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| title: AI Database Query Assistant | |
| emoji: 🤖 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: "4.0.0" | |
| app_file: server.py | |
| pinned: false | |
| # Warning: This project may not work due to Hugging Face restrictions. Please check out the GitHub repo for the latest updates. | |
| <iframe width="560" height="315" src="https://www.youtube.com/embed/0kAYAxU7YsQ?si=6ENuemAOXeLNyh-I" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe> | |
| # 🤖 AI Database Query Assistant | |
| A powerful AI-powered database query assistant that allows you to interact with your MySQL database using natural language. | |
| ## 🏷️ Tags | |
| - agent-demo-track | |
| ## ✨ Features | |
| ### Database Connection | |
| - Secure MySQL database connection with support for: | |
| - Custom host and port configuration | |
| - Username and password authentication | |
| - Special character support in passwords | |
| - Default port (3306) handling | |
| - Connection status monitoring | |
| ### AI-Powered Query Processing | |
| - Natural language to SQL conversion using Google's Gemini model | |
| - Intelligent query validation and error handling | |
| - Automatic query correction and optimization | |
| - Support for complex SQL operations including: | |
| - Joins | |
| - Aggregations | |
| - Subqueries | |
| - Complex functions | |
| ### Database Analysis | |
| - Comprehensive database structure analysis | |
| - Table schema visualization | |
| - Column information display | |
| - Primary and foreign key relationship mapping | |
| - Row count statistics | |
| ### Query Features | |
| - Natural language question processing | |
| - SQL query generation and execution | |
| - Query performance metrics: | |
| - Execution time tracking | |
| - Row count statistics | |
| - Query complexity analysis | |
| - Performance insights | |
| ### Query History | |
| - Track and store query history | |
| - View past queries with: | |
| - Timestamp | |
| - Original question | |
| - Generated SQL | |
| - Execution metrics | |
| - Complexity level | |
| - Reuse previous queries | |
| - Clear history functionality | |
| ### Security Features | |
| - Secure password handling | |
| - SQL injection prevention | |
| - Query validation | |
| - API key management: | |
| - Environment variable support | |
| - User-provided key option | |
| - Secure key storage | |
| ### User Interface | |
| - Modern Gradio-based interface | |
| - Tabbed navigation | |
| - Real-time status updates | |
| - Interactive query input | |
| - Formatted result display | |
| - Example questions for guidance | |
| ### Performance Monitoring | |
| - Query execution time tracking | |
| - Complexity analysis | |
| - Performance insights | |
| - Resource usage optimization | |
| ### Error Handling | |
| - Comprehensive error detection | |
| - User-friendly error messages | |
| - Automatic query correction | |
| - Detailed error reporting | |
| ## 🚀 Getting Started | |
| 1. Install the required dependencies | |
| 2. Set up your Google API key (for Gemini model) | |
| 3. Configure your MySQL database connection | |
| 4. Launch the application | |
| 5. Start querying your database using natural language! | |
| ## 🔧 Requirements | |
| - Python 3.x | |
| - MySQL database | |
| - Google API key for Gemini model | |
| - Required Python packages (see requirements.txt) | |
| ## 📝 License | |
| This project is licensed under the MIT License - see the LICENSE file for details. |