Create a dynamic Telegram bot menu system with multi-level navigation
π€ Telegram Bot with Dynamic Multi-Level Menu System What This Workflow Does Ever wanted to build a Telegram bot with professional-looking menus that actually work? This n8n workflow creates an interactive bot with dynamic inline keyboards, multi-level navigation, and smart button routing - all without writing complex code from scratch. The bot features a clean separation between your menu structure and business logic. This means you can change your menus anytime without breaking the underlying functionality. Think of it like WordPress menus but for Telegram bots - you define the navigation, and the workflow handles everything else. Your bot will respond with personalized messages, remember user context, handle button clicks smoothly (no annoying loading spinners!), and route different actions to specialized handlers. Whether users are rating your service, checking their subscription status, or navigating through settings, everything just works. π Getting Started in 3 Minutes Step 1: Get Your Bot Token Head over to Telegram and chat with @BotFather. Create a new bot (or use an existing one) and grab that token. In the workflow, find the purple "Set Bot Token" node and replace [!!! YOURBOTTOKEN_HERE !!!] with your actual token. Step 2: Activate the Magic Save the workflow, click on "Production" tab, and you'll see a webhook URL. Toggle the workflow to Active. That's it - your bot is live! Step 3: See It In Action Message your bot on Telegram. Type /start and watch your beautiful menu appear. Click around, explore the buttons - everything is already set up and working. π¨ Making It Yours Want to Add Your Own Menus? Open the workflow and look for the sticky note titled "π COMPLETE GUIDE: ADDING MENUS & ACTIONS". I've written step-by-step instructions right there in the workflow. You'll find exact examples showing how to add a contact menu, subscription status checker, or whatever you need. The beauty is in the simplicity - menus are just text and buttons. No complicated logic mixed in. Check the "π REAL EXAMPLES" sticky note for copy-paste templates you can modify. Need Custom Actions? When a button needs to actually DO something (save data, call an API, send an email), that's where handlers come in. The workflow includes 7 pre-built handlers for common tasks like ratings, language switching, and analytics. Want to add your own? The "π‘ ADDING HANDLERS" sticky note walks you through it. π‘ Why This Workflow Is Different Most Telegram bot tutorials have you mixing menu code with business logic, making changes a nightmare. This workflow separates everything cleanly. Your menus live in one place, your logic in another. It's like having a control panel for your bot. The workflow also solves a common n8n limitation - the native Telegram node doesn't support dynamic inline keyboards. Instead of giving up, this workflow uses HTTP requests directly to the Telegram API, giving you full control over every feature. π§ Pro Tips from the Trenches After building dozens of Telegram bots, here's what I've learned: Always include a "Back" button - users panic without an escape route Use emojis in your buttons - they make everything friendlier Test each menu path after changes - one typo can break navigation Keep action handlers focused - one handler, one job Hit a snag? Check the "π TROUBLESHOOTING & TIPS" sticky note in the workflow. I've documented all the common "gotchas" and their fixes. π¦ What's Included This workflow comes with everything you need: Centralized menu configuration system Smart routing that automatically detects which button was pressed 7 ready-to-use action handlers (modify or replace as needed) Parallel processing for lightning-fast responses Built-in error handling with fallback menus Comprehensive documentation right in the workflow via sticky notes π Taking It Further Once you're comfortable with the basics, this architecture scales beautifully. Connect a database to remember user preferences. Integrate with your CRM to pull customer data. Add payment processing for a shopping bot. The modular design means you can enhance one part without touching the others. The workflow sticky notes contain advanced examples for multi-language support, user authentication, and API integrations. Everything is explained in plain English with code examples you can actually use. π€ One Last Thing This workflow started as a simple dynamic menu with rating workflow and evolved into something much more powerful through community feedback. If you build something cool with it, I'd love to hear about it. And if you get stuck, remember - all the answers are in those sticky notes. I spent way too much time making them ridiculously detailed so you wouldn't have to struggle like I did. Happy bot building! π― --- Version: 1.0 - Centralized Menu System with Branching Author: Ruslan Elishev
By Ruslan ElishevFind quality YouTube videos with automated filtering & relevance scoring to Google Sheets
Who's it for Content creators, researchers, educators, and digital marketers who need to discover high-quality YouTube training videos on specific topics. Perfect for building curated learning resource lists, competitive research, or content inspiration. What it does This workflow automatically searches YouTube using multiple search queries, filters for quality content, scores videos by relevance, and exports the top results to Google Sheets. It processes hundreds of videos and delivers only the most valuable educational content ranked by custom relevance criteria. The workflow searches for videos using 10 different AI automation-related queries (easily customizable), filters out low-quality content like shorts and clickbait, then ranks results based on title keywords, view counts, and engagement metrics. How it works Multi-query search: Searches YouTube with an array of related queries to get comprehensive coverage Content filtering: Removes shorts, spam, and low-quality videos using regex patterns Quality assessment: Filters videos based on view count, likes, and publication date Relevance scoring: Assigns scores based on title keywords and engagement metrics Result ranking: Sorts videos by relevance score and limits to top 50 results Export to Sheets: Delivers clean, organized data to Google Sheets with all metadata Requirements YouTube Data API v3 credentials from Google Cloud Console Google Sheets credentials for n8n workspace A Google Sheets document to receive the results How to set up Enable YouTube Data API v3 in your Google Cloud Console Add YouTube OAuth2 credentials to your n8n workspace Add Google Sheets credentials to your n8n workspace Create a Google Sheet and update the Google Sheets node with your document ID Customize search queries in the "Set Query" node for your topic Adjust filtering criteria in the Filter nodes based on your quality requirements How to customize the workflow Search topics: Modify the query array in the "Set Query" node to research any topic: [ "Python tutorial", "JavaScript course", "React beginner guide", // Add your queries here ] Quality thresholds: Adjust minimum views, likes, and date ranges in the "Filter for Quality" node Relevance scoring: Customize keyword weightings in the "Relevance Score" node to match your priorities Result limits: Change the number of final results in the "Limit" node (default: 50) Output format: Modify the "Set Fields" node to include additional YouTube metadata like duration, thumbnails, or category information The workflow is designed to be easily adaptable for any research topic while maintaining high content quality standards.
By Zach @BrightWayAIMulti-agent LinkedIn content creation with GPT-4o, Google Sheets, and human review
Description: This is a Production-Grade Multi-Agent Content Engine designed for creators who prioritize technical authority over generic AI output. Unlike standard "one-shot" prompts, this system uses a Chain-of-Thought (CoT) architecture to separate logical blueprinting from creative writing. It features a Persistent Memory loop via Google Sheets to ensure topic variety and a dedicated Compliance Editor to enforce strict branding rules (e.g., "Sentence Case" and spaced hyphens). Built with enterprise resiliency in mind, it includes Global Error Handling and a Human-in-the-Loop Gmail approval gate with a 48-hour auto-timeout. I built this to solve the 'Technical Content' bottleneck. It ensures that my social presence reflects the same high-quality engineering standards I apply to my client's n8n workflows. Key features: Persistent Topic Memory: Automatically scans your Google Sheets history to prevent repeating technical topics. Multi-Agent Pipeline: Specialized agents for Topic Selection, Structural Architecture, Copywriting, and Brand Compliance. Style Enforcement: A final "Editor" agent that strips AI fluff and ensures a professional, human-sounding tone. Resilient Design: Features a global Error Trigger for instant failure notifications and an Approval Timeout to maintain system resources. Human-in-the-Loop: Sends a clean draft to Gmail for manual image pairing and final review before posting. How to setup Google Sheets: Prepare a sheet with columns for Topic, Status, and Difficulty. Credentials: Connect your OpenAI (or Gemini) and Gmail accounts. IDs: Replace the placeholder Sheet ID and Recipient Email address in the nodes. Error Handling: Point the Error Trigger notification to your preferred email or Slack channel.
By Ailin WernerCYBERPULSE AI RedOps: validate email security gateways generated payloads
Description: Automatically send structured benign payloads (PDF/HTML/JS markers) to test email gateways and sandbox response. AI-generated phishing-style content helps simulate real-world threats without malicious intent. Results logged in Google Sheets. Whoβs It For: Security teams validating email filters and sandboxes Red Teams doing payload simulation GRC/compliance teams testing Secure Email Gateway (SEG) controls How It Works: Loads target list from Google Sheets Crafts payload using OpenAI prompt logic Sends emails with embedded controlled markers Logs responses back to the same sheet Requirements: Google Sheet Requirements Sheet Name: PayloadValidationLog Required Columns: payload status response timestamp Gmail/SMTP or email-sending node Google Sheets credential OpenAI API Key File Templates: RedOpsPayloadValidatorLog_Template.xlsx β track targets, payload, status How to Customize: Modify the OpenAI prompt for alternate payload types Adjust fields or webhook triggers Add logging to SIEM or ticketing platforms This module is part of the CYBERPULSE AI RedOps Suite π https://cyberpulsesolutions.com Detailed README: Purpose Simulate benign payloads (e.g., links, encoded HTML) to test how your email security gateway and sandbox environment responds. How It Works Trigger Test Batch Starts manually or on schedule. Get Targets Loads email recipients from Google Sheets. Generate Payload Prepares static payload like a fake link. OpenAI Node Generates a realistic simulation email using the payload. Merge + Format Combines recipient info with OpenAI output, formats the message, and tags it as simulated. Validated Node Appends results to Google Sheets with fields like: email, payload, response, status, module, time Google Sheets Requirements Sheet Name: RedOps_Targets Columns: email, name, team, payload, status, response, module, time Security Note This workflow uses simulated payloads and never sends real malicious content. No real user data is stored or transmitted. Meant for internal Red Team and security validation use only.
By Adnan Tariq