Block 1 - When chat message received
- Type / Role
- @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
- Config choices
- Version 1.3
This workflow is provided as-is. Please review and test before using in production.
n8n AI Workflow Dashboard Template Overview This template is designed to collect execution data from your AI workflows and generate an interactive dashboard for easy monitoring. It's compatible ...
@n8n/n8n-nodes-langchain.chattrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.set, n8n-nodes-base.datatable, n8n-nodes-base.n8n
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Hugo.
Original n8n.io sourceThis template is designed to collect execution data from your AI workflows and generate an interactive dashboard for easy monitoring. It's compatible with any AI Agent or RAG workflow in n8n.
Messages sent to the AI agent are recorded with:
sessionIdchatInputoutputpromptTokens, completionTokens, totalTokensglobalCost and modelNameThis allows detailed tracking of AI interactions across sessions.
Two tables need to be created:
{
"id": 20,
"createdAt": "2025-10-11T12:16:47.338Z",
"updatedAt": "2025-10-11T12:16:47.338Z",
"name": "claude-4.5-sonnet",
"promptTokensPrice": 0.000003,
"completionTokensPrice": 0.000015
}
[
{
"id": 20,
"createdAt": "2025-10-11T15:28:00.358Z",
"updatedAt": "2025-10-11T15:31:28.112Z",
"sessionId": "c297cdd4-7026-43f8-b409-11eb943a2518",
"action": "sendMessage",
"output": "Hey! \nHow's it going?",
"chatInput": "yo",
"completionTokens": 6,
"promptTokens": 139,
"totalTokens": 139,
"globalCost": null,
"modelName": "gpt-4.1-mini",
"executionId": 245
}
]
These tables store conversation data and pricing info to feed the dashboard and calculations.
Follow these steps to set up and run the workflow in n8n:
Download or copy the JSON workflow and import it into n8n.
Once configured, your workflow tracks AI usage and costs in real-time, providing a live dashboard for quick insights.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 30 workflow blocks. Download the JSON for the full node graph.
| Workflow | AI model usage dashboard: Track token metrics and costs for LLM workflows |
|---|---|
| Complexity | advanced |
| Nodes | 30 |
| Categories | Engineering, AI Chatbot |
| Author | Hugo |
| Published | 11 Oct 2025 |
Use the JSON export at /data/workflows/9497/9497.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
n8n AI Workflow Dashboard Template Overview This template is designed to collect execution data from your AI workflows and generate an interactive dashboard for easy monitoring. It's compatible ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Engineering, AI Chatbot use case.