Query PostgreSQL database with natural language using GPT-4o-mini

This Database SQL Query Agent convert natural language into sql query to get results Turn your PostgreSQL database into a conversational AI agent! Ask questions in plain English and get instant data results without writing SQL. ✨ What It Does - Natural Language Queries: "Show laptops under $500 in stock" → Automatic SQL generation - Smart Column Mapping: Understands your terms and maps them to actual database columns - Conversational Memory: Maintains context across multiple questions - Universal Compatibility: Works with any PostgreSQL table structure 🎯 Perfect For - Business analysts querying data without SQL knowledge - Customer support finding information quickly - Product managers analyzing inventory/sales data - Anyone who needs database insights fast 🚀 Quick Setup Step 1: Prerequisites - n8n instance (cloud/self-hosted) - PostgreSQL database with read access - OpenAI API key/You can use other LLM as well Step 2: Import & Configure 1. Import this workflow template into n8n 2. Add Credentials: - OpenAI API: Add your API key - PostgreSQL: Configure database connection 3. Set Table Name: Edit "Set Table Name" node → Replace "tablename" with your actual table 4. Test Connection: Ensure your database user has SELECT permissions Step 3: Deploy & Use 1. Start the workflow 2. Open the chat interface 3. Ask questions like: - "Show all active users" - "Find orders from last month over $100" - "List products with low inventory" 🔧 Configuration Details Required Settings - Table Name: Update in "Set Table Name" node - Database Schema: Default is 'public' (modify SQL if different) - Result Limit: Default 50 rows (adjustable in system prompt) Optional Customizations - Multi-table Support: Modify system prompt and add table selection logic - Custom Filters: Add business rules to restrict data access - Output Format: Customize response formatting in the agent prompt 💡 Example Queries E-commerce "Show me all electronics under $200 that are in stock" HR Database "List employees hired in 2024 with salary over 70k" Customer Data "Find VIP customers from California with recent orders" 🛡️ Security Features - Read-only Operations: Only SELECT queries allowed - SQL Injection Prevention: Parameterized queries and validation - Result Limits: Prevents overwhelming queries - Safe Schema Discovery: Uses informationschema tables 🔍 How It Works 1. Schema Discovery: Agent fetches table structure and column info 2. Query Planning: Maps natural language to database columns 3. SQL Generation: Creates safe, optimized queries 4. Result Formatting: Returns clean, user-friendly data ⚡ Quick Troubleshooting - No Results: Check table name and ensure data exists - Permission Error: Verify database user has SELECT access - Connection Failed: Confirm PostgreSQL credentials and network access - Unexpected Results: Try more specific queries with exact column names 🎨 Use Cases - Inventory Management: "Show low-stock items by category" - Sales Analysis: "Top 10 products by revenue this quarter" - Customer Support: "Find customer orders with status 'pending'" - Data Exploration: "What are the unique product categories?" 🔧 Advanced Tips - Performance: Add database indexes on frequently queried columns - Customization: Modify the system prompt for domain-specific terminology - Scaling: Use read replicas for high-query volumes - Integration: Connect to Slack/Teams for team-wide data access --- Tags: AI, PostgreSQL, Natural Language, SQL, Business Intelligence, LangChain, Database Query Difficulty: Beginner to Intermediate Setup Time: 10-15 minutes