End of Turn Detection for Smoother Telegram-Gemini AI Chats

This n8n workflow implements end-of-turn detection for AI agent conversations on Telegram, using Gemini AI to predict when users finish their thoughts. Instead of fixed-time buffers, it intelligently buffers messages until the AI classifier determines the utterance is complete, then generates and sends a response.

Key components include a Telegram trigger for incoming messages, Redis for tracking user session states, and a subworkflow with a prediction loop. New messages update the buffer dynamically; once the end is detected, buffered content is concatenated and fed to Gemini for response generation. The session state is cleared post-response, ensuring efficient handling of multi-message user inputs.

Benefits include frustration-free chats by avoiding premature replies during pauses or multi-message inputs, outperforming time-based delays. It's ideal for customer support bots, virtual assistants, or casual AI companions where natural flow enhances user satisfaction.

Use cases: Deploy in Telegram-based support systems, AI therapy bots, or e-commerce chat agents. Scalable with Redis for high traffic, it saves development time on custom interruption logic and boosts engagement through human-like interactions.