Multi-Modal RAG for .NET — query databases, documents, images & audio in natural language

🚀 Quick Start

1. Install SmartRAG

dotnet add package SmartRAG

2. Setup

// For Web API applications
builder.Services.AddSmartRag(builder.Configuration, options =>
{
    options.AIProvider = AIProvider.OpenAI;
    options.StorageProvider = StorageProvider.InMemory;
});

// For Console applications
var serviceProvider = services.UseSmartRag(
    configuration,
    aiProvider: AIProvider.OpenAI,
    storageProvider: StorageProvider.InMemory
);

3. Configure databases in appsettings.json

{
  "SmartRAG": {
    "DatabaseConnections": [
      {
        "Name": "Sales",
        "ConnectionString": "Server=localhost;Database=Sales;...",
        "DatabaseType": "SqlServer"
      }
    ]
    }
}

4. Upload documents & ask questions

// Upload document
var document = await documentService.UploadDocumentAsync(
    fileStream, fileName, contentType, "user-123"
);

// Unified query across databases, documents, images, and audio
var response = await searchService.QueryIntelligenceAsync(
    "Show me all customers who made purchases over $10,000 in the last quarter, their payment history, and any complaints or feedback they provided"
);
// → AI automatically analyzes query intent and routes intelligently:
//   - High confidence + database queries → Searches databases only
//   - High confidence + document queries → Searches documents only  
//   - Medium confidence → Searches both databases and documents, merges results
// → Queries SQL Server (orders), MySQL (payments), PostgreSQL (customer data)
// → Analyzes uploaded PDF contracts, OCR-scanned invoices, and transcribed call recordings
// → Provides unified answer combining all sources

5. (Optional) Configure MCP Client & File Watcher

{
  "SmartRAG": {
    "Features": {
      "EnableMcpSearch": true,
      "EnableFileWatcher": true
    },
    "McpServers": [
      {
        "ServerId": "example-server",
        "Endpoint": "https://mcp.example.com/api",
        "TransportType": "Http"
      }
    ],
    "WatchedFolders": [
      {
        "FolderPath": "/path/to/documents",
        "AllowedExtensions": [".pdf", ".docx", ".txt"],
        "AutoUpload": true
      }
    ],
    "DefaultLanguage": "en"
  }
}

Want to test SmartRAG immediately? → Jump to Examples & Testing

🏆 Why SmartRAG?

🎯 Unified Query Intelligence - Single query searches across databases, documents, images, and audio automatically

🧠 Smart Hybrid Routing - AI analyzes query intent and automatically determines optimal search strategy

🗄️ Multi-Database RAG - Query multiple databases simultaneously with natural language

📄 Multi-Modal Intelligence - PDF, Word, Excel, Images (OCR), Audio (Speech-to-Text), and more

🔌 MCP Client Integration - Connect to external MCP servers and extend capabilities with external tools

📁 Automatic File Watching - Monitor folders and automatically index new documents without manual uploads

🧩 Modular Architecture - Strategy Pattern for SQL dialects, scoring, and file parsing

🏠 100% Local Processing - GDPR, KVKK, HIPAA compliant

🚀 Production Ready - Enterprise-grade, thread-safe, high performance

🎯 Real-World Use Cases

1. Banking - Customer Financial Profile

var answer = await searchService.QueryIntelligenceAsync(
    "Which customers have overdue payments and what's their total outstanding balance?"
);
// → Queries Customer DB, Payment DB, Account DB and combines results
// → Provides comprehensive financial risk assessment for credit decisions

2. Healthcare - Patient Care Management

var answer = await searchService.QueryIntelligenceAsync(
    "Show me all patients with diabetes who haven't had their HbA1c checked in 6 months"
);
// → Combines Patient DB, Lab Results DB, Appointment DB and identifies at-risk patients
// → Ensures preventive care compliance and reduces complications

3. Inventory - Supply Chain Optimization

var answer = await searchService.QueryIntelligenceAsync(
    "Which products are running low on stock and which suppliers can restock them fastest?"
);
// → Analyzes Inventory DB, Supplier DB, Order History DB and provides restocking recommendations
// → Prevents stockouts and optimizes supply chain efficiency

🚀 What Makes SmartRAG Special?

• Native multi-database RAG capabilities for .NET
• Automatic schema detection across different database types
• 100% local processing with Ollama and Whisper.net
• Enterprise-ready with comprehensive error handling and logging
• Cross-database queries without manual SQL writing
• Multi-modal intelligence combining documents, databases, and AI
• MCP Client integration for extending capabilities with external tools
• Automatic file watching for real-time document indexing

🧪 Examples & Testing

SmartRAG provides comprehensive example applications for different use cases:

📁 Available Examples

examples/
├── SmartRAG.API/          # Complete REST API with Swagger UI
└── SmartRAG.Demo/         # Interactive console application

🚀 Quick Test with Demo

Want to see SmartRAG in action immediately? Try our interactive console demo:

# Clone and run the demo
git clone https://github.com/byerlikaya/SmartRAG.git
cd SmartRAG/examples/SmartRAG.Demo
dotnet run

Prerequisites: You need to have databases and AI services running locally, or use Docker for easy setup.

📖 SmartRAG.Demo README - Complete demo application guide and setup instructions

🐳 Docker Setup (Recommended)

For the easiest experience with all services pre-configured:

# Start all services (SQL Server, MySQL, PostgreSQL, Ollama, Qdrant, Redis)
docker-compose up -d

# Setup AI models
docker exec -it smartrag-ollama ollama pull llama3.2
docker exec -it smartrag-ollama ollama pull nomic-embed-text

📚 Complete Docker Setup Guide - Detailed Docker configuration, troubleshooting, and management

📋 Demo Features & Steps:

🔗 Database Management:

• Step 1-2: Show connections & health check
• Step 3-5: Create test databases (SQL Server, MySQL, PostgreSQL)
• Step 6: Create SQLite test database
• Step 7: View database schemas and relationships

🤖 AI & Query Testing:

• Step 8: Query analysis - see how natural language converts to SQL
• Step 9: Automatic test queries - pre-built scenarios
• Step 10: Multi-database AI queries - ask questions across all databases

🏠 Local AI Setup:

• Step 11: Setup Ollama models for 100% local processing
• Step 12: Test vector stores (InMemory, FileSystem, Redis, SQLite, Qdrant)

📄 Document Processing:

• Step 13: Upload documents (PDF, Word, Excel, Images, Audio)
• Step 14: List and manage uploaded documents
• Step 15: Clear documents for fresh testing
• Step 16: Conversational Assistant - combine databases + documents + chat
• Step 17: MCP Integration - list tools and run MCP queries

📁 File Watcher:

• Automatic folder monitoring for new documents
• Real-time document indexing
• Duplicate detection and prevention

Perfect for: Quick evaluation, proof-of-concept, team demos, learning SmartRAG capabilities

📚 Complete Examples & Testing Guide - Step-by-step tutorials and test scenarios

🎯 Supported Data Sources

📊 Databases: SQL Server, MySQL, PostgreSQL, SQLite
📄 Documents: PDF, Word, Excel, PowerPoint, Images, Audio
🤖 AI Models: OpenAI, Anthropic, Gemini, Azure OpenAI, Ollama (local), LM Studio
🗄️ Vector Stores: Qdrant, Redis, InMemory
💬 Conversation Storage: Redis, SQLite, FileSystem, InMemory (independent from document storage)
🔌 External Integrations: MCP (Model Context Protocol) servers for extended tool capabilities
📁 File Monitoring: Automatic folder watching with real-time document indexing

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Built with ❤️ by Barış Yerlikaya

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