## 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>
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Backend Integration Plan
Objective
Implement the backend logic required to support the advanced dashboard features, including study creation, real-time data streaming, 3D mesh conversion, and report generation.
1. Enhanced WebSocket Real-Time Streaming
File: atomizer-dashboard/backend/api/websocket/optimization_stream.py
Tasks
- Update
OptimizationFileHandlerto watch forpareto_frontupdates. - Update
OptimizationFileHandlerto watch foroptimizer_stateupdates. - Implement broadcasting logic for new event types:
pareto_front,optimizer_state.
2. Study Creation API
File: atomizer-dashboard/backend/api/routes/optimization.py
Tasks
- Implement
POST /api/optimization/studiesendpoint. - Add logic to handle multipart/form-data (config + files).
- Create study directory structure (
1_setup,2_results, etc.). - Save uploaded files (
.prt,.sim,.fem) to1_setup/model/. - Save configuration to
1_setup/optimization_config.json.
3. 3D Mesh Visualization API
File: atomizer-dashboard/backend/api/routes/optimization.py & optimization_engine/mesh_converter.py
Tasks
- Create
optimization_engine/mesh_converter.pyutility.- Implement
convert_to_gltf(bdf_path, op2_path, output_path)function. - Use
pyNastranto read BDF/OP2. - Use
trimesh(or custom logic) to export GLTF.
- Implement
- Implement
POST /api/optimization/studies/{study_id}/convert-meshendpoint. - Implement
GET /api/optimization/studies/{study_id}/mesh/{filename}endpoint.
4. Report Generation API
File: atomizer-dashboard/backend/api/routes/optimization.py & optimization_engine/report_generator.py
Tasks
- Create
optimization_engine/report_generator.pyutility.- Implement
generate_report(study_id, format, include_llm)function. - Use
markdownandweasyprint(optional) for rendering.
- Implement
- Implement
POST /api/optimization/studies/{study_id}/generate-reportendpoint. - Implement
GET /api/optimization/studies/{study_id}/reports/{filename}endpoint.
5. Dependencies
File: atomizer-dashboard/backend/requirements.txt
Tasks
- Add
python-multipart(for file uploads). - Add
pyNastran(for mesh conversion). - Add
trimesh(optional, for GLTF export). - Add
markdown(for report generation). - Add
weasyprint(optional, for PDF generation).
Execution Order
- Dependencies: Update
requirements.txtand install packages. - Study Creation: Implement the POST endpoint to enable the Configurator.
- WebSocket: Enhance the stream to support advanced visualizations.
- 3D Pipeline: Build the mesh converter and API endpoints.
- Reporting: Build the report generator and API endpoints.