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>

atomizer-dashboard/frontend/src/api/client.ts

@@ -45,11 +45,18 @@ export interface ConfigResponse {
 
 export interface ProcessStatus {
   is_running: boolean;
+  is_paused?: boolean;
   pid?: number;
   start_time?: string;
   iteration?: number;
   fea_count?: number;
   nn_count?: number;
+  total_trials?: number;
+  completed_trials?: number;
+  time_per_trial_seconds?: number;
+  eta_seconds?: number;
+  eta_formatted?: string;
+  rate_per_hour?: number;
 }
 
 export interface ModelFile {
@@ -144,6 +151,7 @@ class ApiClient {
   async startOptimization(studyId: string, options?: {
     freshStart?: boolean;
     maxIterations?: number;
+    trials?: number;  // For SAT scripts
     feaBatchSize?: number;
     tuneTrials?: number;
     ensembleSize?: number;
@@ -172,6 +180,28 @@ class ApiClient {
     return response.json();
   }
 
+  async pauseOptimization(studyId: string): Promise<OptimizationControlResponse> {
+    const response = await fetch(`${API_BASE}/optimization/studies/${studyId}/pause`, {
+      method: 'POST',
+    });
+    if (!response.ok) {
+      const error = await response.json();
+      throw new Error(error.detail || 'Failed to pause optimization');
+    }
+    return response.json();
+  }
+
+  async resumeOptimization(studyId: string): Promise<OptimizationControlResponse> {
+    const response = await fetch(`${API_BASE}/optimization/studies/${studyId}/resume`, {
+      method: 'POST',
+    });
+    if (!response.ok) {
+      const error = await response.json();
+      throw new Error(error.detail || 'Failed to resume optimization');
+    }
+    return response.json();
+  }
+
   async validateOptimization(studyId: string, options?: {
     topN?: number;
   }): Promise<OptimizationControlResponse> {
@@ -210,6 +240,57 @@ class ApiClient {
     return response.json();
   }
 
+  async checkOptunaAvailable(): Promise<{
+    available: boolean;
+    path: string | null;
+    message: string;
+    install_instructions?: string;
+  }> {
+    const response = await fetch(`${API_BASE}/optimization/optuna-dashboard/check`);
+    if (!response.ok) {
+      return {
+        available: false,
+        path: null,
+        message: 'Failed to check optuna-dashboard availability',
+        install_instructions: 'pip install optuna-dashboard'
+      };
+    }
+    return response.json();
+  }
+
+  // Optimizer state
+  async getOptimizerState(studyId: string): Promise<{
+    available: boolean;
+    source?: string;
+    phase?: string;
+    phase_description?: string;
+    phase_progress?: number;
+    current_strategy?: string;
+    sampler?: {
+      name: string;
+      description: string;
+    };
+    objectives?: Array<{
+      name: string;
+      direction: string;
+      current_best?: number;
+      unit?: string;
+    }>;
+    plan?: {
+      total_phases: number;
+      current_phase: number;
+      phases: string[];
+    };
+    completed_trials?: number;
+    total_trials?: number;
+  }> {
+    const response = await fetch(`${API_BASE}/optimization/studies/${studyId}/optimizer-state`);
+    if (!response.ok) {
+      return { available: false };
+    }
+    return response.json();
+  }
+
   // Model files
   async getModelFiles(studyId: string): Promise<ModelFilesResponse> {
     const response = await fetch(`${API_BASE}/optimization/studies/${studyId}/model-files`);