RAG Framework 🚀

Production-ready containerized RAG (Retrieval-Augmented Generation) framework combining LangGraph multi-agent orchestration, Mem0 persistent memory, and GPTme tool execution for autonomous AI workflows.

🏗️ Architecture Overview

┌─────────────┐ ┌──────────────┐ ┌─────────────┐ │ GPTme │ │ LangGraph │ │ Mem0 │ │ :8090 │◄──►│ :8080 │◄──►│ :8000 │ │ │ │ │ │ │ │ Tool │ │ Multi-Agent │ │ Vector │ │ Execution │ │ Orchestrator │ │ Memory │ └─────────────┘ └──────────────┘ └─────────────┘

🧩 Core Components

• 🔧 GPTme - Advanced tool execution engine with shell access, file operations, and code execution
• 🤖 LangGraph - Multi-agent workflow orchestration with state management and decision routing
• 🧠 Mem0 - Persistent memory layer with vector storage and contextual retrieval
• 🐳 Docker - Containerized deployment with service mesh networking

Current Status

Workflow Overview ┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐ │ LangGraph │ │ Mem0 │ │ GPTme │ │ Orchestrator │◄──►│ Memory Layer │◄──►│ Tool Executor │ └─────────────────┘ └──────────────────┘ └─────────────────┘ │ │ │ ▼ ▼ ▼ ┌─────────────────┐ ┌──────────────────┐ ┌─────────────────┐ │ Workflow │ │ Context & │ │ Git Commands │ │ Planning │ │ History │ │ File Analysis │ └─────────────────┘ └──────────────────┘ └─────────────────┘ Component Responsibilities LangGraph (Orchestration Layer) Role: Workflow coordination and decision making

Project Analysis: Scan codebase for changes and determine commit scope Quality Gates: Verify changes meet standards before committing Approval Workflows: Human-in-the-loop for sensitive operations Error Recovery: Handle git conflicts and operational failures

Mem0 (Memory Layer) Role: Historical context and pattern recognition

Change Patterns: Remember successful commit strategies and messaging patterns Project Knowledge: Maintain understanding of project structure and goals Decision History: Track what worked and what didn't for continuous improvement Context Preservation: Maintain development narrative across sessions

GPTme (Execution Layer) Role: File system operations and git command execution

File Analysis: Read, analyze, and categorize code changes Git Operations: Execute commits, pushes, branching with safety checks Documentation Generation: Create and update README, changelogs, documentation Safety Verification: Validate operations before execution

🚀 Quick Start

Prerequisites

• Docker & Docker Compose (v3.8+)
• OpenRouter API Key (Get yours here)
• Git for version control

1️⃣ Clone & Configure

bash git clone https://github.com/Dutchthenomad/rag-framework.git cd rag-framework

Copy environment template and configure API key

cp .env.template .env

Edit .env and add your OPENROUTER_API_KEY

2️⃣ Launch Services

bash

Build and start all services

docker-compose up -d

Verify all services are healthy

docker-compose ps

3️⃣ Verify Health

bash curl http://localhost:8000/health # Mem0 curl http://localhost:8080/health # LangGraph
curl http://localhost:8090/health # GPTme

📊 Service Endpoints

Service	Port	Health Check	API Documentation
Mem0	8000	/health	API Docs
LangGraph	8080	/health	API Docs
GPTme	8090	/health	API Docs

🛠️ Development

Environment Setup

bash

Development environment with hot reload

docker-compose -f docker-compose.dev.yml up

Run tests

./scripts/testing/run-tests.sh

Check service health

./scripts/testing/health-check.sh

Project Structure

rag-framework/ ├── services/ # Containerized services │ ├── gptme/ # Tool execution service │ ├── langgraph/ # Multi-agent orchestrator
│ ├── mem0/ # Memory persistence layer │ └── shared/ # Common configurations ├── tests/ # Comprehensive test suite ├── docs/ # Architecture & API documentation ├── scripts/ # Automation utilities └── .github/ # CI/CD workflows

🧪 Testing

bash

Unit tests

pytest tests/unit/

Integration tests

pytest tests/integration/

End-to-end tests

pytest tests/integration/test_end_to_end.py

All tests with coverage

pytest --cov=services tests/

📚 Documentation

• Architecture Overview - System design and component interaction
• Development Setup - Detailed development environment configuration
• API Reference - Complete API documentation for all services
• Deployment Guide - Production deployment strategies
• Troubleshooting - Common issues and solutions

🔧 Configuration

Environment Variables

Variable	Description	Required	Default
OPENROUTER_API_KEY	OpenRouter API key for LLM access	✅	-
GPTME_WORKSPACE	GPTme workspace directory	❌	/workspace
TOOL_ALLOWLIST	Allowed GPTme tools (security)	❌	save,append,patch,ipython,shell,browser
DEBUG	Enable debug logging	❌	false

Service Configuration

Each service includes detailed configuration options:

• GPTme Config - Tool restrictions and model settings
• LangGraph Config - Agent definitions and workflows
• Mem0 Config - Vector store and embedding configuration

🤝 Contributing

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

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📊 Monitoring & Observability

• Health Checks - All services expose /health endpoints
• Logging - Structured logging with configurable levels
• Metrics - Service metrics and performance monitoring
• Tracing - Request tracing across service boundaries

🔒 Security

• API Key Management - Environment-based configuration with templates
• Tool Restrictions - Configurable GPTme tool allowlists
• Network Isolation - Services communicate via dedicated Docker network
• Dependency Scanning - Automated vulnerability detection

📈 Performance

• Containerized Deployment - Optimized Docker images with multi-stage builds
• Service Mesh - Efficient inter-service communication
• Persistent Storage - Data persistence across container restarts
• Health Monitoring - Automated health checks and restart policies

📄 License

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

🙋‍♂️ Support

• 📖 Documentation - Check our comprehensive docs
• 🐛 Issues - Report bugs via GitHub Issues
• 💬 Discussions - Join the conversation in GitHub Discussions

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