Welcome to RAG Modulo¶

🎯 What is RAG Modulo?¶

RAG Modulo is a production-ready Retrieval-Augmented Generation platform that provides enterprise-grade document processing, intelligent search, and AI-powered question answering. Built with modern technologies and designed for scalability, it supports multiple vector databases, LLM providers, and document formats.

✨ Key Features¶

🚀 Quick Start¶

Get up and running with RAG Modulo in minutes:

# Clone the repository
git clone https://github.com/manavgup/rag-modulo.git
cd rag-modulo

# Set up environment
cp env.example .env
# Edit .env with your API keys

# Start with pre-built images
make run-ghcr

# Initialize development environment
make dev-init

# Build and start development environment
make dev-build
make dev-up

# Validate everything is working
make dev-validate

🌐 Access Points¶

📊 Current Status¶

🏗️ Architecture Overview¶

RAG Modulo follows a modern, service-based architecture with clear separation of concerns:

graph TB
    subgraph "Frontend Layer"
        UI[React Web UI]
        CLI[Command Line Interface]
    end

    subgraph "API Layer"
        API[FastAPI Backend]
        AUTH[OIDC Authentication]
    end

    subgraph "Service Layer"
        SEARCH[Search Service]
        CONV[Conversation Service]
        TOKEN[Token Tracking]
        COT[Chain of Thought]
    end

    subgraph "Data Layer"
        VDB[(Vector Database)]
        PG[(PostgreSQL)]
        MINIO[(MinIO Storage)]
    end

    subgraph "External Services"
        LLM[LLM Providers]
        EMB[Embedding Models]
    end

    UI --> API
    CLI --> API
    API --> SEARCH
    API --> CONV
    API --> TOKEN
    API --> COT
    SEARCH --> VDB
    SEARCH --> PG
    CONV --> LLM
    TOKEN --> PG
    COT --> LLM
    API --> MINIO

🧪 Testing & Quality¶

Test Results¶

Quick Commands¶

# Run all tests
make test-all

# Quick quality checks
make quick-check

# Code quality
make lint

# Security scanning
make security-check

🛠️ Development Workflow¶

Development Commands¶

Benefits¶

• ✅ Local builds by default - No more remote image confusion
• ✅ Automatic environment setup - Development variables configured
• ✅ Fast iteration - Changes visible immediately
• ✅ Health validation - Know when everything is working
• ✅ Consistent workflow - Same setup for all developers

📚 Documentation Structure¶

🚀 Getting Started¶

• Quick Start - Get up and running quickly
• Installation - Detailed installation guide
• Configuration - Environment setup and configuration
• First Steps - Your first RAG query

🛠️ Development¶

• Development Workflow - Development best practices
• Environment Setup - Local development setup
• GitHub Codespaces - Cloud development
• Contributing - How to contribute

🧪 Testing¶

• Test Strategy - Testing approach and philosophy
• Running Tests - How to run tests
• Test Categories - Understanding test types

🚀 Deployment¶

• Deployment Guide - Complete deployment guide
• IBM Cloud Code Engine - Recommended cloud deployment
• Production Deployment - Production setup
• Cloud Deployment - Cloud deployment options
• Kubernetes - K8s deployment
• Monitoring - Production monitoring

🖥️ CLI¶

• CLI Overview - Command-line interface
• Commands - Available commands
• Examples - CLI usage examples

📚 API Reference¶

• API Overview - API documentation
• Endpoints - Available endpoints
• Schemas - Data schemas
• Examples - API usage examples

🏗️ Architecture¶

• Architecture Overview - System architecture
• Components - System components
• Data Flow - Data flow diagrams
• Security - Security considerations

🧠 Features¶

• Features Overview - All features
• Chain of Thought - Reasoning capabilities
• Token Tracking - Usage monitoring
• Search & Retrieval - Search capabilities

🤝 Contributing¶

We welcome contributions! Please see our Contributing Guide for details.

Quick Contribution¶

1. Fork and Clone the repository
2. Create Feature Branch from main
3. Make Changes following our guidelines
4. Run Tests and ensure they pass
5. Submit Pull Request with clear description

📈 Roadmap¶

✅ Phase 1: Foundation (Completed)¶

• Comprehensive test infrastructure (847 tests passing)
• Core services operational
• Development workflow streamlined
• CI/CD pipeline automated

🔄 Phase 2: Optimization (Current)¶

• Fix remaining 71 test failures
• Performance optimization
• Code quality enhancement
• Documentation improvements

🚀 Phase 3: Production (Next)¶

• Production deployment guides
• Monitoring and observability
• Security hardening
• Performance tuning

🔮 Phase 4: Advanced Features (Future)¶

• Agentic AI enhancement
• Advanced reasoning capabilities
• Multi-modal support
• Enterprise features

🆘 Need Help?¶

Getting Support¶

1. 📚 Documentation: Check our comprehensive guides
2. 🐛 Issues: Report bugs
3. 💬 Discussions: Ask questions
4. 🔧 Troubleshooting: Common issues

📄 License¶

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