Telegram Message Buffering and AI Response Workflow

This workflow is ideal for:

• Developers looking to integrate AI responses into Telegram bots.
• Businesses wanting to enhance customer support through automated responses.
• Chatbot Creators aiming to manage multiple user messages efficiently.
• Product Managers seeking to streamline communication processes within their applications.

This workflow addresses the challenge of handling multiple rapid messages from users in applications like Telegram. Instead of responding to each message individually, it buffers incoming messages and processes them as a single coherent conversation. This enhances user experience by providing a unified response rather than fragmented replies.

1. Receive Message: The workflow begins when a message is received through the Telegram bot.
2. Add to Queued Messages: The message is stored in a Supabase PostgreSQL table called message_queue along with the user's ID and message ID.
3. Wait for Additional Messages: The system waits for 10 seconds to see if any new messages arrive from the same user.
4. Get Queued Messages: After the wait period, all messages from the user are retrieved from the database.
5. Sort by Message ID: The messages are sorted to ensure they are processed in the order they were received.
6. Check Most Recent Message: The workflow checks if the last received message is the most recent one to prevent duplicates.
7. Aggregate Messages: If the most recent message is confirmed, all queued messages are combined into a single conversation.
8. AI Processing: The aggregated messages are sent to an AI model for generating a unified response.
9. Send Reply: The AI's response is sent back to the user on Telegram.
10. Delete Queued Messages: Finally, the processed messages are deleted from the queue to maintain a clean state.