This n8n workflow automates the process of transforming natural language user requests into SQL queries to retrieve data from a structured PostgreSQL database. It begins with a trigger that can be activated by a webhook or another workflow. User input, whether voice or text, is captured via Telegram, then parsed and processed by AI agents to generate precise SQL queries based on the database schema provided. The SQL query is executed against a PostgreSQL database, and the resulting data is formatted and sent back to the user through Telegram. This workflow is ideal for creating conversational interfaces that allow users to access database information seamlessly through chat interactions, making data retrieval intuitive and accessible.
Intelligent Database Query Automation
| Node Count | >20 Nodes |
|---|---|
| Nodes Used | @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmChatOpenRouter, @n8n/n8n-nodes-langchain.memoryPostgresChat, @n8n/n8n-nodes-langchain.openAi, @n8n/n8n-nodes-langchain.toolThink, @n8n/n8n-nodes-langchain.toolWorkflow, executeWorkflowTrigger, merge, postgres, set, stickyNote, switch, telegram, telegramTrigger |
Be the first to review “Intelligent Database Query Automation”
Reviews
There are no reviews yet.