This workflow creates an intelligent chatbot using n8n that engages in conversations via a webhook trigger, leverages OpenAI’s language model for responses, maintains chat history with a memory buffer, integrates with an Airtable database for data storage, and incorporates language model interactions through Langchain nodes. It is ideal for building conversational agents that remember past interactions and store data systematically. The workflow begins with a webhook trigger to start conversations, uses an AI agent to process input, retains chat history in a buffer, interacts with OpenAI’s language model for natural responses, and then optionally saves data to Airtable. This setup is useful for customer support bots, automated assistants, or interactive FAQ systems.

Node Count	6 – 10 Nodes
Nodes Used	@n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.memoryBufferWindow, airtableTool, stickyNote