Anto01
2f3afc3813
Major Features: - Hierarchical substudy system (like NX Solutions/Subcases) * Shared model files across all substudies * Independent configuration per substudy * Continuation support from previous substudies * Real-time incremental history updates - Live history tracking with optimization_history_incremental.json - Complete bracket_displacement_maximizing study with substudy examples Core Fixes: - Fixed expression update workflow to pass design_vars through simulation_runner * Restored working NX journal expression update mechanism * OP2 timestamp verification instead of file deletion * Resolved issue where all trials returned identical objective values - Fixed LLMOptimizationRunner to pass design variables to simulation runner - Enhanced NXSolver with timestamp-based file regeneration verification New Components: - optimization_engine/llm_optimization_runner.py - LLM-driven optimization runner - optimization_engine/optimization_setup_wizard.py - Phase 3.3 setup wizard - studies/bracket_displacement_maximizing/ - Complete substudy example * run_substudy.py - Substudy runner with continuation * run_optimization.py - Standalone optimization runner * config/substudy_template.json - Template for new substudies * substudies/coarse_exploration/ - 20-trial coarse search * substudies/fine_tuning/ - 50-trial refinement (continuation example) * SUBSTUDIES_README.md - Complete substudy documentation Technical Improvements: - Incremental history saving after each trial (optimization_history_incremental.json) - Expression update workflow: .prt update → NX journal receives values → geometry update → FEM update → solve - Trial indexing fix in substudy result saving - Updated README with substudy system documentation Testing: - Successfully ran 20-trial coarse_exploration substudy - Verified different objective values across trials (workflow fix validated) - Confirmed live history updates in real-time - Tested shared model file usage across substudies 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
71 lines
1.8 KiB
Python
71 lines
1.8 KiB
Python
"""Quick test of LLM runner initialization"""
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from optimization_engine.llm_optimization_runner import LLMOptimizationRunner
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# Example LLM workflow
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llm_workflow = {
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'engineering_features': [
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{
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'action': 'extract_displacement',
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'domain': 'result_extraction',
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'description': 'Extract displacement from OP2',
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'params': {'result_type': 'displacement'}
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}
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],
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'inline_calculations': [
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{
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'action': 'normalize',
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'params': {
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'input': 'max_displacement',
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'reference': 'max_allowed_disp',
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'value': 5.0
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},
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'code_hint': 'norm_disp = max_displacement / 5.0'
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}
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],
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'post_processing_hooks': [
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{
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'action': 'weighted_objective',
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'params': {
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'inputs': ['norm_disp'],
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'weights': [1.0],
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'objective': 'minimize'
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}
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}
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],
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'optimization': {
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'algorithm': 'TPE',
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'direction': 'minimize',
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'design_variables': [
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{
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'parameter': 'wall_thickness',
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'min': 3.0,
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'max': 8.0
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}
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]
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}
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}
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def dummy_updater(dv):
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pass
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def dummy_runner():
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return Path('tests/bracket_sim1-solution_1.op2')
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print("Initializing LLM runner...")
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runner = LLMOptimizationRunner(
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llm_workflow=llm_workflow,
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model_updater=dummy_updater,
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simulation_runner=dummy_runner,
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study_name='test'
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)
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print(f"\nSuccess!")
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print(f"Extractors: {len(runner.extractors)}")
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print(f"Inline code: {len(runner.inline_code)}")
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print(f"Hooks: {runner.hook_manager.get_summary()['enabled_hooks']}")
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