John Alejandro SIlva
Detail-oriented professional with a dual degree in Systems Engineering and Business Administration and international experience in technology and process improvement. I specialize in workflow automation with n8n, API integration, programming, and data analysis. Known for strong analytical skills and clear technical documentation.
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Templates by John Alejandro SIlva
Nutrition tracker & meal logger with Telegram, Gemini AI and Google Sheets
🤖🥗 Telegram Nutrition AI Assistant (Alternative to Cal AI App) > AI-powered nutrition assistant for Telegram — log meals, set goals, and get personalized daily reports with Google Sheets integration. 📋 Description This n8n template creates a Telegram-based Nutrition AI Assistant 🥑🔥 designed as an open-source alternative to the Cal AI mobile app. It allows users to interact with an AI agent via text, voice, or images to track meals, calculate macros, and monitor nutrition goals directly from Telegram. The system integrates Google Sheets as the database, handling both user profiles and meal logs, while leveraging Gemini AI for natural conversation, food recognition, and daily progress reports. ✨ Key Features 💬 Multi-input support: Text, voice messages (transcribed), and food images (AI analysis). 📊 Macro calculation: Automatic estimation of calories, proteins, carbs, and fats. 📝 User-friendly registration: Simple onboarding without storing personal health data (no weight/height required). 🎯 Goal tracking: Users can set and update calorie and protein targets. 📈 Daily reports: Personalized progress messages with visual progress bars. 🗂 Google Sheets integration: Profile table for user targets. Meals table for food logs. 🔄 Advanced n8n nodes: Includes use of Merge, Subworkflow, and Code nodes for data processing and report generation. 💡 Acknowledgment Inspired by the Cal AI concept 💡 — this template demonstrates how to reproduce its main functionality with n8n, Telegram, and AI agents as a flexible, open-source automation workflow. 🏷 Tags telegram ai-assistant nutrition meal-tracking google-sheets food-logging voice-transcription image-analysis daily-reports n8n-template merge-node subworkflow-node code-node telegram-trigger google-gemini 💼 Use Case Use this template if you want to: 🥗 Log meals using text, images, or voice messages. 📊 Track nutrition goals (calories, proteins) with daily progress updates. 🤖 Provide a chat-based nutrition assistant without building a full app. 🗂 Store structured nutrition data in Google Sheets for easy access and analysis. 💬 Example User Interactions 📸 User sends a photo of a meal → AI analyzes the food and logs calories/macros. 🎤 User sends a voice message → AI transcribes and logs the meal. ⌨️ User types “report” → AI returns a daily nutrition summary with progress bars. 🥅 User says “update my protein goal” → AI updates profile in Google Sheets. 🔑 Required Credentials Telegram Bot API (Bot Token) Google Sheets API credentials AI Provider API (Google Gemini or compatible LLM) ⚙️ Setup Instructions 🗂 Create two Google Sheets tables: Profile: UserID, Name, Caloriestarget, Protein_target Meals: UserID, Date, Mealdescription, Calories, Proteins, Carbs, Fats 🔌 Configure the Telegram Trigger with your bot token. 🤖 Connect your AI provider credentials (Gemini recommended). 📑 Connect Google Sheets with your credentials. ▶️ Deploy the workflow in n8n. 🎯 Start interacting with your nutrition assistant via Telegram. 📌 Extra Notes 🟩 Green section: Handles Telegram trigger and user check. 🟥 Red section: Registers new users and sets goals. 🟦 Blue section: Processes text, voice, and images. 🟨 Yellow section: Generates nutrition reports. 🟪 Purple section: Main AI agent controlling tools and logic. --- 💡 Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: 📧 Email: johnsilva11031@gmail.com 🔗 LinkedIn: John Alejandro Silva Rodríguez
By John Alejandro SIlvaProcess multiple media files in Telegram with Gemini AI & PostgreSQL database
🤖📨 Telegram AI Assistant with Multi-File Media Group Handling, Smart File Processing & PostgreSQL Integration > AI-powered Telegram bot for text, voice, video, documents & media — with database-driven grouping and Telegram-safe formatting. --- 📋 Description This n8n template creates a next-generation Telegram AI assistant 🧠💬 capable of handling text messages, media files, and documents with advanced processing, PostgreSQL integration, and AI-powered responses. It is designed to solve Telegram’s media group challenge 📦 — when multiple files are sent together, they are stored, processed, and combined into one coherent AI-generated reply. ✨ Key Features 📂 Multi-file media group management with PostgreSQL: media_group media_queue chat_histories 📑 Document parsing for CSV, HTML, ICS, JSON, ODS, PDF (with AI fallback), RTF, TXT, XML, and spreadsheets. 🎤 Voice & video transcription for AI analysis. 🖼️ Image, audio, and video description for richer AI context. 🛡️ Telegram-safe MarkdownV2 formatting with auto-splitting for messages over 4096 chars. ⚠️ Error fallback for unsupported file types. --- 💡 Acknowledgment A huge thank you to Ezema Gingsley Chibuzo 🙌 for the inspiration of the first version of this workflow: Create a Multi-Modal Telegram Support Bot with GPT-4 and Supabase RAG Your pioneering work laid the foundation for this improved, database-powered multi-modal assistant 🚀 --- 🏷 Tags telegram ai-assistant postgresql multi-file media-group file-processing voice-transcription document-parser pdf-extraction markdown-formatting n8n-template --- 💼 Use Case Use this template if you need an AI-powered Telegram bot that can: 📦 Handle multiple files sent in a single message (albums, multiple PDFs, etc.). 🧾 Extract & analyze content from many file formats. 🎙️ Transcribe voice and video messages. 🗂️ Maintain chat memory for contextual AI answers. 🛡️ Avoid Telegram formatting errors and length limit issues. This workflow automates the full chain: Receive → Process → AI Analysis → Telegram-safe Reply. --- 💬 Example User Interactions 📄 Multiple PDFs with a caption → AI extracts and summarizes all PDFs in one combined reply. 🎤 Voice message → AI transcribes and replies with a contextual answer. 📊 CSV or spreadsheet file → AI parses and summarizes the data. 🖼️ Multiple images → AI describes each image and replies in a single message. --- 🔑 Required Credentials Telegram Bot API (Bot Token) PostgreSQL (Connection credentials) AI Provider API (OpenAI, Google Gemini, or compatible LLM) --- ⚙️ Setup Instructions 🗄️ Create the PostgreSQL tables (Gray section SQL): media_group media_queue chat_histories 🔌 Configure the Telegram Trigger with your bot token. 🤖 Connect your AI provider credentials. 🗂️ Set up PostgreSQL credentials in the database nodes. ▶️ Deploy the workflow in n8n. 🎯 Start sending messages and files to your bot. --- 📌 Extra Notes ✅ Green section ensures only one trigger per media group. 📌 Yellow section guarantees captions and files are stored in the correct sequence. ✨ Purple section formats AI output to be Telegram-safe and split if needed. 🧠 AI prompt is not fixed, allowing full customization. --- 💡 Need Assistance? If you’d like help customizing or extending this workflow, feel free to reach out: 📧 Email: johnsilva11031@gmail.com 🔗 LinkedIn: John Alejandro Silva Rodríguez
By John Alejandro SIlva