Smart Telegram Bot for FODMAP Diet Assistance
Bot Development
Project Type: AI Telegram bot
Stack: Python · aiogram · OpenAI API · Airtable · Railway · PostgreSQL
Overview
I developed a smart Telegram bot that assists users in managing their FODMAP diet, commonly recommended for individuals with IBS or digestive sensitivities. The bot serves as a real-time assistant, identifying FODMAP-safe foods, analyzing ingredients in recipes, and providing AI-generated suggestions using a structured database and large language models.
Key Features
Food checker: instantly determines if a product is FODMAP-friendly
Recipe analyzer: parses and classifies multiple ingredients
LLM integration: uses OpenAI API for personalized, natural-language responses
Airtable-powered CMS: allows easy updates to the knowledge base without redeploying
Railway-hosted: fast, cloud-based deployment with CI/CD support
PostgreSQL: supports caching, logging, and efficient data handling
Secure, modular, and extensible architecture (suitable for future SaaS development)
Outcome
The result is a lightweight, scalable, and domain-specific AI tool that combines nutrition science with conversational AI. Designed for both usability and future growth, it’s ready to evolve into a broader dietary or health assistant.
Stack: Python · aiogram · OpenAI API · Airtable · Railway · PostgreSQL
Overview
I developed a smart Telegram bot that assists users in managing their FODMAP diet, commonly recommended for individuals with IBS or digestive sensitivities. The bot serves as a real-time assistant, identifying FODMAP-safe foods, analyzing ingredients in recipes, and providing AI-generated suggestions using a structured database and large language models.
Key Features
Food checker: instantly determines if a product is FODMAP-friendly
Recipe analyzer: parses and classifies multiple ingredients
LLM integration: uses OpenAI API for personalized, natural-language responses
Airtable-powered CMS: allows easy updates to the knowledge base without redeploying
Railway-hosted: fast, cloud-based deployment with CI/CD support
PostgreSQL: supports caching, logging, and efficient data handling
Secure, modular, and extensible architecture (suitable for future SaaS development)
Outcome
The result is a lightweight, scalable, and domain-specific AI tool that combines nutrition science with conversational AI. Designed for both usability and future growth, it’s ready to evolve into a broader dietary or health assistant.