Commit Graph

14 Commits

Author SHA1 Message Date
7eb3d11f02 auto: daily sync 2026-02-19 08:00:36 +00:00
1166741ffd fix: add try/except + debug logging around sandbox extraction 2026-02-16 17:31:33 +00:00
857c01e7ca chore: major repo cleanup - remove dead code and cruft
Remove ~24K lines of dead code for a lean rebuild foundation:

- Remove atomizer-field/ (neural field predictor experiment, concept archived in docs)
- Remove generated_extractors/, generated_hooks/ (legacy generator outputs)
- Remove optimization_validation/ (empty skeleton)
- Remove reports/ (superseded by optimization_engine/reporting/)
- Remove root-level stale files: DEVELOPMENT.md, INSTALL_INSTRUCTIONS.md,
  config.py, atomizer_paths.py, optimization_config.json, train_neural.bat,
  generate_training_data.py, run_training_fea.py, migrate_imports.py
- Update .gitignore for introspection caches and insight outputs

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-02-09 14:26:37 -05:00
4a7422c620 feat(canvas): add AtomizerSpec→ReactFlow converters 2026-01-29 02:37:32 +00:00
a3f18dc377 chore: Project cleanup and Canvas UX improvements (Phase 7-9)
## Cleanup (v0.5.0)
- Delete 102+ orphaned MCP session temp files
- Remove build artifacts (htmlcov, dist, __pycache__)
- Archive superseded plan docs (RALPH_LOOP V2/V3, CANVAS V3, etc.)
- Move debug/analysis scripts from tests/ to tools/analysis/
- Archive redundant NX journals to archive/nx_journals/
- Archive monolithic PROTOCOL.md to docs/archive/
- Update .gitignore with missing patterns
- Clean old study files (optimization_log_old.txt, run_optimization_old.py)

## Canvas UX (Phases 7-9)
- Phase 7: Resizable panels with localStorage persistence
  - Left sidebar: 200-400px, Right panel: 280-600px
  - New useResizablePanel hook and ResizeHandle component
- Phase 8: Enable all palette items
  - All 8 node types now draggable
  - Singleton logic for model/solver/algorithm/surrogate
- Phase 9: Solver configuration
  - Add SolverEngine type (nxnastran, mscnastran, python, etc.)
  - Add NastranSolutionType (SOL101-SOL200)
  - Engine/solution dropdowns in config panel
  - Python script path support

## Documentation
- Update CHANGELOG.md with recent versions
- Update docs/00_INDEX.md
- Create examples/README.md
- Add docs/plans/CANVAS_UX_IMPROVEMENTS.md
2026-01-24 15:17:34 -05:00
ea437d360e docs: Major documentation overhaul - restructure folders, update tagline, add Getting Started guide
- Restructure docs/ folder (remove numeric prefixes):
  - 04_USER_GUIDES -> guides/
  - 05_API_REFERENCE -> api/
  - 06_PHYSICS -> physics/
  - 07_DEVELOPMENT -> development/
  - 08_ARCHIVE -> archive/
  - 09_DIAGRAMS -> diagrams/

- Replace tagline 'Talk, don't click' with 'LLM-driven optimization framework' in 9 files

- Create comprehensive docs/GETTING_STARTED.md:
  - Prerequisites and quick setup
  - Project structure overview
  - First study tutorial (Claude or manual)
  - Dashboard usage guide
  - Neural acceleration introduction

- Rewrite docs/00_INDEX.md with correct paths and modern structure

- Archive obsolete files:
  - 01_PROTOCOLS.md -> archive/historical/01_PROTOCOLS_legacy.md
  - 03_GETTING_STARTED.md -> archive/historical/
  - ATOMIZER_PODCAST_BRIEFING.md -> archive/marketing/

- Update timestamps to 2026-01-20 across all key files

- Update .gitignore to exclude docs/generated/

- Version bump: ATOMIZER_CONTEXT v1.8 -> v2.0
2026-01-20 10:03:45 -05:00
62f3ab03ba chore: Add Claude session temp files to gitignore
- Ignore .claude-mcp-*.json session config files
- Ignore .claude-prompt-*.md system prompt files
- These are ephemeral files created during chat sessions

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-15 22:49:26 -05:00
73a7b9d9f1 feat: Add dashboard chat integration and MCP server
Major changes:
- Dashboard: WebSocket-based chat with session management
- Dashboard: New chat components (ChatPane, ChatInput, ModeToggle)
- Dashboard: Enhanced UI with parallel coordinates chart
- MCP Server: New atomizer-tools server for Claude integration
- Extractors: Enhanced Zernike OPD extractor
- Reports: Improved report generator

New studies (configs and scripts only):
- M1 Mirror: Cost reduction campaign studies
- Simple Beam, Simple Bracket, UAV Arm studies

Note: Large iteration data (2_iterations/, best_design_archive/)
excluded via .gitignore - kept on local Gitea only.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-13 15:53:55 -05:00
18c221a218 chore: Clean up orphaned files and update .gitignore
- Delete orphaned files: temp_compare.py, run_cleanup.py
- Delete stale cache files from archive/temp_outputs/
- Update .gitignore with .coverage.*, .obsidian/ entries

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-07 08:37:58 -05:00
Antoine
d1261d62fd refactor: Major project cleanup and reorganization
## Removed Duplicate Directories
- Deleted old `dashboard/` (replaced by atomizer-dashboard)
- Deleted old `mcp_server/` Python tools (moved model_discovery to optimization_engine)
- Deleted `tests/mcp_server/` (obsolete tests)
- Deleted `launch_dashboard.bat` (old launcher)

## Consolidated Code
- Moved `mcp_server/tools/model_discovery.py` to `optimization_engine/model_discovery/`
- Updated import in `optimization_config_builder.py`
- Deleted stub `extract_mass.py` (use extract_mass_from_bdf instead)
- Deleted unused `intelligent_setup.py` and `hybrid_study_creator.py`
- Archived `result_extractors/` to `archive/deprecated/`

## Documentation Cleanup
- Deleted deprecated `docs/06_PROTOCOLS_DETAILED/` (14 files)
- Archived dated dev docs to `docs/08_ARCHIVE/sessions/`
- Archived old plans to `docs/08_ARCHIVE/plans/`
- Updated `docs/protocols/README.md` with SYS_15

## Skills Consolidation
- Archived redundant study creation skills to `.claude/skills/archive/`
- Kept `core/study-creation-core.md` as canonical

## Housekeeping
- Updated `.gitignore` to prevent `nul` and `_dat_run*.dat`

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-12 11:24:02 -05:00
2f3afc3813 feat: Add substudy system with live history tracking and workflow fixes
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>
2025-11-16 21:29:54 -05:00
0a7cca9c6a feat: Complete Phase 2.5-2.7 - Intelligent LLM-Powered Workflow Analysis
This commit implements three major architectural improvements to transform
Atomizer from static pattern matching to intelligent AI-powered analysis.

## Phase 2.5: Intelligent Codebase-Aware Gap Detection 

Created intelligent system that understands existing capabilities before
requesting examples:

**New Files:**
- optimization_engine/codebase_analyzer.py (379 lines)
  Scans Atomizer codebase for existing FEA/CAE capabilities

- optimization_engine/workflow_decomposer.py (507 lines, v0.2.0)
  Breaks user requests into atomic workflow steps
  Complete rewrite with multi-objective, constraints, subcase targeting

- optimization_engine/capability_matcher.py (312 lines)
  Matches workflow steps to existing code implementations

- optimization_engine/targeted_research_planner.py (259 lines)
  Creates focused research plans for only missing capabilities

**Results:**
- 80-90% coverage on complex optimization requests
- 87-93% confidence in capability matching
- Fixed expression reading misclassification (geometry vs result_extraction)

## Phase 2.6: Intelligent Step Classification 

Distinguishes engineering features from simple math operations:

**New Files:**
- optimization_engine/step_classifier.py (335 lines)

**Classification Types:**
1. Engineering Features - Complex FEA/CAE needing research
2. Inline Calculations - Simple math to auto-generate
3. Post-Processing Hooks - Middleware between FEA steps

## Phase 2.7: LLM-Powered Workflow Intelligence 

Replaces static regex patterns with Claude AI analysis:

**New Files:**
- optimization_engine/llm_workflow_analyzer.py (395 lines)
  Uses Claude API for intelligent request analysis
  Supports both Claude Code (dev) and API (production) modes

- .claude/skills/analyze-workflow.md
  Skill template for LLM workflow analysis integration

**Key Breakthrough:**
- Detects ALL intermediate steps (avg, min, normalization, etc.)
- Understands engineering context (CBUSH vs CBAR, directions, metrics)
- Distinguishes OP2 extraction from part expression reading
- Expected 95%+ accuracy with full nuance detection

## Test Coverage

**New Test Files:**
- tests/test_phase_2_5_intelligent_gap_detection.py (335 lines)
- tests/test_complex_multiobj_request.py (130 lines)
- tests/test_cbush_optimization.py (130 lines)
- tests/test_cbar_genetic_algorithm.py (150 lines)
- tests/test_step_classifier.py (140 lines)
- tests/test_llm_complex_request.py (387 lines)

All tests include:
- UTF-8 encoding for Windows console
- atomizer environment (not test_env)
- Comprehensive validation checks

## Documentation

**New Documentation:**
- docs/PHASE_2_5_INTELLIGENT_GAP_DETECTION.md (254 lines)
- docs/PHASE_2_7_LLM_INTEGRATION.md (227 lines)
- docs/SESSION_SUMMARY_PHASE_2_5_TO_2_7.md (252 lines)

**Updated:**
- README.md - Added Phase 2.5-2.7 completion status
- DEVELOPMENT_ROADMAP.md - Updated phase progress

## Critical Fixes

1. **Expression Reading Misclassification** (lines cited in session summary)
   - Updated codebase_analyzer.py pattern detection
   - Fixed workflow_decomposer.py domain classification
   - Added capability_matcher.py read_expression mapping

2. **Environment Standardization**
   - All code now uses 'atomizer' conda environment
   - Removed test_env references throughout

3. **Multi-Objective Support**
   - WorkflowDecomposer v0.2.0 handles multiple objectives
   - Constraint extraction and validation
   - Subcase and direction targeting

## Architecture Evolution

**Before (Static & Dumb):**
User Request → Regex Patterns → Hardcoded Rules → Missed Steps 

**After (LLM-Powered & Intelligent):**
User Request → Claude AI Analysis → Structured JSON →
├─ Engineering (research needed)
├─ Inline (auto-generate Python)
├─ Hooks (middleware scripts)
└─ Optimization (config) 

## LLM Integration Strategy

**Development Mode (Current):**
- Use Claude Code directly for interactive analysis
- No API consumption or costs
- Perfect for iterative development

**Production Mode (Future):**
- Optional Anthropic API integration
- Falls back to heuristics if no API key
- For standalone batch processing

## Next Steps

- Phase 2.8: Inline Code Generation
- Phase 2.9: Post-Processing Hook Generation
- Phase 3: MCP Integration for automated documentation research

🚀 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-16 13:35:41 -05:00
226ede2a24 feat: Complete working optimization pipeline with stress extraction
COMPLETE PIPELINE VALIDATED:
- Stress extraction: 197.65 MPa (CTETRA elements) ✓
- Displacement extraction: 0.322 mm ✓
- Model parameter updates in .prt files ✓
- Optuna optimization with TPE sampler ✓
- Constraint handling (displacement < 1.0 mm) ✓
- Results saved to CSV/JSON ✓

Test Results (5 trials):
- All extractors working correctly
- Parameters updated successfully
- Constraints validated
- History and summary files generated

New Files:
- examples/test_stress_displacement_optimization.py
  Complete pipeline test with stress + displacement

- examples/test_displacement_optimization.py
  Displacement-only optimization test

- examples/run_optimization_real.py
  Full example with all extractors

- examples/check_op2.py
  OP2 diagnostic utility

- examples/bracket/optimization_config_stress_displacement.json
  Config: minimize stress, constrain displacement

- examples/bracket/optimization_config_displacement_only.json
  Config: minimize displacement only

Updated:
- .gitignore: Exclude NX output files and optimization results
- examples/bracket/optimization_config.json: Updated paths

Next Step: Integrate NX solver execution for real optimization
2025-11-15 11:23:57 -05:00
aa3dafbe4b Initial commit: NX OptiMaster project structure
- Set up Python package structure with pyproject.toml
- Created MCP server, optimization engine, and NX journals modules
- Added configuration templates
- Implemented pluggable result extractor architecture
- Comprehensive README with architecture overview
- Project ready for GitHub push

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-15 07:56:35 -05:00