Telegram Meal Logger with AI

Log meals through Telegram and get automatic nutritional analysis using AI image recognition and macro calculation.

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5 min setup
Setup
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About This Template

Log meals through Telegram and get automatic nutritional analysis using AI image recognition and macro calculation. This template is designed for teams that want a practical it operations automation with clear handoff points and strong operational reliability.

What this workflow does

Build a workflow that monitors a Telegram bot for meal photos and text, uses OpenAI to identify food and calculate nutritional information (calories, protein, carbs, fat), and stores everything in Google Sheets with daily progress reports.

Typical execution flow

  1. Trigger captures a new event from the connected source system.
  2. Validation and normalization steps ensure data quality before processing.
  3. AI or rules-based logic enriches, classifies, or transforms records.
  4. Final actions write results to tools your team already uses.
  5. Notification and logging steps provide traceability for audits and debugging.

Setup checklist

  • Connect all required app credentials and verify permissions.
  • Map required input fields before enabling production runs.
  • Configure destination resources such as sheet, table, inbox, or channel.
  • Run a test event and validate expected outputs end-to-end.
  • Enable monitoring alerts for retries, errors, and completion status.

Operational guidance

Use this template as a baseline and adapt thresholds, routing rules, and prompts to your business context. Keep secrets in your platform vault, add rate-limit controls for external APIs, and...

How This Automation Works

1

Trigger Event

The workflow starts when a specific event occurs in your connected app.

2

Process Data

puq.ai processes the incoming data and applies any filters or transformations.

3

Execute Action

The processed data triggers actions in your destination apps automatically.

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