This n8n workflow automates the process of receiving chat messages to dynamically query a database, analyze the results, and generate visual charts for data visualization. It begins with a language model triggered by a chat webhook, which interprets user prompts and routes actions accordingly. The workflow includes executing SQL queries against a PostgreSQL database, retrieving database schema details, and utilizing AI to generate chart configurations based on query data. The system generates a QuickChart.io URL to visualize data in bar charts, making complex data insights accessible through automated chat interactions. Ideal for real-time data analysis, reporting, or interactive dashboards within WordPress or other platforms, this workflow enhances productivity by integrating AI-powered data querying and visualization tools.
Automated Database Query and Chart Generation Workflow
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.memoryPostgresChat, @n8n/n8n-nodes-langchain.outputParserStructured, @n8n/n8n-nodes-langchain.toolWorkflow, executeWorkflowTrigger, httpRequest, postgresTool, set, stickyNote, switch |
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