Project Goals

This project automates the processing of images received via Telegram using an AI-powered Telegram chat bot integrated with image analysis and data management tools. The workflow listens for new Telegram updates, downloads files sent to the bot, analyzes images with OpenAI's vision models, processes extracted text with pattern matching, and routes data to Google Sheets for structured storage. The goal was to streamline data capture and organization from Telegram conversations, reducing manual effort and improving data accuracy.

Challenges & Problems

Managing large volumes of images and associated text data manually from Telegram can be slow and error-prone. Extracting meaningful information efficiently requires integration of multiple tools and AI-driven analysis, which can be complex without automation.

Solutions Provided

The workflow triggers on Telegram updates and downloads incoming files. It uses OpenAI models (ChatGPT, Whisper, DALL-E) for image analysis and text extraction. Extracted text is parsed to identify relevant patterns, and a router directs the processed data into Google Sheets either adding new rows or updating existing ones. This ensures well-organized and up-to-date records without manual data entry.

The Result

This workflow automates end-to-end processing of Telegram image data, enabling fast and accurate data extraction and organization. It boosts productivity by reducing manual interventions and errors when managing Telegram content. The integration of AI with communication and data tools illustrates a scalable solution for workflows involving multimedia data from messaging platforms.