This n8n workflow automates data operations in Supabase while integrating a conversational AI chatbot. It starts with triggers from a Supabase webhook, then enables real-time data manipulation by creating, deleting, searching, and updating database rows. The workflow incorporates Langchain’s language models and memory buffer to power a sophisticated chat interface, allowing users to send messages and receive AI-driven responses. Practical for chat-based customer support or dynamic data management, this setup streamlines database interactions and enhances chatbot capabilities, making data handling more efficient and conversational AI more accessible in WordPress integrations or other web applications.
Automated Data Management and Chatbot Workflow with Supabase and Langchain
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.chatTrigger, @n8n/n8n-nodes-langchain.lmChatOpenAi, @n8n/n8n-nodes-langchain.mcpClientTool, @n8n/n8n-nodes-langchain.mcpTrigger, @n8n/n8n-nodes-langchain.memoryBufferWindow, stickyNote, supabaseTool |
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