diff --git a/PROJECT_SUMMARY.md b/PROJECT_SUMMARY.md new file mode 100644 index 00000000..efcb3b4a --- /dev/null +++ b/PROJECT_SUMMARY.md @@ -0,0 +1,474 @@ +# Atomizer - Project Summary + +**Last Updated**: 2025-11-15 +**Repository**: https://github.com/Anto01/Atomizer (Private) +**Branch**: main (5 commits) + +--- + +## 🎯 Project Vision + +Atomizer is an advanced optimization platform for Siemens NX Simcenter that combines: +- **LLM-driven configuration** via conversational interface (MCP) +- **Superior optimization** using Optuna (TPE, Gaussian Process surrogates) +- **Real-time monitoring** with interactive dashboards +- **Flexible architecture** with pluggable result extractors +- **NXOpen integration** for seamless NX automation + +**Goal**: Create a general-purpose FEA optimization tool more powerful and flexible than NX's built-in optimizer. + +--- + +## 📂 Repository Structure + +``` +C:\Users\antoi\Documents\Atomaste\Atomizer\ +├── .git/ # Git repository +├── .gitignore # Python, NX, optimization files +├── LICENSE # Proprietary license +├── README.md # Main documentation +├── GITHUB_SETUP.md # GitHub push instructions +├── DEVELOPMENT.md # Development workflow guide +├── PROJECT_SUMMARY.md # This file +├── pyproject.toml # Python package config +├── requirements.txt # Pip dependencies +│ +├── config/ # Configuration templates +│ ├── nx_config.json.template # NX paths (NX 2412) +│ └── optimization_config_template.json # Optimization setup +│ +├── mcp_server/ # MCP Server (LLM interface) +│ ├── __init__.py +│ ├── tools/ # MCP tool implementations +│ │ └── __init__.py # Tool registry +│ ├── schemas/ # JSON validation schemas +│ └── prompts/ +│ ├── system_prompt.md # LLM instructions (complete) +│ └── examples/ # Few-shot examples +│ +├── optimization_engine/ # Core optimization logic +│ ├── __init__.py +│ └── result_extractors/ # Pluggable metric extractors +│ └── __init__.py # Base class + registry +│ +├── nx_journals/ # NXOpen scripts +│ ├── __init__.py +│ └── utils/ # Helper functions +│ +├── dashboard/ # Web UI (planned) +│ ├── frontend/ # React app +│ └── backend/ # FastAPI server +│ +├── docs/ +│ ├── NXOPEN_RESOURCES.md # NXOpen reference guide +│ └── configuration.md # (planned) +│ +├── tests/ # Unit tests +└── examples/ # Example projects +``` + +--- + +## 🔑 Key Technologies + +### Core Stack +- **Python 3.10** (conda environment: `atomizer`) +- **Siemens NX 2412** with NX Nastran solver +- **Optuna 3.5+** for optimization +- **pyNastran 1.4+** for OP2/F06 parsing +- **Pandas 2.0+** for data management + +### MCP & Dashboard +- **MCP Protocol** for LLM integration +- **FastAPI** for backend server +- **WebSockets** for real-time updates +- **React + TypeScript** for frontend (planned) +- **Plotly.js** for 3D visualizations + +### Development Tools +- **pytest** for testing +- **black** for code formatting +- **ruff** for linting +- **Git** for version control + +--- + +## 🏗️ Architecture Overview + +### Three-Tier Design + +``` +┌─────────────────────────────────────────────────────────┐ +│ TIER 1: UI Layer │ +│ ┌─────────────────────┐ ┌──────────────────────────┐ │ +│ │ Web Dashboard │ │ LLM Chat Interface │ │ +│ │ (React + Plotly) │ │ (MCP Client) │ │ +│ └─────────────────────┘ └──────────────────────────┘ │ +└─────────────────────────────────────────────────────────┘ + ↕ HTTP/WebSocket +┌─────────────────────────────────────────────────────────┐ +│ TIER 2: MCP Server │ +│ ┌──────────────────────────────────────────────────┐ │ +│ │ • Model Discovery (parse .sim files) │ │ +│ │ • Config Builder (generate optimization.json) │ │ +│ │ • Optimizer Control (start/stop/monitor) │ │ +│ │ • Result Analyzer (extract metrics) │ │ +│ │ • NXOpen API Wrapper (file-based bridge) │ │ +│ └──────────────────────────────────────────────────┘ │ +└─────────────────────────────────────────────────────────┘ + ↕ File I/O + Subprocess +┌─────────────────────────────────────────────────────────┐ +│ TIER 3: Execution Layer │ +│ ┌──────────┐ ┌──────────┐ ┌────────────────────┐ │ +│ │ NX Core │ │ Optuna │ │ Custom Scripts │ │ +│ │ (NXOpen) │ │ Engine │ │ (Parsing/Analysis) │ │ +│ └──────────┘ └──────────┘ └────────────────────┘ │ +└─────────────────────────────────────────────────────────┘ +``` + +### File-Based Communication Pattern +- **MCP Server** ↔ **NX Journals**: JSON request/response files +- **Optimization Engine** ↔ **NX**: Expression files (.exp) +- **Results**: CSV (history.csv) + SQLite (optuna_study.db) + +--- + +## 🧩 Reusable Components from P04/Atomizer + +The following modules from your existing Atomizer project can be adapted: + +| P04 Module | New Location | Adaptation Needed | +|-----------|--------------|-------------------| +| `code/multi_optimizer.py` | `optimization_engine/multi_optimizer.py` | Minimal - Optuna logic is general | +| `code/config_loader.py` | `optimization_engine/config_loader.py` | Extend for extractor plugins | +| `code/surrogate_optimizer.py` | `optimization_engine/surrogate_optimizer.py` | Direct copy | +| `code/journal_NX_Update_and_Solve.py` | `nx_journals/update_and_solve.py` | Generalize for any .sim file | +| `code/zernike_Post_Script_NX.py` | `optimization_engine/result_extractors/zernike.py` | Convert to plugin class | +| `code/nx_post_each_iter.py` | `nx_journals/post_process.py` | Use extractor registry | + +**Key Insight**: The optimization engine core (Optuna, history management, CSV/DB) works as-is. Main changes are in result extraction (pluggable) and NX interaction (generalized). + +--- + +## 🛠️ MCP Tools (Planned) + +### Model Discovery +- **`discover_fea_model`**: Parse .sim files → extract solutions, expressions, FEM info +- **`search_nxopen_docs`**: Fetch Siemens NXOpen API documentation + +### Optimization Control +- **`build_optimization_config`**: Natural language → optimization_config.json +- **`start_optimization`**: Launch optimization run +- **`query_optimization_status`**: Get current iteration metrics + +### Result Analysis +- **`extract_results`**: Parse OP2/F06/XDB → stress, displacement, mass, etc. +- **`run_nx_journal`**: Execute custom NXOpen scripts + +--- + +## 📚 NXOpen Development Strategy + +### Resource Hierarchy +1. **Official Siemens NXOpen API** - Authoritative reference +2. **NXOpenTSE** - Patterns & best practices (reference only, not dependency) +3. **Atomizer-specific conventions** - Our implementation + +### NXOpenTSE Integration +- **GitHub**: https://github.com/theScriptingEngineer/nxopentse +- **Docs**: https://nxopentsedocumentation.thescriptingengineer.com/ +- **Usage**: Reference for learning, NOT for copying code +- **Benefits**: + - See proven design patterns + - Learn error handling approaches + - Understand NX-specific gotchas + - Discover lesser-known APIs + +### Code Generation Workflow (via MCP) +1. Check official API for method signatures +2. Reference NXOpenTSE for usage patterns +3. Adapt to Atomizer's architecture +4. Add error handling and attribution comments + +**See**: `docs/NXOPEN_RESOURCES.md` for complete guide + +--- + +## 🔄 Development Phases (Recommended Order) + +### ✅ Phase 0: Foundation (COMPLETE) +- [x] Project structure created +- [x] Git repository initialized +- [x] GitHub remote configured (Anto01/Atomizer) +- [x] Documentation framework +- [x] NXOpen resources documented +- [x] MCP system prompt complete + +### 🎯 Phase 1: MCP Server Foundation (NEXT) +- [ ] Implement `discover_fea_model` tool +- [ ] Create .sim file parser +- [ ] Build expression extractor +- [ ] Test with real .sim files +- [ ] Validate JSON schema + +### 🔧 Phase 2: Optimization Engine Port +- [ ] Copy Atomizer's `multi_optimizer.py` +- [ ] Adapt `config_loader.py` for extractors +- [ ] Create pluggable result extractor system +- [ ] Implement Nastran OP2 extractor +- [ ] Implement NX mass properties extractor + +### 🔌 Phase 3: NXOpen Bridge +- [ ] Build file-based NXOpen API wrapper +- [ ] Create generic journal dispatcher +- [ ] Implement expression update journal +- [ ] Implement solve simulation journal +- [ ] Test with NX 2412 + +### 🎨 Phase 4: Dashboard UI +- [ ] React frontend skeleton +- [ ] FastAPI backend with WebSocket +- [ ] Real-time iteration monitoring +- [ ] Plotly visualizations +- [ ] Config editor UI + +### 🚀 Phase 5: Integration & Testing +- [ ] End-to-end workflow testing +- [ ] LLM prompt refinement +- [ ] Error handling improvements +- [ ] Performance optimization +- [ ] User documentation + +--- + +## 📝 Current Git Status + +**Repository**: https://github.com/Anto01/Atomizer +**Visibility**: Private +**Branch**: main +**Commits**: 5 + +### Commit History +``` +f359d4e - chore: Update NX version to 2412 +14d2b67 - docs: Add NXOpen resources guide and MCP system prompt +d1cbeb7 - Rebrand project from nx-optimaster to Atomizer +2201aee - docs: Add GitHub setup and development guides +aa3dafb - Initial commit: NX OptiMaster project structure +``` + +### Files Tracked (15) +- `.gitignore` +- `LICENSE` +- `README.md` +- `GITHUB_SETUP.md` +- `DEVELOPMENT.md` +- `PROJECT_SUMMARY.md` (this file) +- `pyproject.toml` +- `requirements.txt` +- `config/nx_config.json.template` +- `config/optimization_config_template.json` +- `mcp_server/__init__.py` +- `mcp_server/tools/__init__.py` +- `optimization_engine/__init__.py` +- `optimization_engine/result_extractors/__init__.py` +- `nx_journals/__init__.py` +- `mcp_server/prompts/system_prompt.md` +- `docs/NXOPEN_RESOURCES.md` + +--- + +## 🚀 Quick Start Commands + +### Clone Repository (Different Machine) +```bash +git clone https://github.com/Anto01/Atomizer.git +cd Atomizer +``` + +### Set Up Python Environment +```bash +# Create conda environment +conda create -n atomizer python=3.10 +conda activate atomizer + +# Install dependencies +pip install -e . + +# Install dev tools (optional) +pip install -e ".[dev]" + +# Install MCP (when ready) +pip install -e ".[mcp]" +``` + +### Configure NX Path +```bash +# Copy template +cp config/nx_config.json.template config/nx_config.json + +# Edit config/nx_config.json: +# - Set nx_executable to your NX 2412 path +# - Set python_env to your atomizer conda environment +``` + +### Git Workflow +```bash +# Create feature branch +git checkout -b feature/model-discovery + +# Make changes, commit +git add . +git commit -m "feat: implement FEA model discovery tool" + +# Push to GitHub +git push -u origin feature/model-discovery + +# Merge to main (after review) +git checkout main +git merge feature/model-discovery +git push origin main +``` + +--- + +## 🎯 Next Immediate Steps + +**When you're ready to start coding**, choose one of these entry points: + +### Option A: MCP Model Discovery (Recommended First) +**Goal**: Get LLM to parse .sim files and extract expressions + +**Tasks**: +1. Create `mcp_server/tools/model_discovery.py` +2. Implement .sim file parsing logic +3. Extract expression names and values +4. Return structured JSON for LLM +5. Test with your P04 .sim files + +**Benefit**: Establishes MCP pattern, immediately useful + +### Option B: Port Optimization Engine +**Goal**: Get core optimization working independently + +**Tasks**: +1. Copy `multi_optimizer.py`, `config_loader.py` from P04 +2. Adapt for general use (remove Zernike-specific code) +3. Update import paths +4. Create simple test case +5. Verify Optuna integration works + +**Benefit**: Core functionality ready, can test optimization without MCP + +### Option C: NXOpen Bridge +**Goal**: Get NX automation working via file-based communication + +**Tasks**: +1. Create `nx_journals/api_dispatcher.py` +2. Implement JSON request/response pattern +3. Test expression updates +4. Test .sim file loading +5. Document NXOpen patterns + +**Benefit**: NX integration ready for optimization loop + +--- + +## 📊 Key Design Decisions + +### 1. **Why File-Based Communication?** +- NXOpen requires NX GUI process +- MCP server runs in separate Python environment +- Files are robust, inspectable, version-controllable +- Proven pattern from P04 Atomizer + +### 2. **Why Pluggable Result Extractors?** +- Different FEA problems need different metrics +- Zernike analysis is specific to optical surfaces +- General tool needs stress, thermal, modal, etc. +- Easy to add new extractors without changing core + +### 3. **Why MCP vs. Direct UI?** +- Natural language is faster than JSON editing +- LLM can suggest reasonable parameter bounds +- Conversational debugging ("why did this fail?") +- Future: voice commands, multi-modal input + +### 4. **Why Dual Persistence (CSV + SQLite)?** +- CSV: Human-readable, Excel-compatible, git-friendly +- SQLite: Fast queries, Optuna requirement +- Sync on each iteration for crash recovery + +--- + +## 🔗 Important Links + +### GitHub +- **Repository**: https://github.com/Anto01/Atomizer +- **Issues**: GitHub Issues (private repository) + +### Documentation +- **Official NXOpen API**: https://docs.sw.siemens.com/en-US/doc/209349590/ +- **NXOpenTSE**: https://nxopentsedocumentation.thescriptingengineer.com/ +- **Optuna**: https://optuna.readthedocs.io/ +- **pyNastran**: https://github.com/SteveDoyle2/pyNastran + +### Local Documentation +- **NXOpen Resources**: `docs/NXOPEN_RESOURCES.md` +- **MCP System Prompt**: `mcp_server/prompts/system_prompt.md` +- **Development Guide**: `DEVELOPMENT.md` +- **GitHub Setup**: `GITHUB_SETUP.md` + +--- + +## 💡 Key Insights for Success + +1. **Start Small**: Implement one MCP tool at a time, test thoroughly +2. **Reference P04**: Your existing Atomizer is 80% of the solution +3. **Use NXOpenTSE**: Learn patterns, don't copy code +4. **Test Early**: Use real .sim files from day one +5. **Document as You Go**: Future you will thank present you +6. **Commit Often**: Small, focused commits are easier to debug + +--- + +## 🏁 Success Criteria + +**Phase 1 Complete When**: +- LLM can parse a .sim file and list expressions +- User can ask "what parameters can I optimize?" +- System responds with structured list + +**Phase 2 Complete When**: +- Can run optimization without LLM (manual config.json) +- Optuna suggests parameters +- Results saved to history.csv + +**Phase 3 Complete When**: +- NX journals can update expressions via file commands +- Solver runs automatically +- Results extracted to CSV + +**Phase 4 Complete When**: +- Dashboard shows real-time iteration updates +- User can monitor without opening NX +- Plots update automatically + +**Full System Complete When**: +- User says: "Optimize bracket.sim to reduce stress" +- LLM configures optimization +- NX runs iterations automatically +- Dashboard shows progress +- User gets optimized design + +--- + +**Project Status**: Foundation complete, ready for development +**Next Action**: Choose entry point (A, B, or C above) and start coding +**Estimated Timeline**: 12-16 weeks for full system (part-time) + +--- + +**Last Updated**: 2025-11-15 +**Maintained By**: Antoine (Anto01) +**Built With**: Claude Code 🤖