Workflow Templates

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How it works This is an example of using sub-workflow nodes and a proof of concept showing that it’s possible to solve and explain recursive problems with n8n. Towers of Hanoi - Task Move a stack of n disks from rod A to rod C, using rod B as auxiliary. Only one disk can be moved at a time, and no disk may be placed on a smaller disk. Example n=4 | | | = | | === | | ===== | | ======= | | --------- --------- --------- A B C Algorithm procedure Hanoi(n, X, Y, Z): if n == 1: move disk from X to Z else: Hanoi(n-1, X, Z, Y) move disk from X to Z Hanoi(n-1, Y, X, Z) Notes This is a learning example. In a real scenario, you would probably use an iterative approach with only a single code node. When experimenting with recursion, make sure to define a termination condition first. Also, be aware of the "Restart workspace" link in the n8n Dashboard. Learn more about Recursion on Wikipedia&oldid=1301600240#Towers_of_Hanoi). Set up steps Optional: Set "numberOfDiscs" in node "Set number of discs" Execute workflow

WhatsApp Audio Transcriber Bot Overview Automatically transcribe WhatsApp audio messages to text using AI-powered speech recognition. This workflow receives audio messages via webhook, processes them through Groq's Whisper API, and replies with the transcribed text in the same conversation. Use Cases Accessibility**: Help users with hearing impairments access audio content Workplace Communication**: Quickly scan audio messages in professional settings Language Learning**: Get text versions of audio for better comprehension Meeting Notes**: Convert voice messages to searchable text format Multilingual Support**: Transcribe audio in Portuguese (configurable for other languages) How it Works Message Reception: Webhook receives WhatsApp messages in real-time Audio Detection: Filters only audio messages using Switch node Format Conversion: Converts base64 audio to MP3 file format AI Transcription: Processes audio through Groq API with Whisper Large V3 model Response Delivery: Sends transcribed text back to the original conversation Key Features ✅ Real-time Processing: Instant transcription of incoming audio messages ✅ High Accuracy: Uses Whisper Large V3 model for reliable transcription ✅ Auto-Reply: Automatically responds in the same WhatsApp conversation ✅ Message Quoting: References the original audio message in the reply ✅ Portuguese Optimized: Configured for Brazilian Portuguese transcription ✅ Self-Message Filtering: Ignores messages sent by the bot itself Prerequisites Required Services Evolution API**: WhatsApp integration service Groq API**: AI transcription service (Whisper model) n8n Instance**: Workflow automation platform API Keys & Configuration Groq API key (set as environment variable: GROQ_API_KEY) Evolution API instance properly configured Webhook URL configured in Evolution API Setup Instructions Import Workflow: Import the JSON workflow into your n8n instance Configure Environment: Set GROQ_API_KEY environment variable Setup Webhook: Configure Evolution API to send messages to the webhook endpoint Test Connection: Send a test audio message to verify the workflow Workflow Nodes Webhook**: Receives WhatsApp messages from Evolution API Edit Fields**: Extracts relevant data (number, name, message, audio) Switch**: Filters only audio messages (audioMessage type) Convert to File**: Transforms base64 audio to MP3 format HTTP Request**: Sends audio to Groq API for transcription Evolution API**: Sends transcribed text back to WhatsApp Configuration Options Groq API Settings Model**: whisper-large-v3 Language**: pt (Portuguese) Temperature**: 0 (maximum accuracy) Response Format**: json Customization Options Change language by modifying the language parameter Adjust temperature for different accuracy/creativity balance Modify response format for different output styles Response Format Mensagem transcrita automaticamente. [Transcribed text content] Technical Specifications Input**: Base64 encoded audio from WhatsApp Output**: Plain text transcription Processing Time**: Typically 2-5 seconds per audio message Supported Audio**: MP3 format (converted from WhatsApp audio) Language**: Portuguese (configurable) Troubleshooting No Response**: Check Groq API key and webhook configuration Poor Transcription**: Ensure audio quality and check language settings Error Messages**: Monitor n8n execution logs for detailed error information Version History v0.0.1**: Initial release with basic transcription functionality

This n8n workflow turns Telegram into a personal language tutor. Users can choose between different learning modes — vocabulary, grammar, quiz, or mixed lessons — simply by adding a hashtag to their message. The bot processes requests with AI/ML API and sends back structured, interactive lessons in Telegram. 🚀 Features 📩 Telegram-based input with hashtag commands 🧠 Adaptive AI responses (vocabulary, grammar, quiz) 🔤 Pronunciation support in Latin transcription 📒 Grammar explanations with examples ❓ Custom quizzes with auto-feedback 💬 Supportive learning experience with motivational messages ⏳ Typing indicator for smoother UX 🛠 Setup Guide 📲 Create Telegram Bot Go to @BotFather Use /newbot → choose a name and username Save the bot token 🔐 Set Up Credentials in n8n Telegram API: Use your bot token AI/ML API: Add your API key under AI/ML account ⚙️ Configure the Workflow Import the JSON into n8n Update credentials (Telegram + AI/ML API) Activate the workflow 💬 Start Learning In Telegram, send a message with one of the supported hashtags: #vocabulary — learn new words #grammar — study rules with examples #quiz — get exercises Or just send plain text for a free-form AI response 🔍 Node Overview Telegram Trigger** → Listens for incoming messages Show Typing Indicator** → Displays “typing…” while processing Switch Node** → Routes message by hashtag (#vocabulary, #grammar, #quiz) Prompt Builder Nodes** → Create JSON payload for AI/ML API AI/ML API Node** → Generates the structured lesson Telegram Send** → Sends the formatted response back to the user 💡 Example Flow User Input: #vocabulary кукуруза Bot Output: Кукуруза (Kukurúza) — Corn Pronunciation: koo-koo-ROO-zah Sentence: Я люблю есть кукурузу на гриле. I love eating grilled corn. 👉 Try to write your own sentence with “кукуруза”!

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