code-plan/src/services/WorkflowOptimizer.ts

import { Database } from '../database/Database';
import { OptimizationRecommendation } from '../models';
import { TokenTracker } from './TokenTracker';
import { SessionManager } from './SessionManager';

export class WorkflowOptimizer {
  private db: Database;
  private tokenTracker: TokenTracker;
  private sessionManager: SessionManager;

  constructor(db: Database, tokenTracker: TokenTracker, sessionManager: SessionManager) {
    this.db = db;
    this.tokenTracker = tokenTracker;
    this.sessionManager = sessionManager;
  }

  async analyzeWorkflowEfficiency(projectId?: string): Promise<{
    score: number;
    recommendations: OptimizationRecommendation[];
    insights: string[];
  }> {
    const recommendations: OptimizationRecommendation[] = [];
    const insights: string[] = [];
    let score = 100;

    // Analyze session patterns
    const sessionAnalysis = await this.analyzeSessionPatterns(projectId);
    score -= sessionAnalysis.penalties;
    recommendations.push(...sessionAnalysis.recommendations);
    insights.push(...sessionAnalysis.insights);

    // Analyze token usage
    const tokenAnalysis = await this.analyzeTokenUsage();
    score -= tokenAnalysis.penalties;
    recommendations.push(...tokenAnalysis.recommendations);
    insights.push(...tokenAnalysis.insights);

    // Analyze scheduling efficiency
    const schedulingAnalysis = await this.analyzeSchedulingEfficiency();
    score -= schedulingAnalysis.penalties;
    recommendations.push(...schedulingAnalysis.recommendations);
    insights.push(...schedulingAnalysis.insights);

    return {
      score: Math.max(0, Math.min(100, score)),
      recommendations: this.prioritizeRecommendations(recommendations),
      insights
    };
  }

  async suggestOptimalSession(taskDescription: string, complexity: 'simple' | 'medium' | 'complex'): Promise<{
    modelType: 'opus' | 'sonnet';
    estimatedTokens: number;
    batchingSuggestions: string[];
    preparationTips: string[];
  }> {
    const modelType = this.recommendModel(taskDescription, complexity);
    const estimatedTokens = this.estimateTokenUsage(taskDescription, complexity, modelType);
    
    return {
      modelType,
      estimatedTokens,
      batchingSuggestions: this.generateBatchingSuggestions(taskDescription),
      preparationTips: this.generatePreparationTips(complexity)
    };
  }

  async generateOptimalSchedule(upcomingTasks: Array<{
    description: string;
    complexity: 'simple' | 'medium' | 'complex';
    estimatedDuration: number; // minutes
    priority: 'high' | 'medium' | 'low';
  }>): Promise<{
    schedule: Array<{
      task: string;
      recommendedTime: Date;
      modelType: 'opus' | 'sonnet';
      grouping: string;
    }>;
    totalEstimatedTokens: number;
    optimizationNotes: string[];
  }> {
    const schedule = [];
    let totalTokens = 0;
    const optimizationNotes = [];

    // Group tasks by complexity and type
    const groupedTasks = this.groupTasksByType(upcomingTasks);

    // Get current window status
    const currentWindow = await this.sessionManager.getCurrentWindow();
    const nextWindow = await this.sessionManager.getNextAvailableWindow();

    let currentTime = currentWindow ? new Date() : (nextWindow || new Date());

    for (const [groupName, tasks] of Object.entries(groupedTasks)) {
      for (const task of tasks) {
        const suggestion = await this.suggestOptimalSession(task.description, task.complexity);
        
        schedule.push({
          task: task.description,
          recommendedTime: new Date(currentTime),
          modelType: suggestion.modelType,
          grouping: groupName
        });

        totalTokens += suggestion.estimatedTokens;
        currentTime = new Date(currentTime.getTime() + task.estimatedDuration * 60 * 1000);
      }
    }

    // Add optimization notes
    if (totalTokens > 400000) {
      optimizationNotes.push('High token usage expected. Consider splitting across multiple 5-hour windows');
    }

    const opusTasks = upcomingTasks.filter(t => t.complexity === 'complex').length;
    if (opusTasks > 3) {
      optimizationNotes.push('Multiple complex tasks detected. Consider using overlap hack for extended sessions');
    }

    return {
      schedule,
      totalEstimatedTokens: totalTokens,
      optimizationNotes
    };
  }

  async detectWorkflowAnomalies(): Promise<{
    anomalies: Array<{
      type: 'token_spike' | 'session_fragmentation' | 'model_misuse' | 'scheduling_conflict';
      severity: 'low' | 'medium' | 'high';
      description: string;
      recommendation: string;
    }>;
    trends: Array<{
      metric: string;
      trend: 'improving' | 'declining' | 'stable';
      change: number;
    }>;
  }> {
    const anomalies = [];
    const trends = [];

    // Detect token spikes
    const recentUsage = await this.tokenTracker.getUsageStats(7);
    const avgDailyTokens = recentUsage.reduce((sum, day) => sum + day.totalTokens, 0) / 7;
    
    if (avgDailyTokens > 100000) {
      anomalies.push({
        type: 'token_spike',
        severity: 'high',
        description: `Daily token usage (${avgDailyTokens.toLocaleString()}) is unusually high`,
        recommendation: 'Review recent sessions for inefficiencies and consider using /compact more frequently'
      });
    }

    // Detect session fragmentation
    const recentSessions = await this.sessionManager.getSessionHistory(20);
    const shortSessions = recentSessions.filter(s => {
      const duration = s.endTime ? (s.endTime.getTime() - s.startTime.getTime()) / (1000 * 60) : 0;
      return duration < 10;
    }).length;

    if (shortSessions > recentSessions.length * 0.5) {
      anomalies.push({
        type: 'session_fragmentation',
        severity: 'medium',
        description: `${shortSessions} out of ${recentSessions.length} recent sessions were shorter than 10 minutes`,
        recommendation: 'Consider batching similar tasks into longer, more focused sessions'
      });
    }

    // Detect model misuse
    const opusHeavyDays = recentUsage.filter(day => day.opusSessions > day.sonnetSessions).length;
    if (opusHeavyDays > recentUsage.length * 0.6) {
      anomalies.push({
        type: 'model_misuse',
        severity: 'medium',
        description: 'Opus is being used more frequently than Sonnet',
        recommendation: 'Reserve Opus for complex tasks and use Sonnet for routine implementation work'
      });
    }

    // Calculate trends
    if (recentUsage.length >= 2) {
      const recentAvg = recentUsage.slice(0, 3).reduce((sum, day) => sum + day.optimizationScore, 0) / 3;
      const olderAvg = recentUsage.slice(3, 6).reduce((sum, day) => sum + day.optimizationScore, 0) / Math.min(3, recentUsage.length - 3);
      
      if (recentAvg > olderAvg + 5) {
        trends.push({ metric: 'optimization_score', trend: 'improving', change: recentAvg - olderAvg });
      } else if (recentAvg < olderAvg - 5) {
        trends.push({ metric: 'optimization_score', trend: 'declining', change: olderAvg - recentAvg });
      } else {
        trends.push({ metric: 'optimization_score', trend: 'stable', change: 0 });
      }
    }

    return { anomalies, trends };
  }

  private async analyzeSessionPatterns(projectId?: string): Promise<{
    penalties: number;
    recommendations: OptimizationRecommendation[];
    insights: string[];
  }> {
    const penalties = 0;
    const recommendations: OptimizationRecommendation[] = [];
    const insights: string[] = [];

    const sessions = projectId 
      ? await this.db.all('SELECT * FROM sessions WHERE projectId = ? ORDER BY startTime DESC LIMIT 10', [projectId])
      : await this.sessionManager.getSessionHistory(10);

    // Analyze session length distribution
    const sessionLengths = sessions.map(session => {
      const endTime = (session as { endTime?: string | Date }).endTime || new Date();
      const endTimeDate = typeof endTime === 'string' ? new Date(endTime) : endTime;
      return (endTimeDate.getTime() - new Date((session as { startTime: string }).startTime).getTime()) / (1000 * 60); // minutes
    });

    const avgLength = sessionLengths.reduce((sum, length) => sum + length, 0) / sessionLengths.length;
    
    if (avgLength < 15) {
      recommendations.push({
        type: 'workflow',
        priority: 'medium',
        message: 'Average session length is quite short. Consider batching related tasks.'
      });
    }

    insights.push(`Average session duration: ${avgLength.toFixed(1)} minutes`);

    return { penalties, recommendations, insights };
  }

  private async analyzeTokenUsage(): Promise<{
    penalties: number;
    recommendations: OptimizationRecommendation[];
    insights: string[];
  }> {
    const penalties = 0;
    const recommendations: OptimizationRecommendation[] = [];
    const insights: string[] = [];

    const usageStats = await this.tokenTracker.getUsageStats(7);
    usageStats.reduce((sum, day) => sum + day.totalTokens, 0);
    const avgTokensPerSession = usageStats.reduce((sum, day) => sum + (day.totalTokens / Math.max(1, day.sessionsCount)), 0) / usageStats.length;

    if (avgTokensPerSession > 50000) {
      recommendations.push({
        type: 'token',
        priority: 'high',
        message: 'High token usage per session detected. Consider using /compact more frequently.',
        potentialSavings: avgTokensPerSession * 0.3
      });
    }

    insights.push(`Average tokens per session: ${avgTokensPerSession.toLocaleString()}`);

    return { penalties, recommendations, insights };
  }

  private async analyzeSchedulingEfficiency(): Promise<{
    penalties: number;
    recommendations: OptimizationRecommendation[];
    insights: string[];
  }> {
    const penalties = 0;
    const recommendations: OptimizationRecommendation[] = [];
    const insights: string[] = [];

    const currentWindow = await this.sessionManager.getCurrentWindow();
    
    if (!currentWindow) {
      recommendations.push({
        type: 'scheduling',
        priority: 'medium',
        message: 'No active 5-hour window. Consider using the overlap hack to prepare for intensive sessions.'
      });
    }

    insights.push(currentWindow ? 'Currently within an active 5-hour window' : 'No active window detected');

    return { penalties, recommendations, insights };
  }

  private recommendModel(taskDescription: string, complexity: 'simple' | 'medium' | 'complex'): 'opus' | 'sonnet' {
    if (complexity === 'complex') return 'opus';
    if (complexity === 'simple') return 'sonnet';
    
    // For medium complexity, analyze task description
    const complexKeywords = ['architecture', 'design', 'refactor', 'optimize', 'debug complex', 'implement system'];
    const hasComplexKeywords = complexKeywords.some(keyword => 
      taskDescription.toLowerCase().includes(keyword)
    );
    
    return hasComplexKeywords ? 'opus' : 'sonnet';
  }

  private estimateTokenUsage(taskDescription: string, complexity: 'simple' | 'medium' | 'complex', modelType: 'opus' | 'sonnet'): number {
    const baseTokens = {
      simple: { sonnet: 5000, opus: 8000 },
      medium: { sonnet: 15000, opus: 25000 },
      complex: { sonnet: 30000, opus: 50000 }
    };

    return baseTokens[complexity][modelType];
  }

  private generateBatchingSuggestions(taskDescription: string): string[] {
    const suggestions = [
      'Prepare all related files and context before starting',
      'Group similar implementation tasks together',
      'Plan testing and linting as part of the same session'
    ];

    if (taskDescription.includes('test')) {
      suggestions.push('Include test writing in the same session as implementation');
    }

    if (taskDescription.includes('refactor')) {
      suggestions.push('Batch related refactoring tasks to maintain context');
    }

    return suggestions;
  }

  private generatePreparationTips(complexity: 'simple' | 'medium' | 'complex'): string[] {
    const tips = {
      simple: [
        'Have specific files ready to reference',
        'Prepare clear, concise instructions'
      ],
      medium: [
        'Review relevant documentation beforehand',
        'Prepare test cases or expected outcomes',
        'Consider edge cases in advance'
      ],
      complex: [
        'Create a detailed step-by-step plan',
        'Prepare comprehensive project context',
        'Have fallback approaches ready',
        'Schedule adequate time for implementation'
      ]
    };

    return tips[complexity];
  }

  private groupTasksByType(tasks: Array<{
    description: string;
    complexity: 'simple' | 'medium' | 'complex';
    estimatedDuration: number;
    priority: 'high' | 'medium' | 'low';
  }>): Record<string, Array<{
    description: string;
    complexity: 'simple' | 'medium' | 'complex';
    estimatedDuration: number;
    priority: 'high' | 'medium' | 'low';
  }>> {
    return tasks.reduce((groups, task) => {
      const category = this.categorizeTask(task);
      if (!groups[category]) groups[category] = [];
      groups[category].push(task);
      return groups;
    }, {} as Record<string, Array<{
      description: string;
      complexity: 'simple' | 'medium' | 'complex';
      estimatedDuration: number;
      priority: 'high' | 'medium' | 'low';
    }>>);
  }

  private categorizeTask(task: {
    description: string;
    complexity: 'simple' | 'medium' | 'complex';
    estimatedDuration: number;
    priority: 'high' | 'medium' | 'low';
  }): string {
    if (task.complexity === 'complex') return 'Complex Architecture';
    if (task.description.includes('test')) return 'Testing';
    if (task.description.includes('fix') || task.description.includes('bug')) return 'Bug Fixes';
    if (task.description.includes('feature')) return 'Feature Development';
    return 'General Tasks';
  }

  private prioritizeRecommendations(recommendations: OptimizationRecommendation[]): OptimizationRecommendation[] {
    return recommendations.sort((a, b) => {
      const priorityOrder = { high: 3, medium: 2, low: 1 };
      return priorityOrder[b.priority] - priorityOrder[a.priority];
    });
  }
}