Message buffering and AI response generation in Telegram

• Automate responses to multiple user messages in Telegram
• Enhance customer support interactions with cohesive AI replies
• Buffer incoming messages for better conversation context
• Utilize AI for generating responses based on user interactions

Receive messages from Telegram users Store incoming messages in a Supabase database Wait for a specified duration to capture additional messages Aggregate buffered messages into a single conversation Generate a unified response using an AI model Send the AI-generated response back to the user

1. 1
   Import the workflow template into n8n
2. 2
   Create a Supabase table named 'message_queue' with required columns
3. 3
   Configure Telegram, Supabase, OpenAI, and PostgreSQL credentials
4. 4
   Activate the workflow and test by sending multiple messages in Telegram
5. 5
   Adjust the waiting period as needed for optimal performance