dbadeedsai

- AI-Powered Database Assistant: Natural language queries to databases using LLMs
- Multi-Database Support: Oracle and PostgreSQL
- Web Interface: Modern Flask web app with responsive UI
- User Management: Role-based access control
- Connection Management: Secure database connection handling
- AI Agents: Specialized agents for performance monitoring and troubleshooting
- API Endpoints: RESTful API for integrations
- Docker Support: Containerized deployment

- Python 3.8+
- Oracle Instant Client (for Oracle support)
- PostgreSQL client libraries

git clone https://github.com/yourusername/dbadeedsai.git cd dbadeedsai

FLASK_ENV=development SECRET_KEY=your-secret-key OPENAI_API_KEY=sk-...

Visithttp://localhost:5000to access the web interface.

- FLASK_ENV: Set todevelopmentorproduction
- SECRET_KEY: Flask secret key for sessions
- OPENAI_API_KEY: OpenAI API key for AI features
- ANTHROPIC_API_KEY: Anthropic Claude API key (optional)
- GOOGLE_API_KEY: Google AI API key (optional)
- GROQ_API_KEY: Groq API key (optional)

Add database connections indata/db_connections.json:

{ "oracle_1": { "name": "My Oracle DB", "db_type": "oracle", "connection_string": "user/password@host:1521/service", "is_active": true, "owner": "admin" } }

- Dashboard: Overview of connections and recent activity
- AI Assistant: Chat with AI about your databases
- Ask DBA: Natural language database queries
- Connections: Manage database connections
- Users: User management (admin only)

The application provides REST API endpoints documented at/api/docs.

├── app/ # Flask application │ ├── api/ # API blueprints │ ├── templates/ # Jinja2 templates │ └── static/ # CSS/JS assets ├── data/ # Configuration and data files ├── sql/ # SQL scripts for Oracle/PostgreSQL ├── requirements.txt # Python dependencies └── wsgi.py # Application entry point

Contributions, issues, and feature requests are welcome!

📝 License This project is licensed under the MIT License - see the LICENSE file for details. Copyright (c) 2026 sandeep reddy narani

- Built with Flask, SQLAlchemy, and various AI libraries
- Inspired by database administration tools and AI assistants

Note: This tool is designed for experienced database administrators and should be used with appropriate caution in production environments. Always verify AI-generated queries before execution on critical systems.

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