🗺️ Project Roadmap¶

This document outlines the development roadmap for RAG Modulo, including completed features, current work, and future plans.

📊 Current Status¶

✅ Phase 1: Foundation & Testing (Completed)¶

Timeline: Q3-Q4 2024 Status: ✅ Complete

Achievements¶

• 🏗️ Infrastructure: Complete Docker-based development environment
• 🧪 Testing: 847 tests passing (92% success rate)
• 🚀 Core Services: Search, conversation, and token tracking operational
• 🔧 Development Workflow: Streamlined Docker-based development
• 📚 Documentation: Comprehensive documentation across all components
• 🔄 CI/CD Pipeline: Automated builds, testing, and deployment

Key Deliverables¶

• Test Infrastructure: Comprehensive test suite with 847 passing tests
• Core Services: Search, conversation, and token tracking services
• Development Workflow: make dev-* commands for streamlined development
• Docker Integration: Complete containerization with Docker Compose
• CI/CD Pipeline: GitHub Actions with automated builds and testing
• Documentation: MkDocs-based documentation with comprehensive guides

Metrics¶

• Test Coverage: 50% overall coverage with detailed reporting
• Build Time: < 5 minutes for full build
• Development Setup: < 10 minutes from clone to running
• Documentation: 90% complete with interactive examples

🔄 Phase 2: Test Optimization & Bug Fixes (Current)¶

Timeline: Q4 2024 - Q1 2025 Status: 🔄 In Progress (75% complete)

Current Focus¶

Priority: Fix remaining test failures and optimize performance

In Progress¶

1. 🧪 Test Fixes (75% complete)
2. Reduced failing tests from 200+ to 71
3. Fixed atomic and unit test infrastructure
4. Resolve remaining 71 failing tests
5. Fix API endpoint integration issues
6. Resolve CLI testing environment problems

7. Optimize E2E test reliability

8. ⚡ Performance Optimization (60% complete)

9. Improved test execution speed
10. Optimize database queries
11. Enhance memory usage
12. Streamline API responses

13. Implement caching strategies

14. 🔧 Code Quality Enhancement (70% complete)

15. Implemented comprehensive linting
16. Increase test coverage to 80%
17. Improve error handling
18. Enhance logging and monitoring
19. Refactor complex components

Upcoming Milestones¶

• Q4 2024: Complete test fixes and achieve 95% test success rate
• Q1 2025: Performance optimization and 80% code coverage
• Q1 2025: Code quality improvements and documentation updates

🚀 Phase 3: Production Readiness (Next)¶

Timeline: Q1-Q2 2025 Status: 📋 Planned

Objectives¶

Target: Production-ready system with full functionality and monitoring

Planned Features¶

1. 🚀 Production Deployment
2. Production deployment guides
3. Kubernetes manifests and Helm charts
4. Cloud deployment templates (AWS, Azure, GCP)
5. Load balancing and auto-scaling

6. SSL/TLS configuration

7. 📊 Monitoring & Observability

8. Comprehensive monitoring dashboard
9. Metrics collection and alerting
10. Log aggregation and analysis
11. Performance monitoring

12. Health checks and status pages

13. 🔒 Security Hardening

14. Security audit and penetration testing
15. Data encryption at rest and in transit
16. Role-based access control (RBAC)
17. API rate limiting and throttling

18. Audit logging and compliance

19. ⚡ Performance Tuning

20. Database optimization and indexing
21. Caching strategies implementation
22. Query optimization
23. Resource usage optimization
24. Load testing and capacity planning

Success Metrics¶

• Uptime: 99.9% availability
• Performance: < 2s response time for 95% of requests
• Scalability: Support for 1000+ concurrent users
• Security: Pass security audit with no critical issues

🔮 Phase 4: Advanced Features (Future)¶

Timeline: Q2-Q4 2025 Status: 💭 Future

Vision¶

Transform RAG Modulo into a comprehensive AI platform with advanced capabilities

Planned Features¶

1. 🤖 Agentic AI Enhancement
2. Autonomous agent orchestration
3. Multi-agent collaboration
4. Workflow automation
5. Decision-making capabilities

6. Self-improving systems

7. 🧠 Advanced Reasoning

8. Enhanced chain of thought capabilities
9. Multi-step problem solving
10. Logical reasoning and inference
11. Causal reasoning

12. Uncertainty quantification

13. 🎨 Multi-Modal Support

14. Image processing and analysis
15. Video content understanding
16. Audio transcription and analysis
17. Multi-modal document processing

18. Cross-modal search capabilities

19. 🏢 Enterprise Features

20. Advanced security and compliance
21. Multi-tenancy support
22. Enterprise SSO integration
23. Advanced analytics and reporting
24. Custom model fine-tuning

Innovation Areas¶

• 🔬 Research Integration: Academic research and cutting-edge AI
• 🌐 Federated Learning: Distributed model training
• 🔗 Knowledge Graphs: Advanced knowledge representation
• 🎯 Personalization: User-specific model adaptation
• 🌍 Global Scale: Multi-region deployment and data sovereignty

📈 Success Metrics¶

Technical Metrics¶

User Experience Metrics¶

🎯 Key Focus Areas¶

1. Developer Experience¶

• Simplified Setup: One-command installation and setup
• Comprehensive Documentation: Interactive tutorials and examples
• Development Tools: Enhanced debugging and testing tools
• Community Support: Active community and support channels

2. Performance & Scalability¶

• Optimized Performance: Sub-second response times
• Horizontal Scaling: Support for thousands of concurrent users
• Resource Efficiency: Minimal resource usage and cost
• Global Distribution: Multi-region deployment capabilities

3. AI & Machine Learning¶

• Advanced Reasoning: Sophisticated problem-solving capabilities
• Multi-Modal Processing: Support for various content types
• Continuous Learning: Self-improving and adaptive systems
• Research Integration: Cutting-edge AI research implementation

4. Enterprise Readiness¶

• Security & Compliance: Enterprise-grade security features
• Integration: Seamless integration with existing systems
• Support: Professional support and consulting services
• Customization: Flexible configuration and customization options

🤝 Community Involvement¶

How to Contribute¶

1. 🐛 Bug Reports: Report issues and bugs
2. 💡 Feature Requests: Suggest new features and improvements
3. 📚 Documentation: Help improve documentation
4. 🧪 Testing: Contribute to testing and quality assurance
5. 🔧 Code: Contribute code and pull requests

Recognition¶

• Contributors: All contributors recognized in project
• Maintainers: Active contributors can become maintainers
• Advisory Board: Community leaders form advisory board
• Sponsorship: Corporate sponsorship opportunities

📅 Timeline Summary¶

💡 Feedback & Suggestions¶

We welcome feedback and suggestions for the roadmap:

• 📧 Email: team@ragmodulo.com
• 🐛 Issues: GitHub Issues
• 💬 Discussions: GitHub Discussions
• 📋 Roadmap: Project Roadmap