abyss-ai/src/agent/reasoning/ultrathinking-processor.ts

Autonomous AI coding agent - enhanced OpenCode with autonomous capabilities

import { ReasoningMode, type ProcessingContext, type ProcessingResult } from "../types/agent"
import { BaseReasoningProcessor } from "./reasoning-processor"

// Ultrathinking - Real-time Adaptive Processing
export class UltrathinkingProcessor extends BaseReasoningProcessor {
  readonly mode = ReasoningMode.ULTRATHINKING

  async process(code: string, context: ProcessingContext): Promise<ProcessingResult> {
    this.log.info("Starting ultrathinking analysis", { 
      codeLength: code.length, 
      complexity: context.complexity 
    })

    const { result: analysisResult, duration } = await this.measureExecutionTime(async () => {
      // Real-time analysis that adapts based on incoming data
      const adaptiveAnalysis = await this.adaptiveAnalysis(code, context)
      const realTimeOptimization = await this.optimizeInRealtime(adaptiveAnalysis)
      
      return {
        adaptiveAnalysis,
        realTimeOptimization,
        adaptations: this.trackAdaptations(adaptiveAnalysis)
      }
    })

    const confidence = this.calculateConfidence(analysisResult)

    return {
      type: 'ultrathinking',
      result: analysisResult,
      confidence,
      processingTime: duration,
      adaptations: analysisResult.adaptations
    }
  }

  calculateConfidence(result: any): number {
    if (!result || !result.adaptiveAnalysis) return 0.1
    
    const { adaptiveAnalysis, realTimeOptimization } = result
    
    // Base confidence on adaptation success and optimization effectiveness
    const adaptationScore = adaptiveAnalysis.adaptationSuccess ? 0.4 : 0.1
    const optimizationScore = realTimeOptimization.effectiveness * 0.4
    const completenessScore = (adaptiveAnalysis.completeness || 0.5) * 0.2
    
    return Math.min(1, adaptationScore + optimizationScore + completenessScore)
  }

  private async adaptiveAnalysis(code: string, context: ProcessingContext) {
    // Dynamically adjust analysis depth based on complexity
    const complexity = context.complexity || this.assessComplexity(code)
    const analysisDepth = this.calculateDepth(complexity)
    
    this.log.debug("Adaptive analysis", { complexity, analysisDepth })
    
    const analysis = await this.analyzeWithDepth(code, analysisDepth)
    
    return {
      complexity,
      analysisDepth,
      analysis,
      adaptationSuccess: analysis.success,
      completeness: analysis.completeness,
      insights: analysis.insights
    }
  }

  private calculateDepth(complexity: number): number {
    // Adaptive depth calculation
    if (complexity < 0.3) return 1 // Light analysis
    if (complexity < 0.6) return 2 // Medium analysis  
    if (complexity < 0.8) return 3 // Deep analysis
    return 4 // Maximum depth
  }

  private async analyzeWithDepth(code: string, depth: number) {
    const structure = this.analyzeCodeStructure(code)
    
    const analysis = {
      structure,
      success: true,
      completeness: 0.5,
      insights: [] as string[]
    }

    // Level 1: Basic structure
    if (depth >= 1) {
      analysis.insights.push("Analyzed basic code structure")
      analysis.completeness = 0.6
    }

    // Level 2: Pattern recognition
    if (depth >= 2) {
      const patterns = this.recognizePatterns(code)
      analysis.insights.push(`Identified ${patterns.length} code patterns`)
      analysis.completeness = 0.7
      Object.assign(analysis, { patterns })
    }

    // Level 3: Flow analysis
    if (depth >= 3) {
      const flow = this.analyzeControlFlow(code)
      analysis.insights.push("Analyzed control flow and data dependencies")
      analysis.completeness = 0.85
      Object.assign(analysis, { flow })
    }

    // Level 4: Deep semantic analysis
    if (depth >= 4) {
      const semantics = this.analyzeSemantics(code)
      analysis.insights.push("Performed deep semantic analysis")
      analysis.completeness = 0.95
      Object.assign(analysis, { semantics })
    }

    return analysis
  }

  private recognizePatterns(code: string) {
    const patterns = []
    
    // Common design patterns
    if (code.includes('class') && code.includes('extends')) {
      patterns.push({ type: 'inheritance', confidence: 0.8 })
    }
    
    if (code.includes('interface') || code.includes('implements')) {
      patterns.push({ type: 'interface_pattern', confidence: 0.9 })
    }
    
    if (code.match(/function\s+\w+Factory/)) {
      patterns.push({ type: 'factory_pattern', confidence: 0.7 })
    }
    
    if (code.includes('singleton') || code.match(/static\s+instance/)) {
      patterns.push({ type: 'singleton_pattern', confidence: 0.8 })
    }
    
    // Functional patterns
    if (code.includes('.map(') || code.includes('.filter(') || code.includes('.reduce(')) {
      patterns.push({ type: 'functional_programming', confidence: 0.9 })
    }
    
    return patterns
  }

  private analyzeControlFlow(code: string) {
    const branches = code.match(/\b(if|else|switch|case)\b/g)?.length || 0
    const loops = code.match(/\b(for|while|do)\b/g)?.length || 0
    const exceptions = code.match(/\b(try|catch|finally|throw)\b/g)?.length || 0
    
    return {
      branches,
      loops,
      exceptions,
      complexity: branches + loops + exceptions,
      flowTypes: this.identifyFlowTypes(code)
    }
  }

  private identifyFlowTypes(code: string): string[] {
    const types = []
    
    if (code.includes('async') || code.includes('await')) {
      types.push('asynchronous')
    }
    
    if (code.includes('Promise') || code.includes('.then(')) {
      types.push('promise_based')
    }
    
    if (code.includes('callback') || code.match(/\(\s*\w+\s*=>\s*\w+\s*\)/)) {
      types.push('callback_pattern')
    }
    
    return types
  }

  private analyzeSemantics(code: string) {
    return {
      variables: this.extractVariables(code),
      dependencies: this.analyzeDependencies(code),
      sideEffects: this.identifySideEffects(code),
      purity: this.assessPurity(code)
    }
  }

  private extractVariables(code: string) {
    const declarations = code.match(/(?:let|const|var)\s+(\w+)/g) || []
    return declarations.map(decl => decl.split(/\s+/)[1])
  }

  private analyzeDependencies(code: string) {
    const imports = this.analyzeCodeStructure(code).imports
    const globalRefs = code.match(/\bglobal\.\w+|\bwindow\.\w+|\bprocess\.\w+/g) || []
    
    return {
      imports: imports.length,
      globalReferences: globalRefs.length,
      externalDependencies: imports.filter(imp => !imp.startsWith('.'))
    }
  }

  private identifySideEffects(code: string) {
    const effects = []
    
    if (code.includes('console.')) effects.push('console_output')
    if (code.includes('document.') || code.includes('window.')) effects.push('dom_manipulation')
    if (code.includes('fetch(') || code.includes('xhr')) effects.push('network_requests')
    if (code.includes('localStorage') || code.includes('sessionStorage')) effects.push('storage_access')
    if (code.includes('setTimeout') || code.includes('setInterval')) effects.push('timing_effects')
    
    return effects
  }

  private assessPurity(code: string): number {
    const sideEffects = this.identifySideEffects(code)
    const globalRefs = code.match(/\bglobal\.\w+|\bwindow\.\w+/g)?.length || 0
    
    // Pure function indicators
    const pureIndicators = [
      !sideEffects.length,
      !globalRefs,
      !code.includes('this.'),
      code.includes('return')
    ].filter(Boolean).length
    
    return pureIndicators / 4 // Normalize to 0-1
  }

  private async optimizeInRealtime(adaptiveAnalysis: any) {
    // Real-time optimization based on analysis
    const { complexity, analysis } = adaptiveAnalysis
    
    const optimizations = []
    
    // Performance optimizations
    if (complexity > 0.7) {
      optimizations.push({
        type: 'performance',
        suggestion: 'Consider breaking down complex functions',
        impact: 'high'
      })
    }
    
    // Pattern-based optimizations
    if (analysis.patterns) {
      for (const pattern of analysis.patterns) {
        if (pattern.type === 'functional_programming' && pattern.confidence > 0.8) {
          optimizations.push({
            type: 'functional',
            suggestion: 'Good use of functional programming patterns',
            impact: 'positive'
          })
        }
      }
    }
    
    // Flow optimizations
    if (analysis.flow && analysis.flow.complexity > 5) {
      optimizations.push({
        type: 'control_flow',
        suggestion: 'High control flow complexity detected - consider refactoring',
        impact: 'medium'
      })
    }
    
    return {
      optimizations,
      effectiveness: optimizations.length > 0 ? 0.8 : 0.5,
      recommendations: optimizations.map(opt => opt.suggestion)
    }
  }

  private trackAdaptations(adaptiveAnalysis: any) {
    return {
      depthAdaptations: adaptiveAnalysis.analysisDepth,
      complexityAdjustments: adaptiveAnalysis.complexity,
      successRate: adaptiveAnalysis.adaptationSuccess ? 1 : 0,
      timestamp: new Date().toISOString()
    }
  }
}