Artificial Intelligence tools and workflows
Create a WhatsApp-based AI chatbot using document retrieval with Supabase, OpenAI embeddings for semantic search, and Gemini 2.5 Flash for generating responses.
## This Database SQL Query Agent converts natural language into SQL queries 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 `table_name` 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 information_schema 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
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