Calory tracker & meal logger with Telegram, Gemini AI and data tables

This can be your Alternative to Cal AI App

Overview: A comprehensive n8n workflow demonstrating advanced AI agent orchestration, stateful conversation management, and multi-modal input processing for nutrition tracking applications.

Technical Architecture: This workflow showcases production-ready patterns for building complex conversational AI systems in n8n:

1. Multi-Agent System Design

Router Agent: Analyzes user intent and routes to specialized sub-agents Registration Agent: Handles new user onboarding with guided data collection Meal Logging Agent: Processes text, image, and voice inputs for nutrition analysis Update Agent: Manages multi-turn conversations for meal corrections Report Agent: Generates daily nutrition summaries Profile Agent: Handles user preference updates

2. Stateful Conversation Management The workflow implements a state machine using n8n Data Tables:

Tracks conversation context across messages Enables multi-step workflows (e.g., "get meal ID → ask for new description → update") Prevents context loss in long conversations Auto-resets state after task completion

3. Multi-Modal Input Processing