This n8n workflow creates an interactive chatbot that allows users to query a PostgreSQL database through natural language. It integrates AI language models with direct database access, enabling dynamic data retrieval and analysis based on user prompts.
The process begins with a webhook trigger that receives chat messages from users. These messages are processed by an AI agent powered by OpenAI’s GPT-4, which interprets the user’s intent and generates SQL queries or commands accordingly.
The workflow includes several critical nodes:
– The ‘Chat with Postgresql Database’ trigger captures incoming chat messages.
– The ‘AI Agent’ uses OpenAI’s language model to understand the user’s request, consult the database schema, and generate SQL queries.
– ‘Get DB Schema and Tables List’ retrieves all table schemas from the database, helping the AI to understand the database structure.
– ‘Get Table Definition’ fetches detailed information about specific tables, including columns and foreign keys.
– ‘Execute SQL Query’ runs the generated SQL commands against the database to fetch data.
– The ‘OpenAI Chat Model’ can be used to generate conversational responses based on retrieved data.
– ‘Chat History’ maintains a context window to manage ongoing conversations.
Additional sticky notes in the workflow provide setup instructions, tools used, and customization tips, making it accessible for users to deploy and adapt.
This workflow is ideal for creating a dynamic, user-friendly interface for database queries, useful for business intelligence, data dashboards, or support systems that require real-time data access through natural language interaction.
Reviews
There are no reviews yet.