Epic: explore-wrappers #245
Description
Epic: explore-wrappers
Overview
Strategic integration of three mature external tools (RouteLLM, Microsoft POML, LangChain Deep Agents) to replace custom orchestrator implementations, reduce bugs, and improve performance while maintaining 100% backward compatibility. Implementation follows a staged approach prioritizing immediate cost optimization (RouteLLM), template system enhancement (POML), and experimental evaluation (Deep Agents).
Architecture Decisions
Core Wrapper Pattern
- Adapter Pattern: Create compatibility layers maintaining existing orchestrator APIs
- Feature Flag Strategy: Enable/disable external tool usage without code changes
- Fallback Mechanism: Graceful degradation to existing implementations on failure
- Zero Breaking Changes: Preserve all existing pipeline YAML syntax and tool return formats
Technology Choices
- RouteLLM: Drop-in enhancement for
domain_router.pywith OpenAI-compatible interface - Microsoft POML: SDK integration into existing
template_resolver.pyandtemplate_manager.py - LangChain Deep Agents: Prototype evaluation for
control_system.pyenhancements - Configuration: Extend existing config system with feature flags and external tool settings
Design Patterns
- Wrapper Classes: Thin adapters around external tools preserving orchestrator interfaces
- Factory Pattern: Dynamic selection between original and wrapped implementations based on config
- Observer Pattern: Monitoring and metrics collection for cost/performance tracking
- Strategy Pattern: Pluggable routing and template resolution strategies
Technical Approach
Backend Services Enhancement
Model Selection (RouteLLM Integration)
- Enhance
src/orchestrator/models/domain_router.pywith intelligent routing - Add cost tracking and performance monitoring
- Implement A/B testing infrastructure for gradual rollout
- Maintain existing
ModelSelectorinterface while adding optimization
Template Processing (POML Integration)
- Extend
src/orchestrator/core/template_resolver.pywith POML SDK - Enhance
src/orchestrator/core/template_manager.pywith structured markup - Add template validation and debugging tools
- Support incremental migration from existing Jinja2 templates
Control Flow (Deep Agents Evaluation)
- Prototype enhancements to
src/orchestrator/core/control_system.py - Evaluate state management improvements for complex pipelines
- Assess parallel execution capabilities
- Document feasibility and migration complexity
Infrastructure
Configuration Management
- Add feature flags for each external tool integration
- Implement environment-specific configuration for development/production
- Support credential management for external tool APIs
- Maintain backward compatibility with existing config patterns
Monitoring & Observability
- Cost tracking dashboards for RouteLLM routing decisions
- Template validation metrics for POML usage
- Performance benchmarking across all integrations
- Error tracking and alerting for wrapper layer failures
Testing Framework
- Comprehensive test suite for all wrapper implementations
- Validation testing with all 25 example pipelines
- Performance regression testing
- A/B testing infrastructure for gradual rollouts
Implementation Strategy
Development Phases
Phase 1 (4 weeks): RouteLLM Cost Optimization
- Research and wrapper design for domain router enhancement
- Implementation with feature flags and monitoring
- Comprehensive testing and validation
- Production rollout with cost tracking
Phase 2 (4 weeks): POML Template Enhancement
- Template system analysis and incremental migration strategy
- POML SDK integration with backward compatibility
- Complex template conversion and validation tools
- Pipeline testing and quality verification
Phase 3 (2 weeks): Deep Agents Feasibility
- Isolated proof-of-concept for control flow enhancements
- State management and planning capability assessment
- Production readiness evaluation and go/no-go decision
Phase 4 (2 weeks): Final Integration & Validation
- Complete deployment of approved integrations
- Full pipeline testing across all 25 examples
- Performance and cost optimization validation
- Production monitoring and alerting setup
Risk Mitigation
- API Stability: Comprehensive integration testing with version pinning
- Performance Regression: Detailed benchmarking before/after with automatic rollback triggers
- Compatibility Issues: Extensive testing with existing pipeline configurations
- Learning Curve: Phased rollout with team training and documentation
Testing Approach
- Unit Testing: Wrapper layer functionality and fallback mechanisms
- Integration Testing: Full pipeline execution with external tool integrations
- Performance Testing: Cost optimization and speed improvements validation
- Quality Testing: Manual output inspection for all 25 example pipelines
Task Breakdown Preview
High-level task categories that will be created:
- Task 1: RouteLLM Integration - Enhance domain router with intelligent model selection and cost optimization
- Task 2: POML Integration - Enhance template resolver with structured markup capabilities and incremental migration
- Task 3: Deep Agents Evaluation - Assess feasibility of control flow enhancements and create implementation plan
- Task 4: Wrapper Architecture - Implement unified wrapper pattern with feature flags and fallback mechanisms
- Task 5: Configuration & Monitoring - Add external tool configuration management and performance tracking
- Task 6: Testing & Validation - Create comprehensive test suite and validate all 25 example pipelines
- Task 7: Documentation & Migration - Create migration guides and update API documentation
- Task 8: Production Deployment - Deploy integrations with monitoring and rollback capabilities
Dependencies
External Service Dependencies
- RouteLLM: API stability, continued development, model provider compatibility
- Microsoft POML: SDK updates, community support, template library access
- LangChain Deep Agents: Maturation from experimental status, API stability
Internal Team Dependencies
- Architecture Review: Platform team approval of integration approach
- DevOps Support: Deployment pipeline updates and monitoring setup
- QA Validation: Comprehensive testing across all example pipelines
- Documentation: User guides and migration documentation for template changes
Technical Dependencies
- Current
domain_router.pyand model selection architecture - Existing
template_resolver.pyand template processing system - Control flow and pipeline execution infrastructure
- Configuration management and credential systems
- Testing framework and CI/CD pipeline integration
Success Criteria (Technical)
Performance Benchmarks
- Cost Reduction: Achieve 40-85% model API cost reduction through RouteLLM routing
- Speed Maintenance: No performance regression in pipeline execution times
- Quality Preservation: Maintain 95% output quality scores across all integrations
- Wrapper Overhead: Keep adapter layer overhead under 5ms per tool call
Quality Gates
- Zero Breaking Changes: All existing pipeline YAML files execute identically
- Output Quality: Manual inspection confirms identical or improved outputs from 25 example pipelines
- Error Handling: Enhanced error messages and debugging capabilities
- Test Coverage: 95% test coverage for all wrapper implementations
Acceptance Criteria
- Backward Compatibility: 100% existing pipeline compatibility maintained
- Reliability: 99.9% uptime for wrapped tool functionality
- Monitoring: Real-time cost, performance, and reliability dashboards
- Rollback Capability: Instant fallback to existing implementations via feature flags
Estimated Effort
Overall Timeline
- Total Duration: 12 weeks (3 months)
- Developer Resources: 1-2 full-time equivalents
- Parallel Work Opportunity: RouteLLM and POML integration can be developed in parallel after initial design phase
Critical Path Items
- RouteLLM Integration (4 weeks) - Immediate cost optimization benefits
- POML Template Enhancement (4 weeks) - Can run in parallel with RouteLLM
- Deep Agents Evaluation (2 weeks) - Depends on stability assessment
- Final Integration (2 weeks) - Sequential validation and deployment
Resource Requirements
- Primary Development: 60-80 hours per week across 1-2 developers
- QA Testing: 20-30 hours for comprehensive pipeline validation
- DevOps Support: 10-15 hours for deployment and monitoring setup
- External Tool Budget: $1,000/month for API testing and licenses
Risk Assessment
High-Impact Risks
- External Tool Stability: Mitigation through robust fallback mechanisms
- Performance Regression: Mitigation through comprehensive benchmarking
- Compatibility Breaking: Mitigation through extensive pipeline testing
Success Probability
- RouteLLM Integration: High (90%) - mature tool with proven benefits
- POML Integration: Medium-High (75%) - stable Microsoft-backed technology
- Deep Agents Integration: Medium (50%) - depends on experimental tool maturation
This epic represents a strategic modernization of the orchestrator toolbox that reduces technical debt while significantly improving cost efficiency and reliability through proven external tool integration.
Stats
Total tasks: 8
Parallel tasks: 5 (tasks 001, 002, 003, 005, 007 can run concurrently when dependencies are met) (can be worked on simultaneously)
Sequential tasks: 3 (tasks 004, 006, 008 require specific completion order) (have dependencies)
Estimated total effort: 84 hours