
},
{
"id": "3f237c12-20f4-4e77-a991-f231875dad10",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1776,
2624
],
"parameters": {
"options": {},
"chunkSize": 500,
"chunkOverlap": 200
},
"typeVersion": 1
},
{
"id": "14e92af7-eeb2-4afa-9543-62c87ba2074f",
"name": "Embeddings OpenAI",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1520,
2464
],
"parameters": {
"options": {
"dimensions": 512
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "fccdff58-7a8a-44a8-9a1c-a20d681b0438",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
1216,
1552
],
"parameters": {
"rule": {
"interval": [
{
"field": "weeks",
"triggerAtDay": [
1
],
"triggerAtHour": 22
}
]
}
},
"typeVersion": 1.2
},
{
"id": "b357b118-d803-4c9d-ae3d-324eee2cca08",
"name": "Aggregate",
"type": "n8n-nodes-base.aggregate",
"position": [
1744,
1552
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "8ad58732-4dec-4649-a1c6-0b9a6b08eb6a",
"name": "Get Previous Content from Sheet",
"type": "n8n-nodes-base.googleSheetsTool",
"position": [
1696,
992
],
"parameters": {
"sheetName": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": ""
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "="
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
},
{
"id": "8add9b4b-4086-4a8c-be4e-47c591c864ea",
"name": "Conversation Logging",
"type": "n8n-nodes-base.googleSheets",
"position": [
2080,
752
],
"parameters": {
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "id",
"value": ""
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "="
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
},
{
"id": "ef7c257c-accd-47db-a799-21b9f38a933c",
"name": "Pinecone Vector Store Insert",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
1648,
2224
],
"parameters": {
"mode": "insert",
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "id",
"value": "="
},
"embeddingBatchSize": 1000
},
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "3e139499-ba6e-465d-b464-12d74fa0884f",
"name": "Pinecone Vector Store Query for Knowledge Base",
"type": "@n8n/n8n-nodes-langchain.vectorStorePinecone",
"position": [
1856,
1152
],
"parameters": {
"mode": "retrieve-as-tool",
"topK": 5,
"options": {},
"pineconeIndex": {
"__rl": true,
"mode": "list",
"value": "whatsappchatbot",
"cachedResultName": "whatsappchatbot"
},
"toolDescription": "=Retrieve data from the Pinecone knowledge base and use it to answer user queries about the company, products, or projects in a well-structured, human-like manner"
},
"credentials": {
"pineconeApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "c3d32f3d-4804-49dd-8ee2-7da94bea33e0",
"name": "Embeddings OpenAI Query for Chat modal",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1808,
1312
],
"parameters": {
"options": {
"dimensions": 512
}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "83b6174f-12c9-440f-a021-7703570a3b48",
"name": "Get Data from Sheet.",
"type": "n8n-nodes-base.googleSheets",
"position": [
1456,
1552
],
"parameters": {
"sheetName": {
"__rl": true,
"mode": "list",
"value": "",
"cachedResultUrl": "",
"cachedResultName": ""
},
"documentId": {
"__rl": true,
"mode": "id",
"value": "="
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
},
{
"id": "561655e9-9810-4cd4-a770-794d7a60f6cb",
"name": "Convert Data to file",
"type": "n8n-nodes-base.convertToFile",
"position": [
1968,
1552
],
"parameters": {
"options": {},
"operation": "toText",
"sourceProperty": "data"
},
"typeVersion": 1.1
},
{
"id": "5f10e45a-6910-4cc3-897b-ba198d43943d",
"name": "Check File Exist",
"type": "n8n-nodes-base.if",
"position": [
2176,
1552
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a10217a0-9aa9-47eb-9179-b1760ae4fbd4",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $binary.data.mimeType }}",
"rightValue": "application/json"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "e1faaf7b-1b72-460d-94fa-dbdb719e9256",
"name": "Send Chat History with attachment",
"type": "n8n-nodes-base.gmail",
"position": [
2464,
1536
],
"parameters": {
"message": "=Hi [Name], \n\nPlease find attached your chat history from our conversation on chat_history_{{ $now.format('DD') }}. Feel free to refer back to this anytime, and let me know if you have any questions! \n\nBest regards, [Your Name]",
"options": {
"attachmentsUi": {
"attachmentsBinary": [
{}
]
}
},
"subject": "=chat_history_{{ $now.format('DD') }}",
"emailType": "text"
},
"credentials": {
"gmailOAuth2": {
"name": "<your credential>"
}
},
"typeVersion": 2.1
},
{
"id": "8a43b13d-92ea-4847-8080-fa1a8b373253",
"name": "Format Data For AI Agent ",
"type": "n8n-nodes-base.set",
"position": [
1376,
752
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "d917c6d3-ae35-4140-99c8-ae390866e735",
"name": "intent",
"type": "string",
"value": "=Chat"
},
{
"id": "e697ec89-26ed-4fb3-95a9-4a0cc6eed36d",
"name": "topic",
"type": "string",
"value": "=AI Seo Basics"
},
{
"id": "f5a88ad2-7f57-4971-88ea-bad9e1c10992",
"name": "content_id",
"type": "string",
"value": "=C001"
},
{
"id": "06fb1d17-f233-4b22-af27-cd3351c971a0",
"name": "parameter",
"type": "object",
"value": "={{ $json.parameter }}"
}
]
}
},
"typeVersion": 3.4
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "b76952bf-3c23-4299-8602-50580cbc6117",
"connections": {
"Aggregate": {
"main": [
[
{
"node": "Convert Data to file",
"type": "main",
"index": 0
}
]
]
},
"Download file": {
"main": [
[
{
"node": "Pinecone Vector Store Insert",
"type": "main",
"index": 0
}
]
]
},
"Check File Exist": {
"main": [
[
{
"node": "Send Chat History with attachment",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Get Data from Sheet.",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store Insert",
"type": "ai_embedding",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Short-Term Memory": {
"ai_memory": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "ai_memory",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Pinecone Vector Store Insert",
"type": "ai_document",
"index": 0
}
]
]
},
"Get Data from Sheet.": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Google Drive Trigger": {
"main": [
[
{
"node": "Download file",
"type": "main",
"index": 0
}
]
]
},
"Convert Data to file": {
"main": [
[
{
"node": "Check File Exist",
"type": "main",
"index": 0
}
]
]
},
"AI Agent (Chat Composer)": {
"main": [
[
{
"node": "Conversation Logging",
"type": "main",
"index": 0
}
]
]
},
"Format Data For AI Agent ": {
"main": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Format Data For AI Agent ",
"type": "main",
"index": 0
}
]
]
},
"Get Previous Content from Sheet": {
"ai_tool": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "ai_tool",
"index": 0
}
]
]
},
"Output Parser (JSON Enforcement)": {
"ai_outputParser": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings OpenAI Query for Chat modal": {
"ai_embedding": [
[
{
"node": "Pinecone Vector Store Query for Knowledge Base",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Pinecone Vector Store Query for Knowledge Base": {
"ai_tool": [
[
{
"node": "AI Agent (Chat Composer)",
"type": "ai_tool",
"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.
gmailOAuth2googleDriveOAuth2ApigoogleSheetsOAuth2ApiopenAiApipineconeApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
Empower your workflows with an intelligent AI chat assistant that retrieves real-time context from Google Sheets and a Pinecone knowledge base using Retrieval-Augmented Generation (RAG). 🤖📂 This workflow processes chat messages, retrieves relevant contextual data, generates…
Source: https://n8n.io/workflows/10828/ — 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.
This workflow acts as a 24/7 sales agent, engaging leads across WhatsApp, Instagram, Facebook, Telegram, and your website. It intelligently transcribes audio messages, answers questions using a knowle
Chat Trigger, Memory Postgres Chat, Tool Workflow +20
• Create a Google Drive folder to watch. • Connect your Google Drive account in n8n and authorize access. • Point the Google Drive Trigger node to this folder (new/modified files trigger the flow).
Agent, Chat Trigger, Memory Buffer Window +14
⚡AI-Powered YouTube Playlist & Video Summarization and Analysis v2. Uses lmChatGoogleGemini, agent, splitOut, chainLlm. Chat trigger; 72 nodes.
Google Gemini Chat, Agent, Chain Llm +11
This n8n workflow transforms entire YouTube playlists or single videos into interactive knowledge bases you can chat with. Ask questions and get summaries without needing to watch hours of content. 🔗
Google Gemini Chat, Agent, Chain Llm +11
The workflow operates through a three-step process that handles incoming chat messages with intelligent tool orchestration: Message Trigger: The node triggers whenever a user message arrives and passe
Chat Trigger, Memory Postgres Chat, OpenAI Embeddings +16