Commit Graph

9 Commits

Author SHA1 Message Date
a26914bbe8 feat: Add Studio UI, intake system, and extractor improvements
Dashboard:
- Add Studio page with drag-drop model upload and Claude chat
- Add intake system for study creation workflow
- Improve session manager and context builder
- Add intake API routes and frontend components

Optimization Engine:
- Add CLI module for command-line operations
- Add intake module for study preprocessing
- Add validation module with gate checks
- Improve Zernike extractor documentation
- Update spec models with better validation
- Enhance solve_simulation robustness

Documentation:
- Add ATOMIZER_STUDIO.md planning doc
- Add ATOMIZER_UX_SYSTEM.md for UX patterns
- Update extractor library docs
- Add study-readme-generator skill

Tools:
- Add test scripts for extraction validation
- Add Zernike recentering test

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-27 12:02:30 -05:00
5c419e2358 fix(canvas): Multiple fixes for drag-drop, undo/redo, and code generation
Drag-drop fixes:
- Fix Objective default data: use nested 'source' object with extractor_id/output_name
- Fix Constraint default data: use 'type' field (not constraint_type), 'threshold' (not limit)

Undo/Redo fixes:
- Remove dependency on isDirty flag (which is always false due to auto-save)
- Record snapshots based on actual spec changes via deep comparison

Code generation improvements:
- Update system prompt to support multiple extractor types:
  * OP2-based extractors for FEA results (stress, displacement, frequency)
  * Expression-based extractors for NX model values (dimensions, volumes)
  * Computed extractors for derived values (no FEA needed)
- Claude will now choose appropriate signature based on user's description
2026-01-20 15:08:49 -05:00
2f0f45de86 fix(spec): Correct volume extractor structure in m1_mirror_cost_reduction_lateral
- Change custom_function.code to function.source_code per AtomizerSpec v2.0 schema
2026-01-20 14:14:20 -05:00
cb6b130908 feat(config): Add AtomizerSpec v2.0 schema and migrate all studies
Added JSON Schema:
- optimization_engine/schemas/atomizer_spec_v2.json

Migrated 28 studies to AtomizerSpec v2.0 format:
- Drone_Gimbal studies (1)
- M1_Mirror studies (21)
- M2_Mirror studies (2)
- SheetMetal_Bracket studies (4)

Each atomizer_spec.json is the unified configuration containing:
- Design variables with bounds and expressions
- Extractors (standard and custom)
- Objectives and constraints
- Optimization algorithm settings
- Canvas layout information
2026-01-20 13:11:23 -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
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
b1ffc64407 feat: Implement SAT v3 achieving WS=205.58 (new campaign record)
Self-Aware Turbo v3 optimization validated on M1 Mirror flat back:
- Best WS: 205.58 (12% better than previous best 218.26)
- 100% feasibility rate, 100% unique designs
- Uses 556 training samples from V5-V8 campaign data

Key innovations in V9:
- Adaptive exploration schedule (15% → 8% → 3%)
- Mass threshold at 118 kg (optimal sweet spot)
- 70% exploitation near best design
- Seeded with best known design from V7
- Ensemble surrogate with R²=0.99

Updated documentation:
- SYS_16: SAT protocol updated to v3.0 VALIDATED
- Cheatsheet: Added SAT v3 as recommended method
- Context: Updated protocol overview

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-31 16:06:33 -05:00
f0e594570a docs: Add comprehensive podcast briefing document
- Add ATOMIZER_PODCAST_BRIEFING.md with complete technical overview
- Covers all 12 sections: architecture, optimization, neural acceleration
- Includes impressive statistics and metrics for podcast generation
- Update LAC failure insights from recent sessions
- Add M1_Mirror studies README

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-30 09:36:40 -05:00
faa7779a43 feat: Add L-BFGS gradient optimizer for surrogate polish phase
Implements gradient-based optimization exploiting MLP surrogate differentiability.
Achieves 100-1000x faster convergence than derivative-free methods (TPE, CMA-ES).

New files:
- optimization_engine/gradient_optimizer.py: GradientOptimizer class with L-BFGS/Adam/SGD
- studies/M1_Mirror/m1_mirror_adaptive_V14/run_lbfgs_polish.py: Per-study runner

Updated docs:
- SYS_14_NEURAL_ACCELERATION.md: Full L-BFGS section (v2.4)
- 01_CHEATSHEET.md: Quick reference for L-BFGS usage
- atomizer_fast_solver_technologies.md: Architecture context

Usage: python -m optimization_engine.gradient_optimizer studies/my_study --n-starts 20

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

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2025-12-28 16:36:18 -05:00