This n8n workflow leverages GPT-4 to interact with an SQLite database, specifically the Chinook sample database, to enable natural language querying. It automates the process of downloading, extracting, and loading the database locally and integrates memory management for conversational context. Through a webhook trigger, users can input queries that are combined with the database binary data, allowing GPT-4 to execute multiple SQL queries and generate insightful responses. Practical for developing conversational data analysis tools, dashboards, or chatbots that answer database-related questions dynamically.
SQLite Data Querying with GPT-4 in n8n Workflow
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.memoryBufferWindow, compression, httpRequest, manualTrigger, readWriteFile, set, stickyNote |
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