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docs: Comprehensive documentation update for Dashboard V3 and Canvas

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## Documentation Updates
- DASHBOARD.md: Updated to V3.0 with Canvas V3 features, file browser, introspection
- DASHBOARD_IMPLEMENTATION_STATUS.md: Marked Canvas V3 features as COMPLETE
- CANVAS.md: New comprehensive guide for Canvas Builder V3 with all features
- CLAUDE.md: Added dashboard quick reference and Canvas V3 features

## Canvas V3 Features Documented
- File Browser: Browse studies directory for model files
- Model Introspection: Auto-discover expressions, solver type, dependencies
- One-Click Add: Add expressions as design variables instantly
- Claude Bug Fixes: WebSocket reconnection, SQL errors resolved
- Health Check: /api/health endpoint for monitoring

## Backend Services
- NX introspection service with expression discovery
- File browser API with type filtering
- Claude session management improvements
- Context builder enhancements

## Frontend Components
- FileBrowser: Modal for file selection with search
- IntrospectionPanel: View discovered model information
- ExpressionSelector: Dropdown for design variable configuration
- Improved chat hooks with reconnection logic

## Plan Documents
- Added RALPH_LOOP_CANVAS_V2/V3 implementation records
- Added ATOMIZER_DASHBOARD_V2_MASTER_PLAN
- Added investigation and sync documentation

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# Atomizer Canvas - Visual Workflow Builder
**Last Updated**: January 16, 2026
**Version**: 3.0
**Status**: Production
---
## Overview
The Atomizer Canvas is a visual, node-based workflow builder for designing optimization studies. It provides a drag-and-drop interface for configuring FEA optimizations that integrates with Claude to validate and execute workflows.
### Key Features
- **Visual Workflow Design**: Drag-and-drop nodes to build optimization pipelines
- **Professional Lucide Icons**: Clean, consistent iconography throughout the interface
- **Auto-Load from Studies**: Import existing optimization_config.json files
- **NX Model Introspection**: Automatically extract expressions from .prt/.sim/.fem files
- **File Browser**: Browse and select model files with type filtering
- **Expression Search**: Searchable dropdown for design variable configuration
- **One-Click Add**: Add discovered expressions as design variables instantly
- **Claude Integration**: "Process with Claude" button for AI-assisted study creation
- **Responsive Layout**: Full-screen canvas that adapts to window size
### What's New in V3
| Feature | Description |
|---------|-------------|
| **File Browser** | Browse studies directory for .sim/.prt/.fem/.afem files |
| **Introspection Panel** | View discovered expressions, extractors, and dependencies |
| **One-Click Add** | Add expressions as design variables with a single click |
| **Claude Fixes** | Fixed SQL errors, WebSocket reconnection issues |
| **Health Check** | `/api/health` endpoint for database monitoring |
---
## Architecture
### Frontend Stack
| Component | Technology | Purpose |
|-----------|------------|---------|
| Flow Engine | React Flow | Node-based graph rendering |
| State Management | Zustand | Canvas state (nodes, edges, selection) |
| Icons | Lucide React | Professional icon library |
| Styling | Tailwind CSS | Dark theme (Atomaster palette) |
| Chat | WebSocket | Real-time Claude communication |
### Node Types (8)
| Node | Icon | Description | Color |
|------|------|-------------|-------|
| **Model** | `Cube` | NX model file (.prt, .sim, .fem) | Blue |
| **Solver** | `Cpu` | Nastran solution type (SOL101, SOL103, etc.) | Violet |
| **Design Variable** | `SlidersHorizontal` | Parameter to optimize with bounds | Emerald |
| **Extractor** | `FlaskConical` | Physics result extraction (E1-E10) | Cyan |
| **Objective** | `Target` | Optimization goal (minimize/maximize) | Rose |
| **Constraint** | `ShieldAlert` | Design constraint (upper/lower bounds) | Amber |
| **Algorithm** | `BrainCircuit` | Optimization method (TPE, CMA-ES, NSGA-II) | Indigo |
| **Surrogate** | `Rocket` | Neural acceleration (optional) | Pink |
### File Structure
```
atomizer-dashboard/frontend/src/
├── components/canvas/
│ ├── AtomizerCanvas.tsx # Main canvas component
│ ├── nodes/
│ │ ├── index.ts # Node type registry
│ │ ├── BaseNode.tsx # Base node with handles
│ │ ├── ModelNode.tsx # Model file node
│ │ ├── SolverNode.tsx # Solver type node
│ │ ├── DesignVarNode.tsx # Design variable node
│ │ ├── ExtractorNode.tsx # Extractor node
│ │ ├── ObjectiveNode.tsx # Objective node
│ │ ├── ConstraintNode.tsx # Constraint node
│ │ ├── AlgorithmNode.tsx # Algorithm node
│ │ └── SurrogateNode.tsx # Surrogate node
│ ├── panels/
│ │ ├── NodeConfigPanel.tsx # Node configuration sidebar
│ │ ├── ValidationPanel.tsx # Validation toast display
│ │ ├── ExecuteDialog.tsx # Execute confirmation modal
│ │ ├── ChatPanel.tsx # Claude chat sidebar
│ │ ├── ConfigImporter.tsx # Study import dialog
│ │ ├── TemplateSelector.tsx # Workflow template chooser
│ │ ├── FileBrowser.tsx # File picker modal (V3)
│ │ ├── IntrospectionPanel.tsx # Model introspection results (V3)
│ │ └── ExpressionSelector.tsx # Expression search dropdown (V3)
│ └── palette/
│ └── NodePalette.tsx # Draggable node palette
├── hooks/
│ ├── useCanvasStore.ts # Zustand store for canvas state
│ └── useCanvasChat.ts # Claude chat integration
├── lib/canvas/
│ ├── schema.ts # TypeScript type definitions
│ ├── intent.ts # Intent serialization (174 lines)
│ ├── validation.ts # Graph validation logic
│ └── templates.ts # Workflow templates
└── pages/
└── CanvasView.tsx # Canvas page (/canvas route)
```
---
## User Interface
### Layout
```
┌───────────────────────────────────────────────────────────────────┐
│ Canvas Builder Templates Import│
├──────────┬────────────────────────────────────────────┬───────────┤
│ │ │ │
│ Node │ Canvas Area │ Config │
│ Palette │ │ Panel │
│ │ ┌─────┐ ┌─────┐ ┌─────┐ │ │
│ [Model] │ │Model├──────│Solver├──────│Algo │ │ Label: │
│ [Solver]│ └─────┘ └──┬──┘ └─────┘ │ [____] │
│ [DVar] │ │ │ │
│ [Extr] │ ┌─────┐ ┌──┴──┐ ┌─────┐ │ Type: │
│ [Obj] │ │ DVar├──────│Extr ├──────│ Obj │ │ [____] │
│ [Const] │ └─────┘ └─────┘ └─────┘ │ │
│ [Algo] │ │ │
│ [Surr] │ │ │
│ │ │ │
├──────────┴────────────────────────────────────────────┴───────────┤
│ [Validate] [Process with Claude] │
└───────────────────────────────────────────────────────────────────┘
```
### Dark Theme (Atomaster Palette)
| Element | Color | Tailwind Class |
|---------|-------|----------------|
| Background | `#050A12` | `bg-dark-900` |
| Surface | `#0A1525` | `bg-dark-850` |
| Card | `#0F1E32` | `bg-dark-800` |
| Border | `#1A2F4A` | `border-dark-700` |
| Muted Text | `#5A7A9A` | `text-dark-400` |
| Primary | `#00D4E6` | `text-primary-400` |
---
## Core Workflows
### 1. Building a Workflow
1. **Drag nodes** from the left palette onto the canvas
2. **Connect nodes** by dragging from output handle to input handle
3. **Configure nodes** by clicking to open the config panel
4. **Validate** using the Validate button
5. **Process with Claude** to create the study
### 2. Importing from Existing Study
1. Click **Import** in the header
2. Select the **Load Study** tab
3. **Search** for your study by name
4. **Select** a study with an optimization_config.json
5. Click **Load Study** to populate the canvas
### 3. Using Templates
1. Click **Templates** in the header
2. Browse available workflow templates:
- **Mass Minimization**: Single-objective mass reduction
- **Multi-Objective**: Pareto optimization (mass + displacement)
- **Turbo Mode**: Neural-accelerated optimization
- **Mirror WFE**: Zernike wavefront error optimization
- **Frequency Target**: Natural frequency optimization
3. Click a template to load it
### 4. Processing with Claude
1. Build and configure your workflow
2. Click **Validate** to check for errors
3. Click **Process with Claude** to:
- Validate the configuration against Atomizer protocols
- Receive recommendations (method selection, trial count)
- Create the optimization study
---
## Node Configuration
### Model Node
| Field | Description | Example |
|-------|-------------|---------|
| File Path | Path to NX model | `models/bracket.sim` |
| File Type | prt, sim, or fem | `sim` |
When loading a `.sim` file, the system introspects to find:
- Linked `.prt` (geometry part)
- Linked `.fem` (FEM file)
- Solver type (SOL101, SOL103, etc.)
- Available expressions
### Design Variable Node
| Field | Description | Example |
|-------|-------------|---------|
| Expression Name | NX expression to vary | `thickness` |
| Min Value | Lower bound | `5.0` |
| Max Value | Upper bound | `15.0` |
| Unit | Engineering unit | `mm` |
**Expression Selector**: Click the dropdown to:
- **Search** through available expressions
- **Filter** by name
- **Refresh** to reload from model
- **Enter manually** if expression not found
### Extractor Node
| Field | Description | Options |
|-------|-------------|---------|
| Extractor ID | Protocol E1-E10 | E1 (Displacement), E2 (Frequency), etc. |
| Name | Display name | `max_displacement` |
| Config | Extractor-specific settings | Node ID, component, etc. |
**Available Extractors** (SYS_12):
| ID | Physics | Function |
|----|---------|----------|
| E1 | Displacement | `extract_displacement()` |
| E2 | Frequency | `extract_frequency()` |
| E3 | Stress | `extract_solid_stress()` |
| E4 | BDF Mass | `extract_mass_from_bdf()` |
| E5 | CAD Mass | `extract_mass_from_expression()` |
| E8 | Zernike | `extract_zernike_coefficients()` |
| E9 | Zernike | `extract_zernike_rms()` |
| E10 | Zernike | `extract_zernike_wfe()` |
### Objective Node
| Field | Description | Options |
|-------|-------------|---------|
| Name | Objective identifier | `mass`, `displacement` |
| Direction | Optimization goal | `minimize`, `maximize` |
| Weight | Multi-objective weight | `1.0` (0.0-10.0) |
### Constraint Node
| Field | Description | Example |
|-------|-------------|---------|
| Name | Constraint identifier | `max_stress` |
| Operator | Comparison type | `<=`, `>=`, `==` |
| Value | Threshold value | `250.0` |
### Algorithm Node
| Field | Description | Options |
|-------|-------------|---------|
| Method | Optimization algorithm | TPE, CMA-ES, NSGA-II, GP-BO |
| Max Trials | Number of trials | `100` |
| Timeout | Optional time limit | `3600` (seconds) |
**Method Selection** (SYS_15):
| Method | Best For | Design Vars | Objectives |
|--------|----------|-------------|------------|
| TPE | General purpose | 1-10 | 1 |
| CMA-ES | Many variables | 5-100 | 1 |
| NSGA-II | Multi-objective | 1-20 | 2-4 |
| GP-BO | Expensive evaluations | 1-10 | 1 |
### Surrogate Node
| Field | Description | Options |
|-------|-------------|---------|
| Enabled | Toggle acceleration | true/false |
| Model Type | Surrogate architecture | MLP, GNN, Auto |
| Min Trials | Trials before activation | `20` |
---
## File Browser (V3)
The File Browser allows you to navigate the studies directory to select model files.
### Features
- **Directory Navigation**: Browse folder hierarchy with breadcrumbs
- **Type Filtering**: Filters to `.sim`, `.prt`, `.fem`, `.afem` by default
- **Search**: Quick search by file name
- **Single-Click Select**: Click a file to select and close
### Usage
1. Click the **Browse** button (folder icon) next to the Model file path input
2. Navigate to your study folder
3. Click a model file to select it
4. The path is automatically populated in the Model node
---
## Model Introspection (V3)
Model Introspection analyzes NX model files to discover expressions, solver type, and dependencies.
### Features
- **Expression Discovery**: Lists all expressions found in the model
- **Solver Detection**: Infers solver type from file contents (SOL101, SOL103, etc.)
- **Dependency Tracking**: Shows related .prt, .fem, .afem files
- **Extractor Suggestions**: Recommends extractors based on solver type
- **One-Click Add**: Add expressions as Design Variables instantly
### Usage
1. Configure a **Model** node with a valid file path
2. Click **Introspect Model** button
3. View discovered expressions, extractors, and files
4. Click **+** next to any expression to add as Design Variable
5. Click **+** next to any extractor to add to canvas
### Discovered Information
| Section | Contents |
|---------|----------|
| **Solver Type** | Detected solver (SOL101, SOL103, etc.) |
| **Expressions** | Name, current value, unit |
| **Extractors** | Available extractors for this solver |
| **Dependent Files** | Related .prt, .fem, .afem files |
---
## API Integration
### Backend Endpoints
#### Study Configuration
```
GET /api/studies/ # List all studies
GET /api/studies/{path}/config # Get optimization_config.json
```
#### File Browser (V3)
```
GET /api/files/list # List files in directory
Query: path=subdir&types=.sim,.prt,.fem,.afem
Returns: { files: [{name, path, isDirectory}], path }
```
#### NX Introspection (V3)
```
POST /api/nx/introspect # Introspect NX model file
Body: { file_path: string }
Returns: {
file_path, file_type, expressions, solver_type,
dependent_files, extractors_available, warnings
}
GET /api/nx/expressions # Get expressions from model
Query: file_path=path/to/model.sim
Returns: { expressions: [{name, value, unit, type}] }
```
#### Health Check (V3)
```
GET /api/health # Check database and service health
Returns: { status: "healthy", database: "connected" }
```
### MCP Canvas Tools
The Canvas integrates with the MCP server for Claude tool use:
#### `validate_canvas_intent`
Validates an optimization intent from the Canvas.
```typescript
{
intent: OptimizationIntent // The canvas workflow as JSON
}
// Returns: { valid, errors, warnings, recommendations }
```
#### `execute_canvas_intent`
Creates an optimization study from a validated intent.
```typescript
{
intent: OptimizationIntent,
study_name: string, // snake_case name
auto_run?: boolean // Start optimization immediately
}
// Returns: { study_path, config_path, status }
```
#### `interpret_canvas_intent`
Analyzes a Canvas intent and provides recommendations.
```typescript
{
intent: OptimizationIntent
}
// Returns: {
// problem_type: "single-objective" | "multi-objective",
// complexity: "low" | "medium" | "high",
// recommended_method: string,
// recommended_trials: number,
// surrogate_recommended: boolean,
// notes: string[]
// }
```
---
## OptimizationIntent Schema
The Canvas serializes workflows to the `OptimizationIntent` JSON format:
```typescript
interface OptimizationIntent {
model: {
path: string;
type: 'prt' | 'sim' | 'fem';
};
solver: {
type: string; // SOL101, SOL103, etc.
};
design_variables: Array<{
name: string;
expression: string;
min: number;
max: number;
unit?: string;
}>;
extractors: Array<{
id: string; // E1, E2, etc.
name: string;
config?: Record<string, unknown>;
}>;
objectives: Array<{
name: string;
extractor: string;
direction: 'minimize' | 'maximize';
weight?: number;
}>;
constraints?: Array<{
name: string;
extractor: string;
operator: '<=' | '>=' | '==';
value: number;
}>;
optimization: {
method: string;
max_trials: number;
timeout?: number;
};
surrogate?: {
enabled: boolean;
model_type?: string;
min_trials?: number;
};
}
```
---
## Validation Rules
The Canvas validates workflows against these rules:
### Required Components
- At least 1 **Model** node
- At least 1 **Solver** node
- At least 1 **Design Variable** node
- At least 1 **Objective** node
- At least 1 **Algorithm** node
### Configuration Rules
- All nodes must be **configured** (no empty fields)
- Design variable **min < max**
- Objective must connect to an **Extractor**
- Extractor ID must be valid (E1-E10)
### Connection Rules
- Model → Solver (required)
- Solver → Extractor (required for each extractor)
- Extractor → Objective (required for each objective)
- Extractor → Constraint (optional)
### Recommendations
- Multi-objective (2+ objectives) should use **NSGA-II**
- Many variables (5+) may benefit from **surrogate**
- High trial count (100+) should consider **neural acceleration**
---
## Templates
### Mass Minimization
Single-objective mass reduction with stress constraint.
- **Nodes**: 6 (Model, Solver, DVar, Extractor, Objective, Algorithm)
- **Objective**: Minimize mass
- **Constraint**: Max stress < limit
- **Method**: TPE (100 trials)
### Multi-Objective
Pareto optimization for mass vs. displacement trade-off.
- **Nodes**: 7
- **Objectives**: Minimize mass, Minimize displacement
- **Method**: NSGA-II (150 trials)
### Turbo Mode
Neural-accelerated optimization with surrogate.
- **Nodes**: 8 (includes Surrogate)
- **Objective**: User-defined
- **Method**: TPE + MLP Surrogate
- **Trials**: 50 FEA + 5000 surrogate
### Mirror WFE
Zernike wavefront error optimization for optics.
- **Nodes**: 7
- **Objective**: Minimize WFE (E10)
- **Method**: CMA-ES (200 trials)
### Frequency Target
Natural frequency optimization with modal analysis.
- **Nodes**: 6
- **Objective**: Target frequency (E2)
- **Method**: TPE (100 trials)
---
## Keyboard Shortcuts
| Key | Action |
|-----|--------|
| `Delete` / `Backspace` | Delete selected node |
| `Escape` | Deselect all |
| `Ctrl+Z` | Undo (future) |
| `Ctrl+Shift+Z` | Redo (future) |
| `Space` (hold) | Pan canvas |
| Scroll | Zoom in/out |
---
## Troubleshooting
### Canvas Not Visible
- Ensure you're on the `/canvas` route
- Check for JavaScript errors in browser console
- Verify React Flow is properly initialized
### Nodes Not Draggable
- Check that drag-and-drop events are being captured
- Ensure `onDragStart` sets the correct data type
### Config Panel Not Updating
- Verify Zustand store is properly connected
- Check that `updateNodeData` is being called
### Claude Chat Not Working
- Check WebSocket connection status (green indicator)
- Verify backend is running on port 8000
- Check `/api/chat/` endpoint is accessible
### Expression Dropdown Empty
- Ensure a Model node is configured with a file path
- Check `/api/nx/expressions` endpoint is working
- Try the "Refresh" button to reload expressions
---
## Development
### Running Locally
```bash
# Frontend
cd atomizer-dashboard/frontend
npm install
npm run dev
# Backend
cd atomizer-dashboard/backend
python -m uvicorn api.main:app --reload --port 8000
# MCP Server
cd mcp-server/atomizer-tools
npm run build
npm run dev
```
### Building for Production
```bash
# Frontend
cd atomizer-dashboard/frontend
npm run build
# MCP Server
cd mcp-server/atomizer-tools
npm run build
```
### Adding New Node Types
1. Create node component in `components/canvas/nodes/`
2. Add type to `schema.ts`
3. Register in `nodes/index.ts`
4. Add to `NodePalette.tsx`
5. Update validation rules in `validation.ts`
6. Add serialization logic to `intent.ts`
---
## References
- **React Flow Documentation**: https://reactflow.dev/
- **Lucide Icons**: https://lucide.dev/icons/
- **Zustand**: https://github.com/pmndrs/zustand
- **Atomizer Protocols**: See `docs/protocols/`
- **Extractor Library**: See `SYS_12_EXTRACTOR_LIBRARY.md`
- **Method Selector**: See `SYS_15_METHOD_SELECTOR.md`
---
*Canvas Builder: Design optimizations visually, execute with AI.*

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@@ -1,6 +1,7 @@
# Atomizer Dashboard
**Last Updated**: December 5, 2025
**Last Updated**: January 16, 2026
**Version**: 3.0
---
@@ -8,6 +9,18 @@
The Atomizer Dashboard is a real-time web-based interface for monitoring and analyzing multi-objective optimization studies. Built with React, TypeScript, and Tailwind CSS, it provides comprehensive visualization and interaction capabilities for NSGA-II based structural optimization.
### Major Features
| Feature | Route | Description |
|---------|-------|-------------|
| **Canvas Builder** | `/canvas` | Visual node-based workflow designer |
| **Live Dashboard** | `/dashboard` | Real-time optimization monitoring |
| **Results Viewer** | `/results` | Markdown reports with charts |
| **Analytics** | `/analytics` | Cross-study comparison |
| **Claude Chat** | Global | AI-powered study creation |
> **New in V2**: The [Canvas Builder](CANVAS.md) provides a visual, drag-and-drop interface for designing optimization workflows with Claude AI integration.
---
## Architecture
@@ -197,6 +210,14 @@ Reusable markdown rendering component:
- README.md display with full markdown rendering
- New study creation via Claude terminal
### Canvas Page (`/canvas`) **NEW**
- Visual node-based workflow builder
- Drag-and-drop node palette with 8 node types
- Claude integration for workflow processing
- Auto-load from existing studies
- Expression search for design variables
- See [Canvas Documentation](CANVAS.md) for details
### Dashboard Page (`/dashboard`)
- Real-time live tracker for selected study
- Convergence plot, Pareto front, parameter importance
@@ -395,45 +416,92 @@ atomizer-dashboard/
├── frontend/
│ ├── src/
│ │ ├── components/
│ │ │ ├── ParallelCoordinatesPlot.tsx # Multi-objective visualization
│ │ │ ├── ParetoPlot.tsx # Pareto front scatter plot
│ │ │ ├── OptimizerPanel.tsx # Strategy information
│ │ │ ├── ConvergencePlot.tsx # Enhanced convergence chart
│ │ │ ├── ParameterImportanceChart.tsx # Correlation-based importance
│ │ │ ├── StudyReportViewer.tsx # Markdown report viewer
│ │ │ ├── MarkdownRenderer.tsx # Shared markdown renderer
│ │ │ ├── ClaudeTerminal.tsx # Claude AI terminal component
│ │ │ ├── GlobalClaudeTerminal.tsx # Global terminal wrapper
│ │ │ ├── canvas/ # Canvas Builder V2
│ │ │ │ ├── AtomizerCanvas.tsx # Main canvas with React Flow
│ │ │ │ ├── nodes/ # 8 node type components
│ │ │ │ │ ├── BaseNode.tsx # Base with Lucide icons
│ │ │ │ │ ├── ModelNode.tsx # Cube icon
│ │ │ │ │ ├── SolverNode.tsx # Cpu icon
│ │ │ │ │ ├── DesignVarNode.tsx # SlidersHorizontal icon
│ │ │ │ │ ├── ExtractorNode.tsx # FlaskConical icon
│ │ │ │ │ ├── ObjectiveNode.tsx # Target icon
│ │ │ │ │ ├── ConstraintNode.tsx # ShieldAlert icon
│ │ │ │ │ ├── AlgorithmNode.tsx # BrainCircuit icon
│ │ │ │ │ └── SurrogateNode.tsx # Rocket icon
│ │ │ │ ├── panels/
│ │ │ │ │ ├── NodeConfigPanel.tsx # Config sidebar
│ │ │ │ │ ├── ValidationPanel.tsx # Validation toast
│ │ │ │ │ ├── ChatPanel.tsx # Claude chat
│ │ │ │ │ ├── ConfigImporter.tsx # Study browser
│ │ │ │ │ └── TemplateSelector.tsx # Workflow templates
│ │ │ │ └── palette/
│ │ │ │ └── NodePalette.tsx # Draggable palette
│ │ │ ├── chat/ # Chat components
│ │ │ │ ├── ChatMessage.tsx # Message display
│ │ │ │ └── ThinkingIndicator.tsx # Loading indicator
│ │ │ ├── ParallelCoordinatesPlot.tsx # Multi-objective viz
│ │ │ ├── ParetoPlot.tsx # Pareto front scatter
│ │ │ ├── OptimizerPanel.tsx # Strategy info
│ │ │ ├── ConvergencePlot.tsx # Convergence chart
│ │ │ ├── ParameterImportanceChart.tsx # Parameter importance
│ │ │ ├── StudyReportViewer.tsx # Report viewer
│ │ │ ├── MarkdownRenderer.tsx # Markdown renderer
│ │ │ ├── ClaudeTerminal.tsx # Claude terminal
│ │ │ ├── GlobalClaudeTerminal.tsx # Global terminal
│ │ │ ├── common/
│ │ │ │ ├── Card.tsx # Reusable card component
│ │ │ │ └── Button.tsx # Reusable button component
│ │ │ │ ├── Card.tsx # Card component
│ │ │ │ └── Button.tsx # Button component
│ │ │ ├── layout/
│ │ │ │ ├── Sidebar.tsx # Navigation sidebar
│ │ │ │ └── MainLayout.tsx # Page layout wrapper
│ │ │ │ ├── Sidebar.tsx # Navigation
│ │ │ │ └── MainLayout.tsx # Layout wrapper
│ │ │ └── dashboard/
│ │ │ ├── MetricCard.tsx # KPI display
│ │ │ └── StudyCard.tsx # Study selector
│ │ │ ├── MetricCard.tsx # KPI display
│ │ │ └── StudyCard.tsx # Study selector
│ │ ├── pages/
│ │ │ ├── Home.tsx # Study selection & README
│ │ │ ├── Dashboard.tsx # Live optimization tracker
│ │ │ ├── Results.tsx # Report viewer
│ │ │ └── Analytics.tsx # Cross-study analytics
│ │ ├── context/
│ │ │ ├── StudyContext.tsx # Global study state
│ │ │ └── ClaudeTerminalContext.tsx # Terminal state
│ │ │ ├── Home.tsx # Study selection
│ │ │ ├── CanvasView.tsx # Canvas builder
│ │ │ ├── Dashboard.tsx # Live tracker
│ │ │ ├── Results.tsx # Report viewer
│ │ │ └── Analytics.tsx # Analytics
│ │ ├── hooks/
│ │ │ └── useWebSocket.ts # WebSocket connection
│ │ │ ├── useCanvasStore.ts # Zustand canvas state
│ │ │ ├── useCanvasChat.ts # Canvas chat
│ │ │ ├── useChat.ts # WebSocket chat
│ │ │ └── useWebSocket.ts # WebSocket base
│ │ ├── lib/canvas/
│ │ │ ├── schema.ts # Type definitions
│ │ │ ├── intent.ts # Intent serialization
│ │ │ ├── validation.ts # Graph validation
│ │ │ └── templates.ts # Workflow templates
│ │ ├── context/
│ │ │ ├── StudyContext.tsx # Study state
│ │ │ └── ClaudeTerminalContext.tsx # Terminal state
│ │ ├── api/
│ │ │ └── client.ts # API client
│ │ │ └── client.ts # API client
│ │ └── types/
│ │ └── index.ts # TypeScript types
│ │ └── index.ts # TypeScript types
│ └── vite.config.ts
└── backend/
└── api/
├── main.py # FastAPI app
└── routes/
├── optimization.py # Optimization endpoints
└── terminal.py # Claude terminal WebSocket
├── backend/
│ └── api/
│ ├── main.py # FastAPI app
│ ├── services/
│ │ ├── claude_agent.py # Claude API integration
│ │ ├── session_manager.py # Session lifecycle
│ │ ├── context_builder.py # Context assembly
│ │ └── conversation_store.py # SQLite persistence
│ └── routes/
│ ├── optimization.py # Optimization endpoints
│ ├── studies.py # Study config endpoints
│ ├── nx.py # NX introspection
│ └── terminal.py # Claude WebSocket
└── mcp-server/atomizer-tools/
└── src/
├── index.ts # MCP server entry
└── tools/
├── canvas.ts # Canvas tools
├── study.ts # Study management
├── optimization.ts # Optimization control
└── analysis.ts # Analysis tools
```
## NPM Dependencies
@@ -506,9 +574,40 @@ if (!objectives || !designVariables) return <EmptyState />;
---
## Recent Updates (December 2025)
## Recent Updates
### January 2026 (V3.0)
- [x] **Canvas Builder V3**: Major upgrade with model introspection and Claude fixes
- **File Browser**: Browse studies directory for .sim/.prt/.fem/.afem files
- **Model Introspection**: Auto-discover expressions, solver type, and dependencies
- **One-Click Add**: Add expressions as design variables, add suggested extractors
- **Claude Bug Fixes**: Fixed SQL errors, WebSocket reconnection, chat integration
- **Connection Flow Fix**: Design variables now correctly flow INTO model nodes
- **Health Check Endpoint**: `/api/health` for database status monitoring
- [x] **Canvas Builder V2**: Complete visual workflow designer with React Flow
- 8 node types with professional Lucide icons
- Drag-and-drop node palette
- Expression search dropdown for design variables
- Auto-load from existing optimization_config.json
- "Process with Claude" button for AI-assisted study creation
- MCP canvas tools (validate, execute, interpret)
- Responsive full-screen layout
- [x] **Backend Services**:
- NX introspection service (`/api/nx/introspect`, `/api/nx/expressions`)
- File browser API (`/api/files/list`)
- Claude session management with SQLite persistence
- Context builder for study-aware conversations
- [x] **Optimization Engine v2.0**: Major code reorganization
- New modular structure: `core/`, `nx/`, `study/`, `config/`, `reporting/`, `processors/`
- Backwards-compatible imports with deprecation warnings
- 120 files reorganized for better maintainability
### December 2025
### Completed
- [x] **Convergence Plot**: Enhanced with running best, statistics, and gradient fill
- [x] **Parameter Importance Chart**: Correlation analysis with color-coded bars
- [x] **Study Report Viewer**: Full markdown rendering with KaTeX math support
@@ -530,6 +629,7 @@ if (!objectives || !designVariables) return <EmptyState />;
- [ ] Hypervolume indicator tracking
- [ ] Interactive design variable sliders
- [ ] Constraint importance analysis
- [ ] Tauri desktop application (Phase 5)
---

505
docs/04_USER_GUIDES/DASHBOARD_IMPLEMENTATION_STATUS.md
View File

@@ -1,293 +1,300 @@
# Dashboard Implementation Status
**Last Updated**: November 21, 2025
**Last Updated**: January 16, 2026
**Version**: 3.0
---
## Overview
Dashboard implementation following the master plan in [DASHBOARD_MASTER_PLAN.md](DASHBOARD_MASTER_PLAN.md), prioritized as:
1. **Live Dashboard** (Phase 4) - In Progress
2. Study Configurator (Phase 3)
3. Results Viewer (Phase 5)
The Atomizer Dashboard V2 is now feature-complete with the Canvas Builder. This document tracks implementation status across all major features.
---
## Completed: Backend (Phase 1 + 4)
## Phase Summary
### ✅ FastAPI Backend
- **Main application**: [atomizer-dashboard/backend/api/main.py](../atomizer-dashboard/backend/api/main.py)
- **CORS middleware** configured for local development
- **Auto-reload** enabled for development
| Phase | Name | Status | Notes |
|-------|------|--------|-------|
| 0 | MCP Chat Foundation | COMPLETE | Claude API integration, session management |
| 1 | Canvas with React Flow | COMPLETE | 8 node types, validation, serialization |
| 2 | LLM Intelligence Layer | COMPLETE | Canvas chat hook, MCP canvas tools |
| 3 | Bidirectional Sync | COMPLETE | Session persistence, context builder |
| 4 | Templates & Polish | COMPLETE | Template selector, config importer |
| 5 | Tauri Desktop | PLANNED | Future phase |
### ✅ REST API Endpoints
**File**: [atomizer-dashboard/backend/api/routes/optimization.py](../atomizer-dashboard/backend/api/routes/optimization.py)
---
Implemented endpoints:
- `GET /api/optimization/studies` - List all studies
- `GET /api/optimization/studies/{study_id}/status` - Get study status
- `GET /api/optimization/studies/{study_id}/history` - Get trial history
- `GET /api/optimization/studies/{study_id}/pruning` - Get pruning diagnostics
## Phase 0: MCP Chat Foundation - COMPLETE
### ✅ WebSocket Real-Time Updates
**File**: [atomizer-dashboard/backend/api/websocket/optimization_stream.py](../atomizer-dashboard/backend/api/websocket/optimization_stream.py)
### Backend Services
| Component | File | Lines | Status |
|-----------|------|-------|--------|
| Claude Agent | `backend/api/services/claude_agent.py` | 722 | COMPLETE |
| CLI Agent | `backend/api/services/claude_cli_agent.py` | 202 | COMPLETE |
| Conversation Store | `backend/api/services/conversation_store.py` | 295 | COMPLETE |
| Session Manager | `backend/api/services/session_manager.py` | 425 | COMPLETE |
| Context Builder | `backend/api/services/context_builder.py` | 246 | COMPLETE |
### MCP Server
| Tool | Description | Status |
|------|-------------|--------|
| `list_studies` | List all studies | COMPLETE |
| `get_study_status` | Study details | COMPLETE |
| `create_study` | Create from description | COMPLETE |
| `run_optimization` | Start optimization | COMPLETE |
| `stop_optimization` | Stop optimization | COMPLETE |
| `get_trial_data` | Query trials | COMPLETE |
| `analyze_convergence` | Convergence metrics | COMPLETE |
| `compare_trials` | Side-by-side comparison | COMPLETE |
| `get_best_design` | Best design details | COMPLETE |
| `generate_report` | Markdown reports | COMPLETE |
| `export_data` | CSV/JSON export | COMPLETE |
| `explain_physics` | FEA concepts | COMPLETE |
| `recommend_method` | Algorithm recommendation | COMPLETE |
| `query_extractors` | Extractor list | COMPLETE |
---
## Phase 1: Canvas with React Flow - COMPLETE
### Core Components
| Component | Location | Status |
|-----------|----------|--------|
| Schema | `frontend/src/lib/canvas/schema.ts` | COMPLETE |
| Intent Serializer | `frontend/src/lib/canvas/intent.ts` | COMPLETE |
| Validation | `frontend/src/lib/canvas/validation.ts` | COMPLETE |
| Templates | `frontend/src/lib/canvas/templates.ts` | COMPLETE |
| Canvas Store | `frontend/src/hooks/useCanvasStore.ts` | COMPLETE |
| Main Canvas | `frontend/src/components/canvas/AtomizerCanvas.tsx` | COMPLETE |
### Node Types (8)
| Node | Icon | Color | Status |
|------|------|-------|--------|
| Model | `Cube` | Blue | COMPLETE |
| Solver | `Cpu` | Violet | COMPLETE |
| Design Variable | `SlidersHorizontal` | Emerald | COMPLETE |
| Extractor | `FlaskConical` | Cyan | COMPLETE |
| Objective | `Target` | Rose | COMPLETE |
| Constraint | `ShieldAlert` | Amber | COMPLETE |
| Algorithm | `BrainCircuit` | Indigo | COMPLETE |
| Surrogate | `Rocket` | Pink | COMPLETE |
### Panels
| Panel | Purpose | Status |
|-------|---------|--------|
| NodeConfigPanel | Configure selected node | COMPLETE |
| ValidationPanel | Display validation errors | COMPLETE |
| ExecuteDialog | Confirm study creation | COMPLETE |
| ChatPanel | Claude chat sidebar | COMPLETE |
| ConfigImporter | Load from study/JSON | COMPLETE |
| TemplateSelector | Choose workflow template | COMPLETE |
---
## Phase 2: LLM Intelligence Layer - COMPLETE
### Canvas MCP Tools
| Tool | Purpose | Status |
|------|---------|--------|
| `validate_canvas_intent` | Validate graph before execution | COMPLETE |
| `execute_canvas_intent` | Create study + optionally run | COMPLETE |
| `interpret_canvas_intent` | Get recommendations | COMPLETE |
### Canvas Chat Hook
| Hook | File | Status |
|------|------|--------|
| `useCanvasChat` | `frontend/src/hooks/useCanvasChat.ts` | COMPLETE |
Features:
- **File watching** using `watchdog` library
- Monitors `optimization_history_incremental.json` for changes
- Monitors `pruning_history.json` for pruned trials
- **Automatic broadcasting** to all connected clients
- **Connection management** (starts/stops observers automatically)
Message types:
- `connected` - Initial connection confirmation
- `trial_completed` - New trial finished
- `new_best` - New best trial found
- `progress` - Progress updates (current/total trials)
- `trial_pruned` - Trial pruned (with diagnostics)
### ✅ Documentation
- **Backend README**: [atomizer-dashboard/backend/README.md](../atomizer-dashboard/backend/README.md)
- API usage examples
- WebSocket message protocol
- Testing instructions
- `processWithClaude(intent)` - Full processing with study creation
- `validateWithClaude(intent)` - Validation only
- `analyzeWithClaude(intent)` - Get recommendations
---
## ✅ Completed: Enhanced Live Dashboard (Phase 4)
## Phase 3: Bidirectional Sync - COMPLETE
### Live Dashboard Features (dashboard-enhanced.html)
**Location**: [atomizer-dashboard/dashboard-enhanced.html](../atomizer-dashboard/dashboard-enhanced.html)
Fully functional live dashboard with:
- ✅ **Real-time WebSocket streaming** - Instant updates on new trials
- ✅ **Study discovery** - Auto-detects all active studies
- ✅ **Interactive charts** (Chart.js v4.4.0):
- Convergence plot (objective value + "best so far" trajectory)
- Parameter space scatter plot (2D visualization of design variables)
- ✅ **Pruning alerts** - Toast notifications for pruned trials
- ✅ **Data export** - Download trial history as JSON or CSV
- ✅ **Metric dashboard** - Total trials, best value, average, pruned count
- ✅ **Live trial feed** - Last 20 trials with animations
- ✅ **Connection monitoring** - WebSocket status indicator
- ✅ **Alert system** - Success/warning notifications with auto-dismiss
**Access**: http://localhost:8000 (after starting backend)
| Feature | Status |
|---------|--------|
| Session persistence (SQLite) | COMPLETE |
| Context builder | COMPLETE |
| Canvas to Chat bridge | COMPLETE |
| Study context loading | COMPLETE |
---
## Pending: Full React Frontend (Phase 2)
## Phase 4: Templates & Polish - COMPLETE
### Next Phase Tasks
### Templates
#### High Priority
1. **Initialize React + Vite + TypeScript project**
2. **Set up TailwindCSS for styling**
3. **Create WebSocket connection hook** (`useWebSocket.ts`)
4. **Build Dashboard page component** (`Dashboard.tsx`)
5. **Migrate charts to Recharts** (React-compatible charting library)
6. **Add parameter importance chart** (Protocol 9 data)
7. **Add control panel** (start/stop/pause buttons - future)
| Template | Description | Complexity |
|----------|-------------|------------|
| Mass Minimization | Single-objective mass reduction | Simple |
| Multi-Objective | Mass + displacement Pareto | Medium |
| Turbo Mode | Neural-accelerated | Advanced |
| Mirror WFE | Zernike optimization | Advanced |
| Frequency Target | Modal analysis | Medium |
#### Medium Priority
8. **Create study list view**
9. **Add routing** (React Router)
10. **Build Study Configurator page**
11. **Build Results Viewer page**
### UI Features
| Feature | Status |
|---------|--------|
| Lucide icons (no emojis) | COMPLETE |
| Dark theme (Atomaster) | COMPLETE |
| Responsive layout | COMPLETE |
| Full-screen canvas | COMPLETE |
| Floating action buttons | COMPLETE |
---
## Testing Plan
## Canvas V3 Upgrade - COMPLETE
### Backend Testing
All Canvas V2 and V3 features have been implemented:
| Feature | Status |
|---------|--------|
| Professional Lucide icons | COMPLETE |
| Responsive full-screen layout | COMPLETE |
| Auto-load from optimization_config.json | COMPLETE |
| NX model introspection endpoint | COMPLETE |
| Expression search dropdown | COMPLETE |
| "Process with Claude" button | COMPLETE |
| MCP canvas tools | COMPLETE |
| Backend study list endpoint | COMPLETE |
| File browser for model selection | COMPLETE |
| Introspection panel (expressions, extractors) | COMPLETE |
| Claude WebSocket fixes | COMPLETE |
| Health check endpoint | COMPLETE |
---
## File Inventory
### MCP Server (`mcp-server/atomizer-tools/`)
```
src/
├── index.ts # Server entry (imports canvasTools)
├── tools/
│ ├── study.ts # Study management
│ ├── optimization.ts # Optimization control
│ ├── analysis.ts # Analysis tools
│ ├── reporting.ts # Report generation
│ ├── physics.ts # Physics explanations
│ ├── canvas.ts # Canvas intent tools
│ └── admin.ts # Power mode tools
└── utils/
└── paths.ts # Path utilities
```
### Backend Services (`atomizer-dashboard/backend/api/services/`)
```
__init__.py
claude_agent.py # Full Claude API integration (722 lines)
claude_cli_agent.py # CLI-based agent (202 lines)
conversation_store.py # SQLite persistence (295 lines)
session_manager.py # Session lifecycle (425 lines)
context_builder.py # Context assembly (246 lines)
nx_introspection.py # NX model introspection (NEW)
```
### Backend Routes (`atomizer-dashboard/backend/api/routes/`)
```
__init__.py
terminal.py # Claude WebSocket endpoint
optimization.py # Optimization API
studies.py # Study configuration
files.py # File browser API (NEW)
nx.py # NX introspection API (NEW)
```
### Frontend Canvas (`atomizer-dashboard/frontend/src/components/canvas/`)
```
AtomizerCanvas.tsx # Main canvas component
nodes/
├── index.ts # Node type registry
├── BaseNode.tsx # Base with multiple handles
├── ModelNode.tsx
├── SolverNode.tsx
├── DesignVarNode.tsx
├── ExtractorNode.tsx
├── ObjectiveNode.tsx
├── ConstraintNode.tsx
├── AlgorithmNode.tsx
└── SurrogateNode.tsx
panels/
├── NodeConfigPanel.tsx # Node configuration sidebar
├── ValidationPanel.tsx # Validation toast display
├── ExecuteDialog.tsx # Execute confirmation modal
├── ChatPanel.tsx # Claude chat sidebar
├── ConfigImporter.tsx # Study import dialog
├── TemplateSelector.tsx # Workflow template chooser
├── FileBrowser.tsx # File picker for model selection (NEW)
├── IntrospectionPanel.tsx # Model introspection results (NEW)
└── ExpressionSelector.tsx # Expression search dropdown (NEW)
palette/
└── NodePalette.tsx
```
### Canvas Library (`atomizer-dashboard/frontend/src/lib/canvas/`)
```
schema.ts # Type definitions
intent.ts # Serialization (174 lines)
validation.ts # Graph validation
templates.ts # Workflow templates
index.ts # Exports
```
---
## Testing Checklist
### Build Verification
#### Manual Test: REST API
```bash
# Start backend
cd atomizer-dashboard/backend
python -m uvicorn api.main:app --reload
# Build MCP server
cd mcp-server/atomizer-tools
npm run build
# Expected: Compiles without errors
# Test endpoints
curl http://localhost:8000/
curl http://localhost:8000/api/optimization/studies
curl http://localhost:8000/api/optimization/studies/circular_plate_frequency_tuning/status
# Build frontend
cd atomizer-dashboard/frontend
npm run build
# Expected: Compiles without errors
```
#### Manual Test: WebSocket
```bash
# Install wscat
npm install -g wscat
### Functional Testing
# Connect to WebSocket
wscat -c ws://localhost:8000/api/ws/optimization/circular_plate_frequency_tuning
# Or use Python
python -c "
import asyncio
import websockets
import json
async def test():
uri = 'ws://localhost:8000/api/ws/optimization/circular_plate_frequency_tuning'
async with websockets.connect(uri) as ws:
while True:
msg = await ws.recv()
print(json.loads(msg))
asyncio.run(test())
"
```
### Frontend Testing (Once Built)
1. **Unit tests**: React Testing Library
2. **Integration tests**: WebSocket mock server
3. **E2E tests**: Cypress with running optimization
---
## Architecture Summary
### Backend Stack
- **FastAPI** - Async Python web framework
- **Uvicorn** - ASGI server
- **Watchdog** - File system monitoring
- **WebSockets** - Real-time communication
### Frontend Stack (Planned)
- **React 18** - UI framework
- **Vite** - Build tool
- **TypeScript** - Type safety
- **TailwindCSS** - Styling
- **Recharts** - Interactive charts
- **React Query** - Server state management
### Communication Flow
```
optimization_history_incremental.json (file modified)
↓
Watchdog Observer
↓
OptimizationFileHandler
↓
WebSocket Broadcast
↓
Connected Clients (Frontend)
↓
React State Update
↓
UI Re-render (charts, tables)
```
---
## Next Steps
### Completed (This Session)
1. ✅ Backend complete (FastAPI + WebSocket + file watching)
2. ✅ Enhanced live dashboard (charts, pruning alerts, data export)
3. ✅ Real-time updates working end-to-end
4. ✅ Data export functionality (JSON/CSV)
### Short Term (Next Session)
5. Build full React + Vite + TypeScript frontend
6. Migrate to Recharts for React-compatible charts
7. Add parameter importance visualization
8. Build Study Configurator page
9. Build Results Viewer page
### Medium Term
9. Build Study Configurator page
10. Build Results Viewer page
11. Add LLM chat interface (future)
---
## File Structure (Current)
```
atomizer-dashboard/
├── backend/ ✅ COMPLETE
│ ├── api/
│ │ ├── main.py # FastAPI app
│ │ ├── routes/
│ │ │ ├── __init__.py
│ │ │ └── optimization.py # REST endpoints
│ │ └── websocket/
│ │ ├── __init__.py
│ │ └── optimization_stream.py # WebSocket + file watching
│ ├── requirements.txt
│ └── README.md
│
├── dashboard-test.html ✅ Basic live dashboard
├── dashboard-enhanced.html ✅ Enhanced with charts & export
│
└── frontend/ ⏳ PLANNED (React app)
└── (to be created in next phase)
```
---
## Known Issues / Limitations
### Backend
1. **Process management**: No start/stop optimization control yet (future enhancement)
2. **Authentication**: No auth layer (planned for future phase)
3. **Error handling**: Basic error handling, could be improved
4. **Testing**: No automated tests yet
### Frontend
- Not yet started
---
## Performance Considerations
### Backend
- **File watching overhead**: Minimal (~1ms per event)
- **WebSocket latency**: <100ms typical
- **Concurrent connections**: Tested with up to 10 clients per study
- **Memory**: ~50MB per active observer
### Expected Frontend Performance
- **Initial load**: <2s
- **WebSocket message handling**: <50ms
- **Chart re-render**: <100ms (with React.memo optimization)
- [ ] Navigate to `/canvas`
- [ ] Drag nodes from palette
- [ ] Connect nodes with edges
- [ ] Configure node properties
- [ ] Click "Validate"
- [ ] Click "Process with Claude"
- [ ] Chat panel responds
- [ ] Import from existing study
- [ ] Select workflow template
- [ ] Expression dropdown works
---
## References
- [Master Plan](DASHBOARD_MASTER_PLAN.md) - Complete architecture and roadmap
- [Backend README](../atomizer-dashboard/backend/README.md) - API documentation
- [Session Summary Nov 20](SESSION_SUMMARY_NOV20.md) - Previous work on optimization engine
- [Pruning Diagnostics](PRUNING_DIAGNOSTICS.md) - Data available for display
- [Canvas Documentation](CANVAS.md) - Full Canvas Builder guide
- [Dashboard Overview](DASHBOARD.md) - Main dashboard documentation
- [RALPH_LOOP_CANVAS_V2](../plans/RALPH_LOOP_CANVAS_V2.md) - V2 upgrade prompt
---
## Testing Instructions
### Start the Dashboard
```bash
# Terminal 1: Start backend
cd atomizer-dashboard/backend
python -m uvicorn api.main:app --reload --host 0.0.0.0 --port 8000
# Terminal 2: Start an optimization (if needed)
cd ../..
python studies/circular_plate_frequency_tuning/run_optimization.py
# Access dashboard at: http://localhost:8000
```
### Features to Test
1. **Study Discovery**: Dashboard should auto-load all active studies
2. **Study Selection**: Click a study in left sidebar to connect
3. **Real-time Updates**: New trials appear instantly (watch for animation)
4. **Charts**: Convergence and parameter space plots update in real-time
5. **Pruning Alerts**: Orange toast notification when trial is pruned
6. **Data Export**: Click "Export JSON" or "Export CSV" buttons
7. **WebSocket Log**: Check bottom panel for connection events
---
**Status**: ✅ Enhanced live dashboard complete and functional. Ready for React frontend development.
*Implementation completed via autonomous Claude Code sessions.*

2815
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312
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@@ -0,0 +1,312 @@
# Canvas Deep Fix Investigation
**Date**: January 16, 2026
**Status**: ✅ IMPLEMENTATION COMPLETE
---
## Executive Summary
Four critical issues have been identified that are blocking Canvas functionality:
| # | Issue | Root Cause | Severity |
|---|-------|------------|----------|
| 1 | Claude Chat Not Working | `asyncio.create_subprocess_exec` fails on Windows | CRITICAL |
| 2 | Expressions Can't Connect to Model | ModelNode has `inputs={0}` - no input handle | CRITICAL |
| 3 | File Browser Only Shows Studies | Web API can't access OS file system | HIGH |
| 4 | Introspection is Fake | Only reads config files, not actual NX models | HIGH |
---
## Issue 1: Claude Chat NotImplementedError
### Root Cause
```python
# session_manager.py line 138
process = await asyncio.create_subprocess_exec(...)
```
On Windows, `asyncio.create_subprocess_exec` raises `NotImplementedError` because Windows doesn't support the ProactorEventLoop subprocess methods the same way Unix does.
### Evidence
```
Traceback:
File "session_manager.py", line 138, in create_session
process = await asyncio.create_subprocess_exec(
File "asyncio\subprocess.py", line 218, in create_subprocess_exec
File "asyncio\base_events.py", line 498, in _make_subprocess_transport
raise NotImplementedError
NotImplementedError
```
### Solution
Replace async subprocess with synchronous subprocess + ThreadPoolExecutor:
```python
import subprocess
from concurrent.futures import ThreadPoolExecutor
executor = ThreadPoolExecutor(max_workers=4)
async def create_session(...):
# Instead of asyncio.create_subprocess_exec
loop = asyncio.get_event_loop()
process = await loop.run_in_executor(
executor,
lambda: subprocess.Popen(
["claude", "--print", ...],
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
cwd=str(ATOMIZER_ROOT),
)
)
```
**OR** - Simpler approach: Skip session-based subprocess entirely, use HTTP streaming for chat:
The `/api/claude/chat/stream` endpoint already works (it uses `claude_cli_agent.py` which runs Claude one-shot). The WebSocket session approach is over-engineered for the use case.
### Fix Strategy
1. Make `create_session` return a "virtual" session (no subprocess)
2. Route all messages through HTTP streaming endpoint
3. Keep conversation history in `ConversationStore` database
4. WebSocket just wraps the HTTP streaming calls
---
## Issue 2: Expressions Can't Connect to Model
### Root Cause
**ModelNode.tsx:**
```tsx
<BaseNode {...props} icon={...} iconColor="text-blue-400" inputs={0}>
```
`inputs={0}` means Model has **NO input handle** - nothing can connect TO it!
**DesignVarNode.tsx:**
```tsx
<BaseNode {...props} icon={...} iconColor="text-emerald-400">
```
Uses defaults (`inputs=1, outputs=1`) but DesignVar should have:
- `inputs=0` (it's a source node)
- `outputs=1` (connects to Model)
### Visual Problem
```
Current (WRONG):
DesignVar ←─ Model ──→ Solver
↑ ↓
(has input) (has output only)
Should be:
DesignVar ──→ Model ──→ Solver
↓ ↑↓
(output) (input & output)
```
### Fix Required
**ModelNode.tsx** - Add input handle:
```tsx
<BaseNode {...props} icon={...} iconColor="text-blue-400" inputs={1} outputs={1}>
```
**DesignVarNode.tsx** - Remove input handle:
```tsx
<BaseNode {...props} icon={...} iconColor="text-emerald-400" inputs={0} outputs={1}>
```
**SurrogateNode.tsx** - Should be terminal (no output):
```tsx
<BaseNode {...props} icon={...} iconColor="text-pink-400" inputs={1} outputs={0}>
```
---
## Issue 3: File Browser Only Shows Studies Folder
### Root Cause
The current `FileBrowser.tsx` uses fetch to `/api/files/list` which only lists files within the `studies/` directory. The user wants:
1. Native OS file picker to select files from ANYWHERE
2. Import selected files into the study folder
3. Copy all related files (.prt, .sim, .fem, _i.prt, etc.)
### Web Browser Limitation
Browsers can't access the local file system directly for security. Options:
**Option A: File System Access API** (Chrome/Edge only)
```typescript
const handle = await window.showOpenFilePicker({
types: [{ description: 'NX Files', accept: { '*/*': ['.sim', '.prt', '.fem'] } }]
});
const file = await handle.getFile();
// Upload to backend
```
**Option B: Traditional File Input**
```tsx
<input type="file" accept=".sim,.prt,.fem,.afem" onChange={handleFileUpload} />
```
Then upload to backend which saves to study folder.
**Option C: Backend Path Input + Validation**
User enters full Windows path (e.g., `C:\NX_Models\bracket.prt`), backend validates and copies.
### Recommended Solution
Combine B + C:
1. File input for direct upload (drag & drop)
2. Path input for network drives/existing paths
3. Backend endpoint to copy/import files
---
## Issue 4: Introspection is Fake
### Root Cause
Current `nx_introspection.py` does NOT actually read NX files. It only:
- Reads `optimization_config.json` for existing design variables
- Infers expressions based on folder names ("mirror" → suggest mirror expressions)
- Guesses solver type from file names
### What Real Introspection Needs
**For .prt files (NX Part):**
- Use NX Open API to read expressions
- Get expression names, values, units, formulas
- Requires NX to be installed and licensed
**For .sim files (Simulation):**
- Parse XML-like structure or use NX Open
- Get solver type, boundary conditions, loads
- Identify linked .fem and .prt files
**For .fem files (FEM):**
- Get mesh statistics (nodes, elements)
- Material properties
- Element types used
**For .op2 files (Results):**
- Use PyNastran to read binary results
- Extract displacement, stress, frequency data
- Get node/element IDs for specific extractions
### Implementation Approach
**Phase 1: File Discovery (no NX needed)**
```python
def discover_related_files(sim_path: Path) -> List[Dict]:
"""Find all related files by naming convention"""
# model_sim1.sim → model.prt, model_fem1.fem, model_fem1_i.prt
```
**Phase 2: Config-based Expression Discovery**
```python
def discover_expressions_from_config(study_dir: Path) -> List[Dict]:
"""Read optimization_config.json for design variables"""
```
**Phase 3: NX Open Integration (requires NX)**
```python
def introspect_with_nx_open(prt_path: Path) -> Dict:
"""Use NX Open API to read actual expressions"""
# This requires NX to be running
# Use the existing nx_journals/ infrastructure
```
**Phase 4: OP2 Result Analysis (PyNastran)**
```python
def analyze_op2_results(op2_path: Path) -> Dict:
"""Read OP2 file to discover available result types"""
from pyNastran.op2.op2 import OP2
op2 = OP2()
op2.read_op2(str(op2_path))
# Return available subcases, result types, etc.
```
---
## Implementation Plan
### Phase 1: Fix Claude Chat (CRITICAL - 30 min)
1. Modify `create_session` to not spawn subprocess
2. Keep session metadata in database only
3. Route all messages through HTTP streaming
4. WebSocket wraps HTTP calls
### Phase 2: Fix Node Handles (CRITICAL - 15 min)
1. Update `ModelNode.tsx`: `inputs={1}`
2. Update `DesignVarNode.tsx`: `inputs={0}, outputs={1}`
3. Update `SurrogateNode.tsx`: `outputs={0}`
4. Test connections work correctly
### Phase 3: Native File Import (HIGH - 45 min)
1. Add file upload input to FileBrowser
2. Create backend `/api/files/upload` endpoint
3. Add path input with validation
4. Create `/api/files/import` for path-based import
5. Copy all related files to study folder
### Phase 4: Real Introspection Service (HIGH - 2 hours)
1. File discovery by naming convention
2. OP2 analysis with PyNastran
3. NX Open integration (optional, requires NX running)
4. Return comprehensive file metadata
### Phase 5: Integration Testing (30 min)
1. Test complete workflow: Select model → Introspect → Add Design Vars → Connect → Execute
2. Fix any remaining issues
---
## Files to Modify
### Backend
- `session_manager.py` - Fix Windows subprocess issue
- `files.py` - Add upload/import endpoints
- `nx_introspection.py` - Real introspection logic
### Frontend
- `ModelNode.tsx` - Add input handle
- `DesignVarNode.tsx` - Remove input, keep output
- `SurrogateNode.tsx` - Remove output
- `FileBrowser.tsx` - Add file upload, path input
- `IntrospectionPanel.tsx` - Display real introspection data
---
## Estimated Total Time: 4-5 hours
---
## Implementation Summary (Completed)
### Phase 1: Claude Chat Windows Fix ✅
**File**: `atomizer-dashboard/backend/api/services/session_manager.py`
- Replaced `asyncio.create_subprocess_exec` with `subprocess.Popen`
- Used `ThreadPoolExecutor` with `run_in_executor()` for async compatibility
- Made sessions stateless (no persistent subprocess)
- Each message handled via one-shot CLI call with 5-minute timeout
### Phase 2: Node Handles ✅
**Files**:
- `ModelNode.tsx`: Changed `inputs={0}` to `inputs={1}` (now accepts connections)
- `DesignVarNode.tsx`: Added `inputs={0} outputs={1}` (source node)
### Phase 3: Native File Import ✅
**Files**:
- `files.py`: Added `/validate-path`, `/import-from-path`, `/upload` endpoints
- `FileBrowser.tsx`: Complete rewrite with 3 tabs:
- Browse Studies (existing)
- Import Path (paste Windows path, validate, import related files)
- Upload Files (drag & drop)
### Phase 4: Real NX Introspection ✅
**File**: `atomizer-dashboard/backend/api/services/nx_introspection.py`
- Added PyNastran OP2 parsing (displacements, eigenvectors, stress)
- BDF/DAT file analysis (mass, grid count, element counts, solver type)
- Study database queries for expression discovery
- Related file discovery by naming convention
- Result file discovery with trial folder detection

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# RALPH LOOP: Canvas-Study Synchronization Overhaul
**Date**: January 16, 2026
**Status**: 🟢 COMPLETED
**Priority**: CRITICAL
**Completion Date**: January 16, 2026
---
## Executive Summary
The Canvas Builder and actual optimization studies are fundamentally disconnected. When a user loads a study, the canvas doesn't reflect the true optimization pipeline. Claude chat has zero awareness of the canvas state, making it useless for canvas-based interactions.
---
## Part 1: Problem Analysis
### 1.1 Core Issues Identified
| # | Issue | Severity | Impact |
|---|-------|----------|--------|
| 1 | **Canvas doesn't match optimization_config.json schema** | CRITICAL | Canvas nodes don't represent actual extractors, objectives, constraints |
| 2 | **Missing data flow representation** | CRITICAL | No visualization of: displacement → Zernike → WFE pipeline |
| 3 | **Claude has no canvas context** | CRITICAL | Can't help modify canvas because it doesn't know current state |
| 4 | **Study loader is incomplete** | HIGH | Loading a study doesn't populate all nodes correctly |
| 5 | **Canvas exporter is broken/missing** | HIGH | Can't generate valid optimization_config.json from canvas |
| 6 | **No extractor node types** | HIGH | E1-E10 extractors not represented as proper nodes |
| 7 | **No output/result node types** | MEDIUM | Missing nodes for WFE, mass, stress outputs |
| 8 | **No validation against real schema** | MEDIUM | Canvas allows invalid configurations |
### 1.2 Real M1 Mirror Optimization Pipeline (What Canvas Should Show)
```
┌─────────────────────────────────────────────────────────────────────────────┐
│ M1 MIRROR OPTIMIZATION │
├─────────────────────────────────────────────────────────────────────────────┤
│ │
│ INPUTS (Design Variables) │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ flatback_ │ │ rib_height │ │ rib_width │ │ fillet_ │ │
│ │ thickness │ │ [25-60mm] │ │ [4-12mm] │ │ radius │ │
│ │ [15-45mm] │ │ │ │ │ │ [2-10mm] │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │ │
│ └────────────────┴────────────────┴────────────────┘ │
│ │ │
│ ▼ │
│ MODEL + SOLVER │
│ ┌─────────────────────────────────────────────────────────────┐ │
│ │ m1_mirror_sim1.sim → NX Nastran SOL101 (Static) │ │
│ │ Updates: geometry.prt → idealized_i.prt → fem1.fem │ │
│ └─────────────────────────────────────────────────────────────┘ │
│ │ │
│ ▼ │
│ EXTRACTORS (Post-Processing) │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ E5: CAD Mass │ │ E8: Zernike │ │ E1: Max Disp │ │ E3: Max │ │
│ │ (expression) │ │ from OP2 │ │ (optional) │ │ Stress │ │
│ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ └──────┬───────┘ │
│ │ │ │ │ │
│ │ ▼ │ │ │
│ │ ┌───────────────────────┐ │ │ │
│ │ │ Zernike Processing │ │ │ │
│ │ │ - Fit coefficients │ │ │ │
│ │ │ - Calculate WFE_40_20 │ │ │ │
│ │ │ - Calculate RMS │ │ │ │
│ │ └───────────┬───────────┘ │ │ │
│ │ │ │ │ │
│ ▼ ▼ ▼ ▼ │
│ OBJECTIVES & CONSTRAINTS │
│ ┌──────────────┐ ┌──────────────┐ ┌──────────────┐ │
│ │ MINIMIZE │ │ MINIMIZE │ │ CONSTRAINT │ │
│ │ mass_kg │ │ wfe_40_20 │ │ stress < 200 │ │
│ │ weight: 1.0 │ │ weight: 10.0 │ │ MPa │ │
│ └──────────────┘ └──────────────┘ └──────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────────┘
```
### 1.3 What optimization_config.json Actually Contains
```json
{
"study_name": "m1_mirror_flatback_lateral",
"description": "M1 Mirror optimization",
"design_variables": [
{"name": "flatback_thickness", "min": 15, "max": 45, "unit": "mm"},
{"name": "rib_height", "min": 25, "max": 60, "unit": "mm"},
{"name": "rib_width", "min": 4, "max": 12, "unit": "mm"},
{"name": "fillet_radius", "min": 2, "max": 10, "unit": "mm"}
],
"model": {
"sim_file": "1_model/m1_mirror_sim1.sim",
"prt_file": "1_model/m1_mirror.prt",
"fem_file": "1_model/m1_mirror_fem1.fem",
"idealized_file": "1_model/m1_mirror_fem1_i.prt"
},
"solver": {
"type": "SOL101",
"timeout_minutes": 30
},
"extractors": [
{
"id": "E5",
"name": "mass_extractor",
"type": "cad_mass",
"expression_name": "total_mass",
"output_name": "mass_kg"
},
{
"id": "E8",
"name": "zernike_extractor",
"type": "zernike_op2",
"subcase": 1,
"node_set": "mirror_surface",
"terms": [40, 20],
"output_name": "wfe_40_20"
}
],
"objectives": [
{"name": "mass_kg", "direction": "minimize", "weight": 1.0},
{"name": "wfe_40_20", "direction": "minimize", "weight": 10.0}
],
"constraints": [
{"name": "max_stress", "operator": "<=", "value": 200, "unit": "MPa"}
],
"algorithm": {
"method": "NSGA-II",
"max_trials": 200,
"population_size": 40
}
}
```
### 1.4 Current Canvas Schema (INCOMPLETE)
The current canvas has these node types:
- `model` - File path only, no solver integration
- `solver` - Just solver type, no connection to model
- `designVar` - Expression name and bounds only
- `algorithm` - Method and max trials
- `extractor` - Just extractor ID, no configuration
- `objective` - Name, direction, weight
- `constraint` - Name, operator, value
- `surrogate` - Neural surrogate toggle
**MISSING:**
- Proper extractor configuration (subcase, node set, terms)
- Data flow connections (extractor output → objective input)
- Model file relationships (sim → fem → prt → idealized)
- Zernike-specific processing nodes
- Output mapping (which extractor feeds which objective)
---
## Part 2: Claude Context Problem
### 2.1 Current State
When user opens canvas and chats with Claude:
1. Claude receives NO information about:
- Current canvas nodes
- Current canvas edges (connections)
- Current study context
- Current configuration state
2. Claude can only:
- Answer generic questions
- Use MCP tools for study queries
- NOT modify the canvas directly
### 2.2 Required Claude Capabilities
Claude needs to:
1. **See current canvas state** - All nodes, edges, configurations
2. **Modify canvas** - Add/remove/update nodes via API
3. **Validate changes** - Check if configuration is valid
4. **Generate config** - Export canvas to optimization_config.json
5. **Load studies** - Import optimization_config.json to canvas
---
## Part 3: Solution Architecture
### 3.1 Enhanced Canvas Schema
```typescript
// New comprehensive node types
type NodeType =
| 'model' // NX model with all file references
| 'solver' // Solver configuration
| 'designVar' // Design variable (expression)
| 'extractor' // Physics extractor with full config
| 'processor' // Data processor (Zernike fitting, etc.)
| 'objective' // Optimization objective
| 'constraint' // Constraint definition
| 'algorithm' // Optimization algorithm
| 'surrogate' // Neural surrogate
| 'output' // Final output metric
// Enhanced extractor node
interface ExtractorNodeData {
type: 'extractor';
extractorId: 'E1' | 'E2' | 'E3' | 'E4' | 'E5' | 'E8' | 'E9' | 'E10';
extractorName: string;
// E1/E3 specific
subcase?: number;
nodeId?: number;
elementId?: number;
// E8 Zernike specific
zernikeTerms?: number[];
nodeSet?: string;
referenceRadius?: number;
// E5 Mass specific
expressionName?: string;
// Output mapping
outputName: string; // Name of the output variable
}
// Enhanced model node
interface ModelNodeData {
type: 'model';
simFile: string;
prtFile: string;
femFile: string;
idealizedFile?: string;
// Discovered info
expressions?: Array<{name: string; value: number; unit: string}>;
meshInfo?: {nodes: number; elements: number};
}
// Data processor node (for Zernike fitting, etc.)
interface ProcessorNodeData {
type: 'processor';
processorType: 'zernike_fit' | 'relative_calc' | 'rms_calc' | 'custom';
// Inputs (connected from extractors)
inputMapping: Record<string, string>;
// Processing config
config: Record<string, any>;
// Outputs
outputNames: string[];
}
```
### 3.2 Canvas-Config Synchronization
```typescript
// Canvas State Manager - shared between frontend and Claude
class CanvasStateManager {
// Current state
nodes: CanvasNode[];
edges: CanvasEdge[];
studyId: string | null;
// Load from optimization_config.json
async loadFromConfig(configPath: string): Promise<void>;
// Export to optimization_config.json
async exportToConfig(): Promise<OptimizationConfig>;
// Validation
validate(): ValidationResult;
// Claude API
toClaudeContext(): string; // Markdown summary for Claude
// Modification API (for Claude)
addNode(type: NodeType, data: NodeData): string;
updateNode(nodeId: string, data: Partial<NodeData>): void;
removeNode(nodeId: string): void;
addEdge(source: string, target: string): string;
removeEdge(edgeId: string): void;
}
```
### 3.3 Claude Context Injection
When Claude receives a message in canvas mode:
```markdown
## Current Canvas State
**Study**: m1_mirror_flatback_lateral
**Status**: Configured (valid)
### Design Variables (4)
| Name | Min | Max | Unit |
|------|-----|-----|------|
| flatback_thickness | 15 | 45 | mm |
| rib_height | 25 | 60 | mm |
| rib_width | 4 | 12 | mm |
| fillet_radius | 2 | 10 | mm |
### Model
- **Sim File**: 1_model/m1_mirror_sim1.sim
- **Solver**: SOL101 (Static)
### Extractors (2)
1. E5: CAD Mass → mass_kg
2. E8: Zernike OP2 → wfe_40_20 (terms: 40, 20)
### Objectives (2)
1. MINIMIZE mass_kg (weight: 1.0)
2. MINIMIZE wfe_40_20 (weight: 10.0)
### Constraints (1)
1. max_stress <= 200 MPa
### Algorithm
- Method: NSGA-II
- Max Trials: 200
---
User can ask to modify any of the above. Use canvas_* tools to make changes.
```
### 3.4 New MCP Tools for Canvas
```typescript
// New tools Claude can use
const canvasTools = {
// Read current state
canvas_get_state: () => CanvasState,
// Modify nodes
canvas_add_design_var: (name: string, min: number, max: number, unit: string) => NodeId,
canvas_update_design_var: (nodeId: string, updates: Partial<DesignVarData>) => void,
canvas_remove_node: (nodeId: string) => void,
// Add extractors
canvas_add_extractor: (type: ExtractorType, config: ExtractorConfig) => NodeId,
// Add objectives/constraints
canvas_add_objective: (name: string, direction: 'minimize' | 'maximize', weight: number) => NodeId,
canvas_add_constraint: (name: string, operator: string, value: number) => NodeId,
// Connections
canvas_connect: (sourceId: string, targetId: string) => EdgeId,
canvas_disconnect: (edgeId: string) => void,
// Validation & Export
canvas_validate: () => ValidationResult,
canvas_export_config: () => OptimizationConfig,
canvas_apply_to_study: (studyPath: string) => void,
};
```
---
## Part 4: Implementation Plan
### Phase 1: Schema & Store Enhancement (Priority: CRITICAL)
**Files to modify:**
- `frontend/src/lib/canvas/schema.ts` - Enhanced node types
- `frontend/src/hooks/useCanvasStore.ts` - State management
- `frontend/src/lib/canvas/configSync.ts` - NEW: Config sync utilities
**Tasks:**
- [ ] Define complete ExtractorNodeData with all E1-E10 configs
- [ ] Define ProcessorNodeData for Zernike processing
- [ ] Define complete ModelNodeData with all file references
- [ ] Add output mapping to all extractors
- [ ] Create validation functions
### Phase 2: Study Loader Enhancement (Priority: CRITICAL)
**Files to modify:**
- `frontend/src/lib/canvas/studyLoader.ts` - NEW: Full study loading
- `backend/api/routes/canvas.py` - NEW: Canvas API endpoints
**Tasks:**
- [ ] Parse optimization_config.json completely
- [ ] Create nodes for ALL config elements
- [ ] Create edges for data flow
- [ ] Handle Zernike-specific extractors
- [ ] Handle nested processor configurations
### Phase 3: Canvas Exporter (Priority: HIGH)
**Files to create:**
- `frontend/src/lib/canvas/configExporter.ts` - Export to config
- `backend/api/routes/canvas.py` - Save config endpoint
**Tasks:**
- [ ] Convert canvas nodes to optimization_config.json
- [ ] Validate exported config
- [ ] Handle edge-to-dependency mapping
- [ ] Write to study folder
### Phase 4: Claude Context Integration (Priority: CRITICAL)
**Files to modify:**
- `backend/api/services/context_builder.py` - Add canvas context
- `backend/api/routes/claude.py` - Include canvas state in prompt
- `frontend/src/components/chat/ChatPanel.tsx` - Send canvas state
**Tasks:**
- [ ] Generate markdown summary of canvas state
- [ ] Include in every Claude message
- [ ] Update context on canvas changes
- [ ] Add canvas modification instructions
### Phase 5: MCP Canvas Tools (Priority: HIGH)
**Files to create:**
- `mcp-server/atomizer-tools/src/canvas-tools.ts` - Canvas modification tools
**Tasks:**
- [ ] Implement canvas_get_state
- [ ] Implement canvas_add_* tools
- [ ] Implement canvas_update_* tools
- [ ] Implement canvas_remove_node
- [ ] Implement canvas_connect/disconnect
- [ ] Implement canvas_validate
- [ ] Implement canvas_export_config
### Phase 6: UI Node Enhancements (Priority: MEDIUM)
**Files to modify:**
- `frontend/src/components/canvas/nodes/ExtractorNode.tsx` - Full config display
- `frontend/src/components/canvas/panels/NodeConfigPanel.tsx` - All config options
**Tasks:**
- [ ] Show extractor configuration in node
- [ ] Show output mapping
- [ ] Show data flow direction
- [ ] Add quick-edit for common settings
---
## Part 5: Immediate Actions
### Action 1: Read actual optimization_config.json from M1 mirror
```bash
Read studies/M1_Mirror/m1_mirror_flatback_lateral/optimization_config.json
```
### Action 2: Read current run_optimization.py to understand pipeline
```bash
Read studies/M1_Mirror/m1_mirror_flatback_lateral/run_optimization.py
```
### Action 3: Compare with canvas schema
```bash
Read atomizer-dashboard/frontend/src/lib/canvas/schema.ts
```
### Action 4: Check current study loading logic
```bash
Find and read study loading code in useCanvasStore
```
### Action 5: Check Claude context builder
```bash
Read atomizer-dashboard/backend/api/services/context_builder.py
```
---
## Part 6: Success Criteria
1. **Loading M1 Mirror study shows ALL nodes**:
- 4 design variables with correct bounds
- Model node with all file references
- Solver node (SOL101)
- E5 Mass extractor with expression name
- E8 Zernike extractor with terms [40, 20]
- 2 objectives (mass, wfe)
- Proper edge connections
2. **Claude knows canvas state**:
- User says "add hole_diameter" → Claude immediately adds it
- No clarifying questions about which study
- Validates against current config
3. **Canvas exports valid config**:
- Click "Export" → generates optimization_config.json
- Config is valid and runnable
- Matches what run_optimization.py expects
4. **Bidirectional sync**:
- Edit canvas → config updates
- Edit config file → canvas updates (on reload)
---
## Tracking
| Phase | Status | Notes |
|-------|--------|-------|
| Phase 1: Schema | 🟢 COMPLETE | Enhanced ExtractorNodeData, DesignVarNodeData, AlgorithmNodeData with ZernikeConfig, baseline, penalty weights |
| Phase 2: Loader | 🟢 COMPLETE | Fixed OptimizationConfig to use min/max, added extraction_method, zernike_settings parsing |
| Phase 3: Exporter | 🟡 Partial | loadFromConfig now creates proper nodes from real configs |
| Phase 4: Claude Context | 🟢 COMPLETE | context_builder.py now has _canvas_context(), useChat passes canvas state |
| Phase 5: MCP Tools | 🟢 COMPLETE | Added canvas_add_node, canvas_update_node, canvas_remove_node, canvas_connect_nodes |
| Phase 6: UI | 🟡 Partial | useCanvasChat syncs canvas state, applyModification handles Claude responses |
---
## Implementation Summary
### Files Modified
**Frontend:**
- `src/lib/canvas/schema.ts` - Enhanced node data types (ZernikeConfig, baseline, penalty weights)
- `src/hooks/useCanvasStore.ts` - Fixed OptimizationConfig interface (min/max), enhanced loadFromConfig
- `src/hooks/useChat.ts` - Added CanvasState, updateCanvasState, passes canvas to backend
- `src/hooks/useCanvasChat.ts` - Syncs canvas state, applyModification for Claude modifications
**Backend:**
- `api/services/context_builder.py` - Added _canvas_context() method with full canvas serialization
- `api/services/session_manager.py` - send_message now accepts canvas_state parameter
- `api/routes/claude.py` - WebSocket handler accepts set_canvas messages, passes to session
**MCP Server:**
- `src/tools/canvas.ts` - Added canvas_add_node, canvas_update_node, canvas_remove_node, canvas_connect_nodes
### Key Changes
1. **Canvas-Config Interface Fixed**:
- Uses `min/max` instead of `lower/upper`
- Supports `extraction_method` and `zernike_settings`
- Handles `baseline`, `units`, `enabled`, `notes` for design vars
2. **Claude Context Injection**:
- Full canvas state passed with every message
- Tables for design vars, objectives, extractors
- Instructions for canvas modification tools
3. **Canvas Modification Tools**:
- Claude can add design variables with `canvas_add_node`
- Claude can update weights/bounds with `canvas_update_node`
- Frontend applies modifications via `applyModification()`
---
*Document completed January 16, 2026*

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# Atomizer Dashboard V2 - Implementation Status
**Last Updated:** January 14, 2026
**Status:** COMPLETE
---
## Implementation Audit Summary
All phases of the Atomizer Dashboard V2 have been implemented.
### Phase 0: MCP Chat Foundation - COMPLETE
| Component | Files | Lines | Status |
|-----------|-------|-------|--------|
| MCP Server | `mcp-server/atomizer-tools/src/` | 579+ | COMPLETE |
| Backend Services | `backend/api/services/` | 1,897 | COMPLETE |
| Frontend Chat | `frontend/src/components/chat/` | 6 files | COMPLETE |
**MCP Tools Implemented:**
- `list_studies` - List all studies
- `get_study_status` - Study details
- `create_study` - Create from description
- `run_optimization` - Start optimization
- `stop_optimization` - Stop optimization
- `get_trial_data` - Query trials
- `analyze_convergence` - Convergence metrics
- `compare_trials` - Side-by-side comparison
- `get_best_design` - Best design details
- `generate_report` - Markdown reports
- `export_data` - CSV/JSON export
- `explain_physics` - FEA concepts
- `recommend_method` - Algorithm recommendation
- `query_extractors` - Extractor list
### Phase 1: Canvas with React Flow - COMPLETE
| Component | Location | Status |
|-----------|----------|--------|
| Schema | `frontend/src/lib/canvas/schema.ts` | COMPLETE |
| Intent Serializer | `frontend/src/lib/canvas/intent.ts` | COMPLETE |
| Validation | `frontend/src/lib/canvas/validation.ts` | COMPLETE |
| Templates | `frontend/src/lib/canvas/templates.ts` | COMPLETE |
| Canvas Store | `frontend/src/hooks/useCanvasStore.ts` | COMPLETE |
| Main Canvas | `frontend/src/components/canvas/AtomizerCanvas.tsx` | COMPLETE |
**Node Types (8):**
- ModelNode, SolverNode, DesignVarNode, ExtractorNode
- ObjectiveNode, ConstraintNode, AlgorithmNode, SurrogateNode
**Panels (6):**
- NodeConfigPanel, ValidationPanel, ExecuteDialog
- ChatPanel, ConfigImporter, TemplateSelector
### Phase 2: LLM Intelligence Layer - COMPLETE
| Component | Location | Status |
|-----------|----------|--------|
| Canvas Chat Hook | `frontend/src/hooks/useCanvasChat.ts` | COMPLETE |
| Canvas MCP Tools | `mcp-server/atomizer-tools/src/tools/canvas.ts` | COMPLETE |
**Canvas Tools:**
- `validate_canvas_intent` - Validate graph before execution
- `execute_canvas_intent` - Create study + optionally run
- `interpret_canvas_intent` - Get recommendations
### Phase 3: Bidirectional Sync - COMPLETE
| Feature | Status |
|---------|--------|
| Session persistence | COMPLETE (SQLite) |
| Context builder | COMPLETE |
| Canvas ↔ Chat bridge | COMPLETE |
| Study context loading | COMPLETE |
### Phase 4: Templates & Polish - COMPLETE
| Feature | Status |
|---------|--------|
| Template selector | COMPLETE |
| Config importer | COMPLETE |
| Route: /canvas | COMPLETE |
---
## File Inventory
### MCP Server (`mcp-server/atomizer-tools/`)
```
src/
├── index.ts # Server entry (imports canvasTools)
├── tools/
│ ├── study.ts # Study management
│ ├── optimization.ts # Optimization control
│ ├── analysis.ts # Analysis tools
│ ├── reporting.ts # Report generation
│ ├── physics.ts # Physics explanations
│ ├── canvas.ts # Canvas intent tools
│ └── admin.ts # Power mode tools
└── utils/
└── paths.ts # Path utilities
```
### Backend Services (`atomizer-dashboard/backend/api/services/`)
```
__init__.py
claude_agent.py # Full Claude API integration (722 lines)
claude_cli_agent.py # CLI-based agent (202 lines)
conversation_store.py # SQLite persistence (295 lines)
session_manager.py # Session lifecycle (425 lines)
context_builder.py # Context assembly (246 lines)
```
### Frontend Canvas (`atomizer-dashboard/frontend/src/components/canvas/`)
```
AtomizerCanvas.tsx # Main canvas component
nodes/
├── index.ts # Node type registry
├── BaseNode.tsx
├── ModelNode.tsx
├── SolverNode.tsx
├── DesignVarNode.tsx
├── ExtractorNode.tsx
├── ObjectiveNode.tsx
├── ConstraintNode.tsx
├── AlgorithmNode.tsx
└── SurrogateNode.tsx
panels/
├── NodeConfigPanel.tsx
├── ValidationPanel.tsx
├── ExecuteDialog.tsx
├── ChatPanel.tsx
├── ConfigImporter.tsx
└── TemplateSelector.tsx
palette/
└── NodePalette.tsx
```
### Canvas Library (`atomizer-dashboard/frontend/src/lib/canvas/`)
```
schema.ts # Type definitions
intent.ts # Serialization (174 lines)
validation.ts # Graph validation
templates.ts # Workflow templates
index.ts # Exports
```
---
## Testing Checklist
To verify the implementation:
### 1. Build MCP Server
```bash
cd mcp-server/atomizer-tools
npm run build
# Expected: Compiles without errors
```
### 2. Start MCP Server
```bash
npm run dev
# Expected: "Atomizer MCP Server running in user mode"
```
### 3. Build Frontend
```bash
cd atomizer-dashboard/frontend
npm run build
# Expected: Compiles without errors
```
### 4. Start Dashboard
```bash
npm run dev
# Expected: Vite dev server starts
```
### 5. Browser Tests
- [ ] Navigate to `/canvas`
- [ ] Drag nodes from palette
- [ ] Connect nodes with edges
- [ ] Configure node properties
- [ ] Click "Validate"
- [ ] Click "Execute with Claude"
- [ ] Chat panel responds
---
## What's Next?
The Dashboard V2 implementation is complete. Remaining work falls into:
### Integration Testing
- End-to-end flow: Canvas → Intent → Claude → Study Creation → Optimization
- WebSocket stability under load
- Session recovery after browser refresh
### Documentation
- Update ATOMIZER_PODCAST_BRIEFING.md (already done)
- Add user guide for Canvas interface
- Update README with new features
### Optional Enhancements (Future)
- Phase 5: Tauri Desktop (see master plan)
- More workflow templates
- Advanced constraint types
- Real-time optimization progress on canvas
---
## Original Ralph Loop Prompt (Archived)
The original autonomous development prompt is no longer needed since all phases are complete. The prompt below is kept for reference only.
<details>
<summary>Click to expand archived prompt</summary>
```
[Original prompt content - now obsolete]
All phases (0-4) have been implemented. The Canvas feature with React Flow
is fully functional with:
- 8 node types
- Drag-drop from palette
- Node configuration panels
- Graph validation
- Intent JSON serialization
- MCP tool integration
- Claude chat integration
```
</details>
---
*Implementation completed via autonomous Claude Code sessions.*
*Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>*