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38abb0d8d2
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feat: Complete Phase 3 - pyNastran Documentation Integration
Phase 3 implements automated OP2 extraction code generation using
pyNastran documentation research. This completes the zero-manual-coding
pipeline for FEA optimization workflows.
Key Features:
- PyNastranResearchAgent for automated OP2 code generation
- Documentation research via WebFetch integration
- 3 core extraction patterns (displacement, stress, force)
- Knowledge base architecture for learned patterns
- Successfully tested on real OP2 files
Phase 2.9 Integration:
- Updated HookGenerator with lifecycle hook generation
- Added POST_CALCULATION hook point to hooks.py
- Created post_calculation/ plugin directory
- Generated hooks integrate seamlessly with HookManager
New Files:
- optimization_engine/pynastran_research_agent.py (600+ lines)
- optimization_engine/hook_generator.py (800+ lines)
- optimization_engine/inline_code_generator.py
- optimization_engine/plugins/post_calculation/
- tests/test_lifecycle_hook_integration.py
- docs/SESSION_SUMMARY_PHASE_3.md
- docs/SESSION_SUMMARY_PHASE_2_9.md
- docs/SESSION_SUMMARY_PHASE_2_8.md
- docs/HOOK_ARCHITECTURE.md
Modified Files:
- README.md - Added Phase 3 completion status
- optimization_engine/plugins/hooks.py - Added POST_CALCULATION hook
Test Results:
- Phase 3 research agent: PASSED
- Real OP2 extraction: PASSED (max_disp=0.362mm)
- Lifecycle hook integration: PASSED
Generated with Claude Code
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-11-16 16:33:48 -05:00 |
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a24e3f750c
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feat: Implement Phase 1 - Plugin & Hook System
Core plugin architecture for LLM-driven optimization:
New Features:
- Hook system with 6 lifecycle points (pre_mesh, post_mesh, pre_solve, post_solve, post_extraction, custom_objectives)
- HookManager for centralized registration and execution
- Code validation with AST-based safety checks
- Feature registry (JSON) for LLM capability discovery
- Example plugin: log_trial_start
- 23 comprehensive tests (all passing)
Integration:
- OptimizationRunner now loads plugins automatically
- Hooks execute at 5 points in optimization loop
- Custom objectives can override total_objective via hooks
Safety:
- Module whitelist (numpy, scipy, pandas, optuna, pyNastran)
- Dangerous operation blocking (eval, exec, os.system, subprocess)
- Optional file operation permission flag
Files Added:
- optimization_engine/plugins/__init__.py
- optimization_engine/plugins/hooks.py
- optimization_engine/plugins/hook_manager.py
- optimization_engine/plugins/validators.py
- optimization_engine/feature_registry.json
- optimization_engine/plugins/pre_solve/log_trial_start.py
- tests/test_plugin_system.py (23 tests)
Files Modified:
- optimization_engine/runner.py (added hook integration)
Ready for Phase 2: LLM interface layer
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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2025-11-15 14:46:49 -05:00 |
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