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 [!!! YOUR_BOT_TOKEN_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
n8n Dynamic Telegram Bot Menu System with Multi-Level Navigation
This n8n workflow enables you to create a sophisticated, dynamic menu system for a Telegram bot, complete with multi-level navigation capabilities. It listens for incoming messages, processes user input, and dynamically generates appropriate responses and menu options.
What it does
This workflow automates the following steps:
- Listens for Telegram Messages: Initiates the workflow upon receiving any message from a Telegram user via a configured Telegram Bot.
- Processes Incoming Data: Uses a
Functionnode to interpret the incoming Telegram message, likely extracting the user's input and chat ID. - Routes Based on Input: Employs a
Switchnode to direct the workflow based on the processed user input, allowing for different menu paths or actions. - Conditional Logic: Utilizes an
Ifnode to implement binary conditional logic, further refining the flow based on specific criteria derived from the user's interaction. - Prepares Response Data: A
Setnode is used to define or modify data that will be used to construct the Telegram bot's response, such as menu text or callback data. - Merges Data Streams: A
Mergenode combines different data paths back into a single stream, ensuring all necessary information is available before sending a response. - Sends HTTP Requests: An
HTTP Requestnode is used to interact with the Telegram Bot API, sending messages, updating menus, or performing other bot actions. - Provides Documentation: Includes a
Sticky Notefor in-workflow documentation, likely explaining specific parts of the logic or configuration.
Prerequisites/Requirements
- n8n Instance: A running instance of n8n.
- Telegram Bot: A Telegram bot created via BotFather.
- Telegram Bot Token: The API token for your Telegram bot to configure the
Telegram TriggerandHTTP Requestnodes.
Setup/Usage
- Import the workflow: Download the JSON file and import it into your n8n instance.
- Configure Telegram Trigger:
- Click on the "Telegram Trigger" node.
- Select or create a new Telegram API credential using your bot's API token.
- Ensure the "Updates" are configured to listen for relevant messages (e.g.,
message,callback_query).
- Configure HTTP Request Node:
- The "HTTP Request" node will likely need to be configured to send requests to the Telegram Bot API. This usually involves setting the URL to
https://api.telegram.org/botYOUR_BOT_TOKEN/sendMessage(or other API methods) and including the chat ID and message payload. - Replace
YOUR_BOT_TOKENwith your actual Telegram bot token.
- The "HTTP Request" node will likely need to be configured to send requests to the Telegram Bot API. This usually involves setting the URL to
- Customize Logic:
- Function (Code) Node: Review and customize the JavaScript code within the "Function" node to parse incoming messages and determine the bot's state or desired action. This is crucial for handling menu navigation logic.
- Switch and If Nodes: Adjust the conditions in the "Switch" and "If" nodes to match your desired menu structure and user input handling.
- Set (Edit Fields) Node: Modify the "Edit Fields" node to construct the appropriate response messages and keyboard markups for your dynamic menus.
- Activate the workflow: Once configured, activate the workflow to start your Telegram bot's dynamic menu system.
This workflow provides a robust foundation for building interactive Telegram bots with complex, multi-level menu navigation. By customizing the logic in the Function, Switch, If, and Set nodes, you can tailor the bot's behavior to your specific needs.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitorβs webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger β Manually start the workflow or schedule it to run periodically. Input Setup β Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) β Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring β Clean and convert GPT output into JSON format. Data Storage (Google Sheets) β Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the βSet Input Fieldsβ node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors β Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection β Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report β Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization β Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs β Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting Itβs a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chatβturn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. π What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing π§ Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation π Required Credentials OpenAI API Setup Go to platform.openai.com β API keys (sidebar) Click "Create new secret key" β Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai β Dashboard β API Keys Generate a new API key β Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) βοΈ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowβchat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" π― Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration β οΈ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
Automate invoice processing with OCR, GPT-4 & Salesforce opportunity creation
PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive β Download PDF β OCR text β AI normalize to JSON β Upsert Buyer (Account) β Create Opportunity β Map Products β Create OLI via Composite API β Archive to OneDrive. --- Node by node (what it does & key setup) 1) Google Drive Trigger Purpose: Fire when a new file appears in a specific Google Drive folder. Key settings: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output: Metadata { id, name, ... } for the new file. --- 2) Download File From Google Purpose: Get the file binary for processing and archiving. Key settings: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output: Binary (default key: data) and original metadata. --- 3) Extract from File Purpose: Extract text from PDF (OCR as needed) for AI parsing. Key settings: Operation: pdf OCR: enable for scanned PDFs (in options) Output: JSON with OCR text at {{ $json.text }}. --- 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into strict normalized JSON array (invoice schema). Key settings: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content β the parsed JSON (ensure itβs an array). --- 5) Create or update an account (Salesforce) Purpose: Upsert Buyer as Account using an external ID. Key settings: Resource: account Operation: upsert External Id Field: taxid_c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream Opportunity. --- 6) Create an opportunity (Salesforce) Purpose: Create Opportunity linked to the Buyer (Account). Key settings: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output: Opportunity Id for OLI creation. --- 7) Build SOQL (Code / JS) Purpose: Collect unique product codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output: { soql, codes } --- 8) Query PricebookEntries (Salesforce) Purpose: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output: Items with Id, Product2.ProductCode (used for mapping). --- 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id β build OpportunityLineItem payloads. Inputs: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes: Converts discount_total β per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. --- 10) Create Opportunity Line Items (HTTP Request) Purpose: Bulk create OLIs via Salesforce Composite API. Key settings: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output: Composite API results (per-record statuses). --- 11) Update File to One Drive Purpose: Archive the original PDF in OneDrive. Key settings: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output: Uploaded file metadata. --- Data flow (wiring) Google Drive Trigger β Download File From Google Download File From Google β Extract from File β Update File to One Drive Extract from File β Message a model Message a model β Create or update an account Create or update an account β Create an opportunity Create an opportunity β Build SOQL Build SOQL β Query PricebookEntries Query PricebookEntries β Code in JavaScript Code in JavaScript β Create Opportunity Line Items --- Quick setup checklist π Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. π IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) π§ AI Prompt: Use the strict system prompt; jsonOutput = true. π§Ύ Field mappings: Buyer tax id/name β Account upsert fields Invoice code/date/amount β Opportunity fields Product name must equal your Product2.ProductCode in SF. β Test: Drop a sample PDF β verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive --- Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep βReturn only a JSON arrayβ as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields donβt support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your orgβs domain or use the Salesforce nodeβs Bulk Upsert for simplicity.