This workflow automates the process of receiving chat messages via a webhook, processing them using OpenAI’s Gemini model within LangChain, and generating intelligent responses. It starts with a trigger that listens for incoming chat messages. The message is then passed to a language model (Gemini-2.5) configured for conversation, with context management handled by a memory buffer. A custom code node initializes Langfuse for monitoring and metrics, enhancing the workflow’s observability. Finally, the AI agent synthesizes the response and sends it back, making this setup ideal for real-time chatbots, customer support automation, or conversational AI applications.

Node Count	0 – 5 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.code, @n8n/n8n-nodes-langchain.lmChatGoogleGemini, @n8n/n8n-nodes-langchain.memoryBufferWindow