Transcribe WhatsApp audio messages with Whisper AI via Groq

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 1. Message Reception: Webhook receives WhatsApp messages in real-time 2. Audio Detection: Filters only audio messages using Switch node 3. Format Conversion: Converts base64 audio to MP3 file format 4. AI Transcription: Processes audio through Groq API with Whisper Large V3 model 5. 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: GROQAPIKEY) - Evolution API instance properly configured - Webhook URL configured in Evolution API Setup Instructions 1. Import Workflow: Import the JSON workflow into your n8n instance 2. Configure Environment: Set GROQAPIKEY environment variable 3. Setup Webhook: Configure Evolution API to send messages to the webhook endpoint 4. 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