This n8n workflow automates the process of generating SQL queries based solely on a database schema, leveraging AI capabilities for efficient data retrieval. It begins by connecting to a MySQL database hosted on db4free, listing all tables, and extracting each table’s schema. The schema information is stored locally as a JSON file, improving processing speed and reducing remote database hits. When a user sends a chat message, the workflow retrieves the local schema, combines it with the user’s request, and feeds this data into an AI agent. The agent, trained to generate SQL queries without executing them, produces accurate query commands based on the schema. If a query is generated, it is executed against the database, and results are formatted for readability. The final output includes both the AI’s response and query results, making it suitable for dynamic database interactions through conversational interfaces. This workflow is ideal for developers or analysts seeking quick, AI-driven database querying without complex setup or real-time schema fetching.
AI-Powered SQL Query Generation from Database Schema
Node Count | >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, convertToFile, extractFromFile, if, manualTrigger, merge, mySql, noOp, readWriteFile, set, stickyNote |
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