Food image analysis for calorie estimation with Vision AI and Telegram
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 6 nodes and runs on Telegram events (message). Along the way it connects Telegram, OpenRouter Chat Model and Gmail.
How it runs
Trigger: On Telegram events (message).
- AI Agent: runs an AI agent, with model: OpenRouter Chat Model; output parser: Structured Output Parser
- Format for Gmail (Code): runs custom JavaScript code
- Send a message (Gmail): uses Gmail
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (6)
- AI Agent
@n8n/n8n-nodes-langchain.agent - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Telegram Trigger
n8n-nodes-base.telegramTrigger - OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter - Code
n8n-nodes-base.code - Gmail
n8n-nodes-base.gmail
From the author
Who’s it for Teams building health/fitness apps, coaches running check-ins in chat, and anyone who needs quick, structured nutrition insights from food photos—without manual logging. What it does / How it works This workflow accepts a food image (URL or…