Hunyao This workflow corresponds to n8n.io template #7231 — 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": "B68FORPfxycLElJZ",
"name": "Track LLM Token Usage and Agent Observability on Google Sheets",
"tags": [],
"nodes": [
{
"id": "74b8b8f2-8152-4a8f-991b-6eb8dea2ad4a",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
0,
0
],
"parameters": {
"public": true,
"options": {},
"initialMessages": "Welcome to Troopers!\n\nSo glad you\u2019re here! \ud83d\ude0a Are you already a Troopers client, or just getting started?"
},
"typeVersion": 1.1
},
{
"id": "cbcf9a4b-1f17-4dac-8ee2-0c58766923d2",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
464,
0
],
"parameters": {
"text": "={{ $('When chat message received').item.json.chatInput }}",
"options": {
"systemMessage": "=You are a helpful assistant",
"returnIntermediateSteps": true
},
"promptType": "define"
},
"typeVersion": 2.1
},
{
"id": "482a8e1a-3d9e-419c-a671-932fc0724c1c",
"name": "Token Usage Log",
"type": "n8n-nodes-base.googleSheetsTool",
"position": [
528,
432
],
"parameters": {
"columns": {
"value": {
"date": "={{ $fromAI(\"date\") }}",
"model": "={{ $fromAI(\"model\") }}",
"llm_node": "={{ $fromAI(\"llm_node\") }}",
"client_id": "={{ $fromAI(\"client_id\") }}",
"input_cost": "={{ $fromAI(\"input_cost\") }}",
"total_cost": "={{ $fromAI(\"total_cost\") }}",
"output_cost": "={{ $fromAI(\"output_cost\") }}",
"workflow_id": "={{ $fromAI(\"workflow_id\") }}",
"execution_id": "={{ $fromAI(\"execution_id\") }}",
"input_tokens": "={{ $fromAI(\"input_tokens\") }}",
"total_tokens": "={{ $fromAI(\"total_tokens\") }}",
"output_tokens": "={{ $fromAI(\"output_tokens\") }}",
"input_token_cost ($ / million)": "={{ $fromAI(\"input_token_cost\") }}",
"output_token_cost ($ / million)": "={{ $fromAI(\"output_token_cost\") }}"
},
"schema": [
{
"id": "date",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "llm_node",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "llm_node",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "model",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "model",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "workflow_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "workflow_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "execution_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "execution_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "client_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "client_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "input_tokens",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "input_tokens",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "input_token_cost ($ / million)",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "input_token_cost ($ / million)",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "output_tokens",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "output_tokens",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "output_token_cost ($ / million)",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "output_token_cost ($ / million)",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "total_tokens",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "total_tokens",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "input_cost",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "input_cost",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "output_cost",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "output_cost",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "total_cost",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "total_cost",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "autoMapInputData",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1O4PVOD584KWLzzj8gEym95hs8z3-Y4UjImMwKfby98c/edit#gid=0",
"cachedResultName": "Token cost tracker"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": ""
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "34d054aa-9ad4-4381-8707-77903eef3b71",
"name": "Sticky Note8",
"type": "n8n-nodes-base.stickyNote",
"position": [
-832,
304
],
"parameters": {
"width": 624,
"height": 560,
"content": "## Start here: Step-by Step Youtube Tutorial :star:\nFor model-specific tweaks to the LangChain Code node, follow your provider\u2019s LangChain setup. For a walkthrough, see the attached video:\n\n[](https://youtu.be/JSulRS128MA)\n"
},
"typeVersion": 1
},
{
"id": "78fa52a2-c7c4-4c88-a357-57e6b03541e1",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-832,
-368
],
"parameters": {
"width": 624,
"height": 640,
"content": "**Start here (required settings)**\n\n* In **Set \u2022 Workflow + Client Metadata**, set `client_id`. Keep `workflow_id` and `execution_id` as is.\n* In **LangChain Chat Model + Token Callback**, set `model`, `input_token_cost`, `output_token_cost`.\n* Ensure `OPENAI_API_KEY` or your provider key is set as an environment variable.\n* In **Token Usage Log**, select your Spreadsheet and the Metrics sheet. **Replace with\u2026** Sheet ID and Sheet name.\n* In **Log \u2022 Token Metrics to Sheets (Tool)**, select your Spreadsheet and the Observability sheet. **Replace with\u2026** Sheet ID and Sheet name.\n* Add **Google Sheets OAuth2** credentials.\n\n\n**What this workflow does**\n\n* Receives a chat message and runs an AI Agent.\n* Tracks tokens and computes costs in a LangChain callback.\n* Logs token metrics to a Metrics sheet.\n* Logs input, output, and tool usage to an Observability sheet.\n* Associates each row with workflow, execution, and client IDs.\n\n\n**Customize**\n\n* Change `model` and token prices to match your provider\u2019s pricing.\n* Add more metadata fields in **Set metadata** as needed.\n* Extend the callback to include latency or provider request IDs.\n* Add a Limit or Sample node for high-volume runs.\n* Swap the Chat Trigger for Webhook Trigger if you do not need the built-in chat."
},
"typeVersion": 1
},
{
"id": "ae40d18f-8bc8-4a4f-8ddb-f31099fcd24b",
"name": "Set \u2022 Workflow + Client Metadata",
"type": "n8n-nodes-base.set",
"position": [
224,
0
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "ca1744cf-69e7-4a85-81d3-2fb2b936e496",
"name": "workflow_id",
"type": "string",
"value": "={{ $workflow.id }}"
},
{
"id": "205c7c4d-2dfa-471f-9306-33d30e16722a",
"name": "execution_id",
"type": "string",
"value": "={{ $execution.id }}"
},
{
"id": "3fa4932f-c3cc-41a8-90a4-d1b3a2d32cdd",
"name": "client_id",
"type": "string",
"value": "123"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "0b9d9c4b-7bc7-4057-a78f-bc5fc9b6f857",
"name": "LangChain Chat Model + Token Callback",
"type": "@n8n/n8n-nodes-langchain.code",
"position": [
448,
224
],
"parameters": {
"code": {
"supplyData": {
"code": "const { ChatOpenAI } = require(\"@langchain/openai\");\n\n// 1. Configure as required.\n// - costs are per million tokens and depends on the model.\nconst openAIApiKey = process.env.OPENAI_API_KEY;\nconst model = \"gpt-5-mini-2025-08-07\";\nconst input_token_cost = 0.25;\nconst output_token_cost = 2.00;\n\n// 2. Customize LLM token tracker\nconst tools = await this.getInputConnectionData('ai_tool', 0);\nconst googleSheetTool = tools[0];\n\nconst {\n workflow_id,\n execution_id,\n client_id } = $('Set metadata').first().json;\n\nconst llm = new ChatOpenAI({\n apiKey: openAIApiKey,\n model,\n callbacks: [\n {\n handleLLMEnd: async function(output,runId,parentId) {\n const generation = output.generations[0][0];\n const message = generation.message;\n const row = {\n date: (new Date()).toGMTString(),\n workflow_id,\n execution_id,\n client_id,\n model,\n input_tokens: message.usage_metadata.input_tokens,\n output_tokens: message.usage_metadata.output_tokens,\n total_tokens: message.usage_metadata.total_tokens,\n input_cost: (message.usage_metadata.input_tokens / 1_000_000) * input_token_cost,\n output_cost: (message.usage_metadata.output_tokens / 1_000_000) * output_token_cost,\n };\n row.total_cost = row.input_cost + row.output_cost;\n await googleSheetTool.func(row);\n }\n }\n ]\n});\n\nreturn llm;"
}
},
"inputs": {
"input": [
{
"type": "ai_tool",
"required": true
}
]
},
"outputs": {
"output": [
{
"type": "ai_languageModel"
}
]
}
},
"typeVersion": 1
},
{
"id": "383dc17c-d479-4f3d-965f-f708931c4865",
"name": "Branch \u2022 Tool Used?",
"type": "n8n-nodes-base.if",
"position": [
816,
0
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "9c8947e8-fa44-4e3e-b869-9284afc03a61",
"operator": {
"type": "array",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json.intermediateSteps }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "e9f7bef2-c21e-45e1-ade5-33fdcee5fc0a",
"name": "Log \u2022 Token Metrics to Sheets (Tool)",
"type": "n8n-nodes-base.googleSheets",
"position": [
1040,
0
],
"parameters": {
"columns": {
"value": {
"date": "={{ $now }}",
"input": "={{ $('When chat message received').item.json.chatInput }}",
"output": "={{ $json.output }}",
"Tool use": "={{ $json.intermediateSteps[0].action.tool }}",
"client_id": "={{ $('Set \u2022 Workflow + Client Metadata').item.json.client_id }}",
"workflow_id": "={{ $('Set \u2022 Workflow + Client Metadata').item.json.workflow_id }}",
"execution_id": "={{ $('Set \u2022 Workflow + Client Metadata').item.json.execution_id }}"
},
"schema": [
{
"id": "date",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "workflow_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "workflow_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "execution_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "execution_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "client_id",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "client_id",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "input",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "input",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Tool use",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "Tool use",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "output",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "output",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 94625050,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1O4PVOD584KWLzzj8gEym95hs8z3-Y4UjImMwKfby98c/edit#gid=94625050",
"cachedResultName": "Observability"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "1O4PVOD584KWLzzj8gEym95hs8z3-Y4UjImMwKfby98c",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/1O4PVOD584KWLzzj8gEym95hs8z3-Y4UjImMwKfby98c/edit?usp=drivesdk",
"cachedResultName": "Track LLM Tokens"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 4.6
}
],
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "67022965-a398-44c9-b241-bd09709760ec",
"connections": {
"AI Agent": {
"main": [
[
{
"node": "Branch \u2022 Tool Used?",
"type": "main",
"index": 0
}
]
]
},
"Token Usage Log": {
"ai_tool": [
[
{
"node": "LangChain Chat Model + Token Callback",
"type": "ai_tool",
"index": 0
}
]
]
},
"Branch \u2022 Tool Used?": {
"main": [
[],
[
{
"node": "Log \u2022 Token Metrics to Sheets (Tool)",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "Set \u2022 Workflow + Client Metadata",
"type": "main",
"index": 0
}
]
]
},
"Set \u2022 Workflow + Client Metadata": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"LangChain Chat Model + Token Callback": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"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.
googleSheetsOAuth2Api
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
What it does Captures token usage and cost from your AI Agent/LLM. Logs model, tokens, cost, tool use, and conversation I/O to Google Sheets for simple observability and billing.
Source: https://n8n.io/workflows/7231/ — original creator credit. Request a take-down →
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