This comprehensive n8n workflow enhances chat interactions by intelligently predicting when a user has finished their message, thus reducing unnecessary interruptions. Using Telegram as a trigger, the workflow buffers partial messages, utilizes language models to determine message completion, and only then responds to ensure more natural and seamless conversations. Key components include session management with Redis, predictive models from Google Gemini, and a series of logical flow controls to handle new sessions, ongoing conversations, and message endings. Ideal for creating more human-like chatbot experiences, this workflow is perfect for customer support, virtual assistants, or any interactive chat system aiming for natural communication.

Node Count	>20 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.memoryRedisChat, @n8n/n8n-nodes-langchain.textClassifier, executeWorkflow, executeWorkflowTrigger, httpRequest, if, noOp, redis, set, stickyNote, telegram, telegramTrigger, wait