This workflow follows the Chainllm → Google Sheets 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": "KMsRice",
"nodes": [
{
"parameters": {
"updates": [
"message"
],
"additionalFields": {}
},
"type": "n8n-nodes-base.telegramTrigger",
"typeVersion": 1.2,
"position": [
0,
0
],
"id": "dd85dbe0-1f48-4be1-b726-a63a575a330c",
"name": "Telegram Trigger",
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "={{ $json.message.text }}",
"messages": {
"messageValues": [
{
"message": "You are a sack sales data extraction assistant. Extract structured sales data from ANY natural language message format. The user message might be formal or casual. Extract quantities for these sack sizes: - 5kg sacks (also called: small, 5kg, five kg) - 10kg sacks (also called: medium, 10kg, ten kg) - 25kg sacks (also called: large, 25kg, twenty-five kg) - 50kg sacks (also called: extra large, XL, 50kg, fifty kg) Return ONLY a valid JSON object with NO additional text before or after: { \"date\": null, \"sack_5kg\": 0, \"sack_10kg\": 0, \"sack_25kg\": 0, \"sack_50kg\": 0, \"notes\": \"\" } Examples of valid inputs: - \"Hi! Today: 7 units of 5kg, 7 of 10kg, 7 of 25kg\" - \"5kg=5, 10kg=10, 25kg=5, 50kg=3\" - \"Sold 23 sacks: 10 small, 8 medium, 5 large\" - \"November 5: 10 of 5kg, 20 of 10kg\" (extract the date if mentioned) Rules: 1. If date is NOT mentioned, set date to null (not a made-up date) 2. If date IS mentioned, convert to YYYY-MM-DD format 3. If a sack size is not mentioned, set to 0 4. Extract numbers from natural language (seven \u2192 7, ten \u2192 10) 5. Return ONLY the JSON object, no explanations or extra text"
}
]
},
"batching": {}
},
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"typeVersion": 1.7,
"position": [
416,
0
],
"id": "a6ef73f5-1e33-4e3d-a956-c74822f2b61c",
"name": "Basic LLM Chain"
},
{
"parameters": {
"model": {
"__rl": true,
"value": "gpt-4o-mini",
"mode": "list",
"cachedResultName": "gpt-4o-mini"
},
"options": {}
},
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"typeVersion": 1.2,
"position": [
544,
128
],
"id": "78f7c60c-93bd-44a8-aa7a-82d855496fe5",
"name": "OpenAI Chat Model",
"notesInFlow": false,
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"notes": "Purpose: Parse natural language sales input\n\nPrompt Template:\n\"You are a sales data extraction assistant. Extract structured data from the following message:\n\nMessage: {{$json.message.text}}\n\nExtract and return ONLY a JSON object with these fields:\n{\n \"date\": \"YYYY-MM-DD\",\n \"amount\": number,\n \"quantity\": number,\n \"product_category\": \"string\",\n \"notes\": \"string\"\n}\n\nIf the user doesn't specify a date, use today's date. If information is missing, use null.\nRespond ONLY with valid JSON, no additional text.\"\n\nConfiguration:\n- Temperature: 0.1 (for consistency)\n- Max Tokens: 500"
},
{
"parameters": {
"jsCode": "const message = $input.first().json.message?.text || $input.first().json.chatInput;\n\n// Get AI response - Basic LLM Chain outputs to \"text\" field\nconst aiResponse = $input.first().json.text || \n $input.first().json.output || \n $input.first().json.choices?.[0]?.message?.content;\n\n// Parse AI response\nlet salesData;\ntry {\n // Try to extract JSON from AI response\n const jsonMatch = aiResponse.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) {\n throw new Error(\"No JSON found\");\n }\n salesData = JSON.parse(jsonMatch[0]);\n} catch (error) {\n return [{\n json: {\n error: true,\n message: \"Invalid format. Please try again.\\n\\nExample: '5kg=5, 10kg=10, 25kg=5, 50kg=3'\",\n telegram_chat_id: $('Telegram Trigger').item.json.message.chat.id\n }\n }];\n}\n// Always use today's date unless a valid recent date is provided\nconst today = new Date();\nconst todayString = today.toISOString().split('T')[0];\n\nif (!salesData.date || salesData.date === null || salesData.date === \"null\") {\n // No date provided - use today\n salesData.date = todayString;\n} else {\n // Check if the date is reasonable (within last 30 days or future 7 days)\n const providedDate = new Date(salesData.date);\n const daysDiff = (providedDate - today) / (1000 * 60 * 60 * 24);\n \n if (daysDiff < -30 || daysDiff > 7) {\n // Date is too old or too far in future - use today instead\n salesData.date = todayString;\n }\n}\n\n// Define prices (adjust to your actual prices)\nconst PRICES = {\n sack_5kg: 50,\n sack_10kg: 100,\n sack_25kg: 250,\n sack_50kg: 500\n};\n\n// Ensure all values are numbers\nsalesData.sack_5kg = Number(salesData.sack_5kg) || 0;\nsalesData.sack_10kg = Number(salesData.sack_10kg) || 0;\nsalesData.sack_25kg = Number(salesData.sack_25kg) || 0;\nsalesData.sack_50kg = Number(salesData.sack_50kg) || 0;\n\n// Calculate totals\nconst totalUnits = salesData.sack_5kg + \n salesData.sack_10kg + \n salesData.sack_25kg + \n salesData.sack_50kg;\n\nconst revenue = (salesData.sack_5kg * PRICES.sack_5kg) +\n (salesData.sack_10kg * PRICES.sack_10kg) +\n (salesData.sack_25kg * PRICES.sack_25kg) +\n (salesData.sack_50kg * PRICES.sack_50kg);\n\n// Validate\nif (totalUnits === 0) {\n return [{\n json: {\n error: true,\n message: \"No sales data found. Please specify quantities.\\n\\nExample: 'Today sold 5 of 5kg, 10 of 10kg'\",\n telegram_chat_id: $('Telegram Trigger').item.json.message.chat.id\n }\n }];\n}\n\n// Set default date if not provided\nif (!salesData.date) {\n const today = new Date();\n salesData.date = today.toISOString().split('T')[0];\n}\n\n// Enrich data\nsalesData.total_units = totalUnits;\nsalesData.revenue = revenue;\nsalesData.salesperson = $('Telegram Trigger').item.json.message.from.username || \n $('Telegram Trigger').item.json.message.from.first_name || \n 'Unknown';\nsalesData.telegram_user_id = $('Telegram Trigger').item.json.message.from.id;\nsalesData.telegram_chat_id = $('Telegram Trigger').item.json.message.chat.id;\nsalesData.timestamp = new Date().toISOString();\nsalesData.raw_message = message;\nsalesData.error = false; // IMPORTANT: Set error to false on success\n\nreturn [{ json: salesData }];"
},
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
736,
0
],
"id": "f1195d34-bfaa-4f5b-80d5-7964f3ffb302",
"name": "Code in JavaScript"
},
{
"parameters": {
"operation": "append",
"documentId": {
"__rl": true,
"value": "1QvcxnrLSf6jlRLOgOG7oT-CGSm_ARK1ljTgbITv3Ums",
"mode": "list",
"cachedResultName": "KM's Sales Management",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QvcxnrLSf6jlRLOgOG7oT-CGSm_ARK1ljTgbITv3Ums/edit?usp=drivesdk"
},
"sheetName": {
"__rl": true,
"value": "gid=0",
"mode": "list",
"cachedResultName": "Daily_Sales",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1QvcxnrLSf6jlRLOgOG7oT-CGSm_ARK1ljTgbITv3Ums/edit#gid=0"
},
"columns": {
"mappingMode": "defineBelow",
"value": {
"Date": "={{ $json.date }}\n",
"5kg Sacks": "={{ $json.sack_5kg }}\n",
"10kg Sacks": "={{ $json.sack_10kg }}",
"25kg Sacks": "={{ $json.sack_25kg }}",
"50kg Sacks": "={{ $json.sack_50kg }}",
"Revenue": "={{ $json.revenue }}",
"Notes": "={{ $json.notes }}",
"Timestamp": "= {{ $json.timestamp }}",
"Total Units": "={{ $json.total_units }}"
},
"matchingColumns": [],
"schema": [
{
"id": "Date",
"displayName": "Date",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "5kg Sacks",
"displayName": "5kg Sacks",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "10kg Sacks",
"displayName": "10kg Sacks",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "25kg Sacks",
"displayName": "25kg Sacks",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "50kg Sacks",
"displayName": "50kg Sacks",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "Total Units",
"displayName": "Total Units",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true,
"removed": false
},
{
"id": "Revenue",
"displayName": "Revenue",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "Notes",
"displayName": "Notes",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
},
{
"id": "Timestamp",
"displayName": "Timestamp",
"required": false,
"defaultMatch": false,
"display": true,
"type": "string",
"canBeUsedToMatch": true
}
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {}
},
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.7,
"position": [
944,
0
],
"id": "a8d2612b-af58-45d9-a032-94f7c9225225",
"name": "Append row in sheet",
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"conditions": {
"options": {
"caseSensitive": true,
"leftValue": "",
"typeValidation": "loose",
"version": 2
},
"conditions": [
{
"id": "0ece93b2-ab85-4715-9706-8e7bc62801f1",
"leftValue": "= {{$json.error}}",
"rightValue": "",
"operator": {
"type": "boolean",
"operation": "false",
"singleValue": true
}
}
],
"combinator": "and"
},
"looseTypeValidation": true,
"options": {}
},
"type": "n8n-nodes-base.if",
"typeVersion": 2.2,
"position": [
1152,
0
],
"id": "7b1f0281-c39c-4336-b289-b1715809eeff",
"name": "If"
},
{
"parameters": {
"chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
"text": "=\"\u2705 Sales logged successfully! \ud83d\udcca Summary: \u2022 Date: {{$json.date}} \u2022 Amount: ${{$json.amount}} \u2022 Product: {{$json.product_category}} \u2022 Quantity: {{$json.quantity}} View your dashboard:https://docs.google.com/spreadsheets/d/1QvcxnrLSf6jlRLOgOG7oT-CGSm_ARK1ljTgbITv3Ums/edit?usp=sharing\"",
"additionalFields": {}
},
"type": "n8n-nodes-base.telegram",
"typeVersion": 1.2,
"position": [
1360,
208
],
"id": "6fea6967-277a-4291-94b1-ac3ec33bf2c5",
"name": "Send a text message",
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
}
},
{
"parameters": {
"chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
"text": "={{ $json.message }} Please try again with the correct format: \ud83d\udccb EXAMPLES: \u2022 \"5kg=5, 10kg=10, 25kg=5, 50kg=3\" \u2022 \"Today sold 5 of 5kg and 10 of 10kg\" \u2022 \"Sold 23 sacks: 10 small, 8 medium, 5 large\" \ud83d\udca1 TIP: Make sure to include quantities for at least one sack size. Need help? Reply with /help",
"additionalFields": {}
},
"type": "n8n-nodes-base.telegram",
"typeVersion": 1.2,
"position": [
1360,
-96
],
"id": "6acce18c-8ca3-4d18-8390-c6928e8b32ad",
"name": "Send a text message1",
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
}
}
],
"connections": {
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Telegram Trigger": {
"main": [
[
{
"node": "Basic LLM Chain",
"type": "main",
"index": 0
}
]
]
},
"Basic LLM Chain": {
"main": [
[
{
"node": "Code in JavaScript",
"type": "main",
"index": 0
}
]
]
},
"Code in JavaScript": {
"main": [
[
{
"node": "Append row in sheet",
"type": "main",
"index": 0
}
]
]
},
"Append row in sheet": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"If": {
"main": [
[
{
"node": "Send a text message1",
"type": "main",
"index": 0
}
],
[
{
"node": "Send a text message",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "4dee118f-1c71-48e6-89c7-36cd94618829",
"meta": {
"templateCredsSetupCompleted": true
},
"id": "BX1sg0BYAestgrVF",
"tags": []
}
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.
googleSheetsOAuth2ApiopenAiApitelegramApi
Pro
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About this workflow
KMsRice. Uses telegramTrigger, chainLlm, lmChatOpenAi, googleSheets. Event-driven trigger; 8 nodes.
Source: https://github.com/7Aceace/kms-salesmgmt-n8n/blob/a48f12a793aed9fe90a1dbe1325458f35babcfe3/workflows/KMsRice.json — original creator credit. Request a take-down →
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