Yashraj singh sisodiya This workflow corresponds to n8n.io template #8344 — 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": "3v8t7FV5f5vkU9LM",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Data analytics Workflow 4 bakery.",
"tags": [],
"nodes": [
{
"id": "e559ce26-07d1-4bca-aa53-082ff8480e63",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
-384,
-192
],
"parameters": {
"options": {}
},
"typeVersion": 1.3
},
{
"id": "517129d9-18fc-4bf3-8193-8d8ed8fb8b1f",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
-112,
-192
],
"parameters": {
"options": {
"systemMessage": "You are a professional Data Analysis Assistant specialized in Excel datasets. \nYou never assume what the user wants \u2014 you only respond based on their exact question. \n\nBehavior & Tone:\n- Clear, concise, and professional.\n- Always answer in plain English, avoiding unnecessary jargon.\n- Use short, structured insights (bullets, small tables, or compact summaries).\n- Keep responses brief but meaningful \u2014 no long reports unless explicitly requested.\n- Provide actionable insights when appropriate, but do not invent analysis that was not asked.\n\nInstructions:\n1. Only analyze the Excel data when the user asks a specific question.\n2. Never output full raw data unless explicitly requested.\n3. Present results in a compact format (e.g., weekly breakdown, totals, highlights) if the question relates to time or quantities.\n4. If the data is insufficient, state the limitation clearly.\n5. Keep a balanced tone: informative, decision-oriented, and easy to understand.\n6. Never assume tasks \u2014 wait for user instructions before analyzing. \n7. If a recommendation is reasonable (like stocking, trends, or anomalies), keep it short and relevant to the user\u2019s query.\n"
}
},
"typeVersion": 2.2
},
{
"id": "ed8f4fe1-272f-4657-ac41-36ffb7456bb1",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
-16,
32
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "d1a293d6-7e5b-4543-9107-9caf45b4051a",
"name": "Retrieve bakery data",
"type": "n8n-nodes-base.googleSheetsTool",
"position": [
320,
-80
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 764145761,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1dCCQzjoDZak-mQD1iyGd5aHKGFeh15fsBPUIoTgAYGw/edit#gid=764145761",
"cachedResultName": "Full Month"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1dCCQzjoDZak-mQD1iyGd5aHKGFeh15fsBPUIoTgAYGw",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1dCCQzjoDZak-mQD1iyGd5aHKGFeh15fsBPUIoTgAYGw/edit?usp=drivesdk",
"cachedResultName": "Bakery data 1 month"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.7
},
{
"id": "1106cbea-591d-4dd4-88dd-03ad52052e38",
"name": "Azure OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatAzureOpenAi",
"position": [
-400,
32
],
"parameters": {
"model": "gpt-5-mini",
"options": {}
},
"credentials": {
"azureOpenAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "dc450b50-9326-40a1-a25a-c044c459a1ff",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-464,
-512
],
"parameters": {
"width": 256,
"height": 496,
"content": "## Workflow: **Data Analytics for Bakery**\n\n### Node 1: **When chat message received**\n\n*Purpose:*\nThis node acts as the **entry point** of the workflow. It triggers the process whenever a user sends a **chat message**.\n\n"
},
"typeVersion": 1
},
{
"id": "982b0dd2-ac23-47d6-a91b-5df8d2d42527",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-192,
-512
],
"parameters": {
"color": 3,
"width": 336,
"height": 496,
"content": "### Node 2: **AI Agent**\n\n*Purpose:*\nThis is the **central AI reasoning engine**. It processes the user\u2019s request, interprets the context, and decides how to handle it.\n\n*Key roles:*\n\n* Ensures **professional and concise** responses\n* Analyzes bakery Excel data only when asked\n* Provides insights in **plain English** with short, actionable summaries\n"
},
"typeVersion": 1
},
{
"id": "4fa77358-11a8-4c21-bdb2-c1f606773d17",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-128,
144
],
"parameters": {
"color": 2,
"width": 320,
"height": 272,
"content": "### Node 3: **Simple Memory**\n\n*Purpose:*\nThis node stores **short-term conversational memory**.\n\n*Key roles:*\n\n* Keeps track of the **previous chat context**\n* Allows the AI to maintain continuity during ongoing discussions\n"
},
"typeVersion": 1
},
{
"id": "3e234b21-725b-4aaa-a767-a2a05e744a55",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
208,
-384
],
"parameters": {
"color": 4,
"width": 320,
"height": 432,
"content": "### Node 4: **Retrieve bakery data**\n\n*Purpose:*\nThis node connects to the **Google Sheets bakery dataset**.\n\n*Key roles:*\n\n* Retrieves sales and stock data from the linked **spreadsheet**\n* Provides structured data for the AI Agent to analyze\n* Dataset: [Bakery Data Sheet](https://docs.google.com/spreadsheets/d/1dCCQzjoDZak-mQD1iyGd5aHKGFeh15fsBPUIoTgAYGw/edit?usp=drivesdk)\n"
},
"typeVersion": 1
},
{
"id": "4b5eb0ce-e311-4bed-821b-fcf7e5cf74ba",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-528,
176
],
"parameters": {
"color": 6,
"width": 352,
"height": 336,
"content": "### Node 5: **Azure OpenAI Chat Model**\n\n*Purpose:*\nThis node provides the **language model backend** for the AI Agent.\n\n*Key roles:*\n\n* Uses **GPT-based reasoning** for natural conversation\n* Handles query understanding and response generation\n* Ensures responses follow the defined **tone and style**\n"
},
"typeVersion": 1
}
],
"active": true,
"settings": {
"executionOrder": "v1"
},
"versionId": "fe8411cd-b13e-40b3-beca-c579c00be0fc",
"connections": {
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Retrieve bakery data": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Azure OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"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.
azureOpenAiApigoogleSheetsOAuth2Api
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About this workflow
The aim of the Bakery Data Analytics Workflow is to automate the process of analyzing bakery sales and stock data stored in Google Sheets. It allows bakery owners or managers to interact with an AI assistant via chat and receive clear, concise, and actionable insights about…
Source: https://n8n.io/workflows/8344/ — original creator credit. Request a take-down →
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