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## Phase 1: Monolithic File Refactoring ✅ - Refactored 8 large files (300-500 LOC) into 40+ modular components/hooks - All files now <150 LOC per file (max 125 LOC) - CanvasSettings: 343 → 7 components - SecuritySettings: 273 → 6 components - NotificationSettings: 239 → 6 components - Editor/Toolbar: 258 → 7 components - InfiniteCanvas: 239 → 10 modules - WorkflowCard: 320 → 5 components + custom hook - useProjectCanvas: 322 → 8 hooks - projectSlice: 335 → 4 Redux slices ## Phase 2: Business Logic Extraction ✅ - Extracted logic from 5 components into 8 custom hooks - register/page.tsx: 235 → 167 LOC (-29%) - login/page.tsx: 137 → 100 LOC (-27%) - MainLayout.tsx: 216 → 185 LOC (-14%) - ProjectSidebar.tsx: 200 → 200 LOC (refactored) - page.tsx (Dashboard): 197 → 171 LOC (-13%) - New hooks: useAuthForm, usePasswordValidation, useLoginLogic, useRegisterLogic, useHeaderLogic, useResponsiveSidebar, useProjectSidebarLogic, useDashboardLogic ## Phase 3: Dead Code Analysis & Implementation ✅ - Identified and documented 3 unused hooks (244 LOC) - Removed useRealtimeService from exports - Cleaned 8 commented lines in useProject.ts - Documented useExecution stub methods - Removed 3 commented dispatch calls in useCanvasKeyboard - Fixed 3 'as any' type assertions ## Phase 4: Stub Code Implementation ✅ - Fully implemented useExecution methods: execute(), stop(), getDetails(), getStats(), getHistory() - Integrated useCanvasKeyboard into InfiniteCanvas with Redux dispatch - Verified useCanvasVirtualization for 100+ items - Enhanced useRealtimeService documentation for Phase 4 WebSocket integration ## Backend Updates - Added SQLAlchemy models: Workspace, Project, ProjectCanvasItem - Added Flask API endpoints for CRUD operations - Configured multi-tenant filtering for all queries - Added database migrations for new entities ## Build Verification ✅ - TypeScript strict mode: 0 errors - Production build: ✅ Successful (161 kB First Load JS) - No breaking changes - 100% backward compatibility maintained ## Documentation Generated - 6 comprehensive guides (70+ KB total) - Test templates for all new implementations - Quick reference for all 42 hooks - Implementation checklist and deployment guide Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>
Workflow Executor Runtimes
This folder contains language-specific runtime executors for the workflow engine.
Structure
executor/
├── cpp/ # C++ runtime (high-performance)
├── python/ # Python runtime (AI/ML capabilities)
└── ts/ # TypeScript runtime + core engine
├── executor/ # DAG executor
├── registry/ # Plugin registry
├── utils/ # Priority queue, template engine
├── types.ts # Type definitions
└── index.ts # Main exports
Purpose
Each runtime provides the execution environment for plugins written in that language:
TypeScript Runtime (ts/)
- Contains the core engine (DAG executor, registry, utils)
- Default runtime for orchestration
- Direct JavaScript/TypeScript execution
- Full type safety
- Fastest startup time
Python Runtime (python/)
- Child process execution
- AI/ML library access (TensorFlow, PyTorch, transformers)
- Data science capabilities (pandas, numpy)
- NLP processing (spaCy, NLTK)
C++ Runtime (cpp/)
- Native FFI bindings
- 100-1000x faster than TypeScript
- Low memory footprint
- Ideal for bulk data processing
How It Works
┌─────────────────────────────────────────┐
│ DAGExecutor (TypeScript Core) │
│ - Orchestrates workflow execution │
│ - Resolves dependencies │
│ - Manages execution state │
└─────────────────┬───────────────────────┘
│
┌─────────┼─────────┐
│ │ │
↓ ↓ ↓
┌────────┬────────┬────────┐
│ TS │ C++ │ Python │
│Runtime │Runtime │Runtime │
└────────┴────────┴────────┘
│ │ │
↓ ↓ ↓
┌────────┬────────┬────────┐
│Direct │Native │Child │
│Import │FFI │Process │
└────────┴────────┴────────┘
Adding a New Runtime
- Create folder:
executor/{language}/ - Implement
PluginLoaderinterface - Register loader in
ts/registry/node-executor-registry.ts - Add plugins to
plugins/{language}/