A comprehensive AI-powered database query assistant with advanced features for enterprise environments.

• Natural Language to SQL: Converts English questions to SQL with schema awareness
• Knowledge Base Q&A: Vector search-based document Q&A with conversational support
• Database Metadata Search: Enhanced schema exploration with BM25 reranking
• Agent Mode: Multi-server AI agent with MCP protocol support
• AI Data Mapping Analyst: Advanced data mapping and lineage analysis
• MCP Skill Library: Enterprise skill repository with semantic search
• Audit Logging: Comprehensive audit trails for compliance
• Security: RBAC, CSRF protection, rate limiting, and sensitive tool confirmation
• Admin Dashboard: User management, system monitoring, and configuration

• Backend: Python, Flask, SQLAlchemy
• AI: Azure AI Inference Service, Sentence-Transformers, OpenRouter
• Frontend: HTML, CSS, JavaScript, Bootstrap 5, jQuery
• Database: SQLite (default), ChromaDB for vector storage
• MCP Support: Model Context Protocol for stdio and HTTP servers

1. Clone Repository:

   git clone <repository-url> && cd text2sql

2. Setup Environment:

   python -m venv venv && source venv/bin/activate  # Linux/Mac
   # or venv\Scripts\activate on Windows
   pip install -r requirements.txt

3. Configuration:

   • Copy .env.example to .env
   • Set required variables: AZURE_ENDPOINT, AZURE_MODEL_NAME, GITHUB_TOKEN, DATABASE_URI, SECRET_KEY

4. Initialize Database:

   python src/utils/init_db.py

5. Start Services:

   # Start ChromaDB service
   cd chromadb_service && ./start_service.sh
   
   # Start main application
   cd .. && python app.py

6. Access Application:

   • Open http://127.0.0.1:5000
   • Default admin: admin/admin123 (change immediately!)

text2sql/
├── app.py                    # Main Flask application
├── config/                   # Configuration files
├── src/                      # Core source code
│   ├── agents/              # AI agents for sub-tasks
│   ├── models/              # Business logic
│   ├── routes/              # Flask Blueprints
│   ├── services/            # MCP servers and orchestrators
│   ├── static/              # CSS, JavaScript files
│   └── utils/               # Helper modules
├── chromadb_service/        # Vector database service
├── templates/               # HTML templates
├── logs/                    # Application logs
├── uploads/                 # Knowledge base documents
└── text2sql.db             # SQLite database

Advanced enterprise-grade system for data warehousing and data mart development:

• Intelligent column mapping with AI-powered analysis
• Graph-based join path discovery using NetworkX
• Semantic column matching across different naming conventions
• ETL transformation logic generation
• New table structure proposals

Enterprise skill repository with:

• Vector search for natural language queries
• Dynamic category organization
• Step-by-step technical guidance
• Admin interface for skill management
• HTTP/SSE interface for MCP integration

Multi-server AI agent capabilities:

• Automatic MCP server selection
• Tool execution with user confirmation
• Streaming responses and conversation context
• Integration with skill library and data mapping tools

• Metadata Search: BM25 reranking with query reformatting
• Knowledge Base: Conversational Q&A with vector similarity
• Schema Exploration: Comprehensive database metadata analysis

# AI Configuration
AZURE_ENDPOINT=your-azure-endpoint
AZURE_MODEL_NAME=your-model-name
MESSAGE_FORMAT=openai  # or llama

# Database
DATABASE_URI=sqlite:///text2sql.db

# Security
SECRET_KEY=your-secret-key
DEBUG=False

# Services
CHROMADB_SERVICE_URL=http://localhost:8001

# Conversation Limits
KNOWLEDGE_CONVERSATION_HISTORY_LIMIT=10
METADATA_CONVERSATION_HISTORY_LIMIT=10

AUTH_PROVIDER=ldap
LDAP_SERVER_URI=ldaps://ad.example.com
LDAP_USE_SSL=true
LDAP_USER_FILTER_TEMPLATE=(sAMAccountName={username})
LDAP_ALLOWED_GROUP_DN=CN=Text2SQL Users,OU=Groups,DC=example,DC=com

# Start service
cd chromadb_service && ./start_service.sh

# Health check
curl http://localhost:8001/health

# View logs
tail -f chromadb_service/service.log

# Skill Library Server
./start_mcp_skill_server.sh

# Data Mapping Server
python -m src.services.mcp_data_mapping_server --host 0.0.0.0 --port 8003

• Secure password hashing with bcrypt
• Role-Based Access Control (RBAC)
• CSRF protection and security headers
• Rate limiting on sensitive endpoints
• Audit logging for compliance
• Sensitive tool confirmation dialogs

Contributions welcome! Please follow standard fork/branch/pull request workflow.

MIT License