abyss-ai/src/agent/file-processing/large-file-processor.ts

Autonomous AI coding agent - enhanced OpenCode with autonomous capabilities

import { Log } from "../../util/log"
import { 
  IAgent,
  AgentTask, 
  AgentResult, 
  ProcessingContext, 
  ProcessingResult,
  FileChunk,
  ChunkResult,
  ReasoningMode
} from "../types/agent"

export class LargeFileProcessor {
  private log = Log.create({ service: "large-file-processor" })
  
  private chunkSize: number = 5000 // characters per chunk
  private overlapSize: number = 200 // overlap between chunks
  private maxConcurrentChunks: number = 4 // parallel processing limit
  
  constructor(
    chunkSize: number = 5000,
    overlapSize: number = 200,
    maxConcurrentChunks: number = 4
  ) {
    this.chunkSize = chunkSize
    this.overlapSize = overlapSize
    this.maxConcurrentChunks = maxConcurrentChunks
    
    this.log.info("LargeFileProcessor initialized", {
      chunkSize: this.chunkSize,
      overlapSize: this.overlapSize,
      maxConcurrentChunks: this.maxConcurrentChunks
    })
  }

  async processLargeFile(filePath: string, context: ProcessingContext): Promise<ProcessingResult> {
    this.log.info("Processing large file", { filePath, context })
    
    const startTime = Date.now()
    
    try {
      // Read file content
      const fileContent = await this.readFile(filePath)
      
      if (fileContent.length <= this.chunkSize) {
        this.log.info("File is small enough for direct processing")
        return await this.processSmallFile(fileContent, context)
      }
      
      // Create chunks with overlap
      const chunks = this.chunkFile(fileContent)
      this.log.info("File chunked", { 
        totalChunks: chunks.length,
        avgChunkSize: Math.round(chunks.reduce((sum, c) => sum + c.content.length, 0) / chunks.length)
      })
      
      // Create sub-agents for each chunk (virtual agents using provided processing logic)
      const chunkAgents = this.createChunkAgents(chunks.length)
      
      // Process chunks in parallel with all reasoning modes
      const chunkResults = await this.processChunksInParallel(chunks, chunkAgents, context)
      
      // Synthesize results across chunks
      const synthesizedResult = await this.synthesizeChunkResults(chunkResults, fileContent)
      
      // Verify progress and ensure no details missed
      const verificationResult = await this.verifyAnalysis(synthesizedResult, fileContent, chunks)
      
      const processingTime = Date.now() - startTime
      
      return {
        type: 'large-file-processing',
        result: synthesizedResult,
        verification: verificationResult,
        chunksProcessed: chunks.length,
        confidence: this.calculateOverallConfidence(synthesizedResult, verificationResult),
        processingTime
      }
      
    } catch (error) {
      this.log.error("Large file processing failed", { filePath, error })
      throw error
    }
  }

  private async readFile(filePath: string): Promise<string> {
    try {
      // Use Bun's file API for reading
      const file = Bun.file(filePath)
      const content = await file.text()
      
      this.log.debug("File read successfully", { 
        filePath, 
        size: content.length,
        lines: content.split('\n').length
      })
      
      return content
    } catch (error) {
      this.log.error("Failed to read file", { filePath, error })
      throw new Error(`Cannot read file: ${filePath}`)
    }
  }

  private async processSmallFile(content: string, context: ProcessingContext): Promise<ProcessingResult> {
    // For small files, process directly without chunking
    return {
      type: 'direct-processing',
      result: {
        content,
        analysis: 'File processed directly without chunking',
        insights: ['File size within direct processing limit'],
        structure: this.analyzeFileStructure(content)
      },
      confidence: 0.9,
      processingTime: 0
    }
  }

  private chunkFile(content: string): FileChunk[] {
    const chunks: FileChunk[] = []
    const lines = content.split('\n')
    
    let currentChunk = ''
    let currentLine = 0
    let chunkStartLine = 0
    let chunkIndex = 0
    
    for (let i = 0; i < lines.length; i++) {
      const line = lines[i] + '\n'
      
      // Check if adding this line would exceed chunk size
      if (currentChunk.length + line.length > this.chunkSize && currentChunk.length > 0) {
        // Create chunk with overlap from previous chunk
        const overlap = this.getOverlap(chunks[chunks.length - 1])
        const chunkContent = overlap + currentChunk
        
        chunks.push({
          index: chunkIndex++,
          content: chunkContent,
          startLine: chunkStartLine,
          endLine: i - 1,
          overlap: overlap
        })
        
        // Start new chunk with overlap
        currentChunk = this.getChunkOverlap(currentChunk) + line
        chunkStartLine = Math.max(0, i - this.getOverlapLines())
        currentLine = i
      } else {
        currentChunk += line
        if (currentChunk.length === line.length) {
          // First line of chunk
          chunkStartLine = i
        }
        currentLine = i
      }
    }
    
    // Add final chunk
    if (currentChunk.length > 0) {
      const overlap = this.getOverlap(chunks[chunks.length - 1])
      chunks.push({
        index: chunkIndex,
        content: overlap + currentChunk,
        startLine: chunkStartLine,
        endLine: lines.length - 1,
        overlap: overlap
      })
    }
    
    return chunks
  }

  private getOverlap(previousChunk?: FileChunk): string {
    if (!previousChunk) return ''
    
    const lines = previousChunk.content.split('\n')
    const overlapLines = Math.min(this.getOverlapLines(), lines.length)
    
    return lines.slice(-overlapLines).join('\n') + (overlapLines > 0 ? '\n' : '')
  }

  private getChunkOverlap(chunk: string): string {
    const lines = chunk.split('\n')
    const overlapLines = Math.min(this.getOverlapLines(), lines.length)
    
    return lines.slice(-overlapLines).join('\n') + (overlapLines > 0 ? '\n' : '')
  }

  private getOverlapLines(): number {
    // Calculate overlap in terms of lines (rough estimate)
    return Math.floor(this.overlapSize / 50) // Assuming ~50 chars per line
  }

  private createChunkAgents(chunkCount: number): VirtualChunkAgent[] {
    const agents: VirtualChunkAgent[] = []
    
    for (let i = 0; i < chunkCount; i++) {
      agents.push(new VirtualChunkAgent(`chunk-agent-${i}`, i))
    }
    
    return agents
  }

  private async processChunksInParallel(
    chunks: FileChunk[], 
    agents: VirtualChunkAgent[], 
    context: ProcessingContext
  ): Promise<ChunkResult[]> {
    this.log.info("Processing chunks in parallel", { 
      chunkCount: chunks.length,
      maxConcurrent: this.maxConcurrentChunks
    })
    
    const results: ChunkResult[] = []
    
    // Process chunks in batches to limit concurrency
    for (let i = 0; i < chunks.length; i += this.maxConcurrentChunks) {
      const chunkBatch = chunks.slice(i, i + this.maxConcurrentChunks)
      const agentBatch = agents.slice(i, i + this.maxConcurrentChunks)
      
      const batchPromises = chunkBatch.map(async (chunk, batchIndex) => {
        const agent = agentBatch[batchIndex]
        
        // Create task for chunk processing
        const chunkTask: AgentTask = {
          id: `chunk-${chunk.index}`,
          type: 'chunk-analysis',
          data: chunk,
          context: {
            ...context,
            chunkIndex: chunk.index,
            totalChunks: chunks.length,
            filePath: context.filePath
          },
          reasoningModes: [
            ReasoningMode.ULTRATHINKING,
            ReasoningMode.ULTRAREASONING,
            ReasoningMode.HYBRID_REASONING,
            ReasoningMode.HYBRID_THINKING
          ]
        }
        
        try {
          const result = await agent.process(chunkTask)
          const verification = await this.verifyChunkResult(result, chunk)
          
          return {
            chunkIndex: chunk.index,
            result: result,
            verification: verification
          }
        } catch (error) {
          this.log.error("Chunk processing failed", { 
            chunkIndex: chunk.index, 
            error 
          })
          
          // Return error result instead of failing completely
          return {
            chunkIndex: chunk.index,
            result: {
              agentId: agent.id,
              agentType: agent.type,
              taskId: chunkTask.id,
              reasoningMode: ReasoningMode.ULTRATHINKING,
              result: { error: 'Processing failed', chunk: chunk.index },
              confidence: 0.1,
              processingTime: 0,
              errors: [error instanceof Error ? error.message : String(error)]
            },
            verification: { success: false, issues: ['Processing failed'] }
          }
        }
      })
      
      const batchResults = await Promise.all(batchPromises)
      results.push(...batchResults)
      
      this.log.debug("Batch processed", { 
        batchStart: i,
        batchSize: chunkBatch.length,
        totalProcessed: results.length
      })
    }
    
    return results.sort((a, b) => a.chunkIndex - b.chunkIndex)
  }

  private async verifyChunkResult(result: AgentResult, chunk: FileChunk): Promise<any> {
    // Verification logic for individual chunk results
    const verification = {
      success: true,
      issues: [] as string[],
      coverage: 0,
      qualityScore: 0
    }
    
    // Check if result contains meaningful analysis
    if (!result.result || typeof result.result !== 'object') {
      verification.success = false
      verification.issues.push('Result does not contain analysis data')
    }
    
    // Check confidence level
    if (result.confidence < 0.3) {
      verification.issues.push('Low confidence in chunk analysis')
    }
    
    // Check for errors
    if (result.errors && result.errors.length > 0) {
      verification.success = false
      verification.issues.push(...result.errors)
    }
    
    // Calculate coverage (how much of the chunk was analyzed)
    verification.coverage = this.calculateChunkCoverage(result, chunk)
    
    // Calculate quality score
    verification.qualityScore = this.calculateChunkQuality(result, chunk)
    
    return verification
  }

  private calculateChunkCoverage(result: AgentResult, chunk: FileChunk): number {
    // Simple coverage calculation - could be more sophisticated
    if (!result.result) return 0
    
    const analysis = result.result
    let coverage = 0
    
    // Check if different aspects were analyzed
    if (analysis.structure) coverage += 0.3
    if (analysis.issues) coverage += 0.3
    if (analysis.insights) coverage += 0.2
    if (analysis.patterns) coverage += 0.2
    
    return Math.min(1, coverage)
  }

  private calculateChunkQuality(result: AgentResult, chunk: FileChunk): number {
    // Quality assessment based on result depth and confidence
    const confidence = result.confidence
    const processingTime = result.processingTime || 0
    
    // Penalize very fast processing (might indicate superficial analysis)
    const timeScore = processingTime > 100 ? 1 : processingTime / 100
    
    return (confidence * 0.7 + timeScore * 0.3)
  }

  private async synthesizeChunkResults(chunkResults: ChunkResult[], originalContent: string): Promise<any> {
    this.log.info("Synthesizing chunk results", { chunkCount: chunkResults.length })
    
    const synthesis = {
      overview: this.generateOverview(chunkResults, originalContent),
      combinedInsights: this.combineInsights(chunkResults),
      structuralAnalysis: this.synthesizeStructuralAnalysis(chunkResults),
      issueAggregation: this.aggregateIssues(chunkResults),
      patterns: this.identifyGlobalPatterns(chunkResults),
      recommendations: this.generateRecommendations(chunkResults),
      confidence: this.calculateSynthesisConfidence(chunkResults),
      coverage: this.calculateTotalCoverage(chunkResults, originalContent)
    }
    
    return synthesis
  }

  private generateOverview(chunkResults: ChunkResult[], originalContent: string): any {
    const totalLines = originalContent.split('\n').length
    const totalChars = originalContent.length
    const successfulChunks = chunkResults.filter(r => r.verification.success).length
    
    return {
      fileStats: {
        totalLines,
        totalCharacters: totalChars,
        language: this.detectLanguage(originalContent),
        complexity: this.assessFileComplexity(originalContent)
      },
      processingStats: {
        totalChunks: chunkResults.length,
        successfulChunks,
        failedChunks: chunkResults.length - successfulChunks,
        averageConfidence: this.calculateAverageConfidence(chunkResults),
        totalProcessingTime: chunkResults.reduce((sum, r) => sum + (r.result.processingTime || 0), 0)
      }
    }
  }

  private detectLanguage(content: string): string {
    // Simple language detection based on file content
    if (content.includes('function') && content.includes('const')) return 'javascript'
    if (content.includes('def ') && content.includes('import ')) return 'python'
    if (content.includes('public class') && content.includes('import ')) return 'java'
    if (content.includes('#include') && content.includes('int main')) return 'c++'
    if (content.includes('fn ') && content.includes('use ')) return 'rust'
    
    return 'unknown'
  }

  private assessFileComplexity(content: string): string {
    const lines = content.split('\n').length
    const functions = (content.match(/function\s+\w+|def\s+\w+|fn\s+\w+/g) || []).length
    const classes = (content.match(/class\s+\w+|struct\s+\w+/g) || []).length
    
    const complexityScore = (lines / 100) + (functions / 5) + (classes / 2)
    
    if (complexityScore > 10) return 'high'
    if (complexityScore > 5) return 'medium'
    return 'low'
  }

  private calculateAverageConfidence(chunkResults: ChunkResult[]): number {
    if (chunkResults.length === 0) return 0
    
    const totalConfidence = chunkResults.reduce((sum, r) => sum + r.result.confidence, 0)
    return totalConfidence / chunkResults.length
  }

  private combineInsights(chunkResults: ChunkResult[]): string[] {
    const allInsights: string[] = []
    
    chunkResults.forEach(chunkResult => {
      const result = chunkResult.result.result
      if (result && result.insights) {
        if (Array.isArray(result.insights)) {
          allInsights.push(...result.insights)
        } else if (typeof result.insights === 'string') {
          allInsights.push(result.insights)
        }
      }
    })
    
    // Deduplicate and categorize insights
    const uniqueInsights = Array.from(new Set(allInsights))
    return uniqueInsights.slice(0, 20) // Limit to top 20 insights
  }

  private synthesizeStructuralAnalysis(chunkResults: ChunkResult[]): any {
    const structures = chunkResults.map(r => r.result.result?.structure).filter(Boolean)
    
    if (structures.length === 0) {
      return { error: 'No structural analysis available' }
    }
    
    // Combine structural information from all chunks
    const combined = {
      totalFunctions: 0,
      totalClasses: 0,
      totalLines: 0,
      imports: new Set<string>(),
      complexity: 0
    }
    
    structures.forEach(structure => {
      combined.totalFunctions += structure.functions?.length || 0
      combined.totalClasses += structure.classes?.length || 0
      combined.totalLines += structure.lineCount || 0
      
      if (structure.imports) {
        structure.imports.forEach((imp: string) => combined.imports.add(imp))
      }
      
      combined.complexity += structure.complexity || 0
    })
    
    return {
      ...combined,
      imports: Array.from(combined.imports),
      averageComplexity: combined.complexity / structures.length
    }
  }

  private aggregateIssues(chunkResults: ChunkResult[]): any {
    const allIssues: any[] = []
    
    chunkResults.forEach((chunkResult, index) => {
      const result = chunkResult.result.result
      
      // Collect issues from result
      if (result && result.issues) {
        const issues = Array.isArray(result.issues) ? result.issues : [result.issues]
        issues.forEach(issue => {
          allIssues.push({
            ...issue,
            chunkIndex: index,
            source: 'chunk-analysis'
          })
        })
      }
      
      // Collect errors
      if (chunkResult.result.errors) {
        chunkResult.result.errors.forEach(error => {
          allIssues.push({
            type: 'error',
            severity: 'high',
            message: error,
            chunkIndex: index,
            source: 'processing-error'
          })
        })
      }
      
      // Collect verification issues
      if (chunkResult.verification.issues) {
        chunkResult.verification.issues.forEach(issue => {
          allIssues.push({
            type: 'verification',
            severity: 'medium',
            message: issue,
            chunkIndex: index,
            source: 'verification'
          })
        })
      }
    })
    
    // Categorize issues
    const categorized = {
      critical: allIssues.filter(i => i.severity === 'critical'),
      high: allIssues.filter(i => i.severity === 'high'),
      medium: allIssues.filter(i => i.severity === 'medium'),
      low: allIssues.filter(i => i.severity === 'low'),
      total: allIssues.length
    }
    
    return categorized
  }

  private identifyGlobalPatterns(chunkResults: ChunkResult[]): any[] {
    const patterns: any[] = []
    
    // Look for patterns that appear across multiple chunks
    const chunkPatterns = chunkResults.map(r => r.result.result?.patterns).filter(Boolean)
    
    if (chunkPatterns.length === 0) return patterns
    
    // Count pattern occurrences across chunks
    const patternCounts = new Map<string, number>()
    
    chunkPatterns.forEach(chunkPatternSet => {
      if (Array.isArray(chunkPatternSet)) {
        chunkPatternSet.forEach(pattern => {
          const key = pattern.type || pattern.name || String(pattern)
          patternCounts.set(key, (patternCounts.get(key) || 0) + 1)
        })
      }
    })
    
    // Return patterns that appear in multiple chunks
    patternCounts.forEach((count, patternType) => {
      if (count > 1) {
        patterns.push({
          type: patternType,
          occurrences: count,
          frequency: count / chunkResults.length,
          scope: 'global'
        })
      }
    })
    
    return patterns
  }

  private generateRecommendations(chunkResults: ChunkResult[]): string[] {
    const recommendations: string[] = []
    
    // Analyze overall quality
    const avgConfidence = this.calculateAverageConfidence(chunkResults)
    
    if (avgConfidence < 0.6) {
      recommendations.push('Consider running additional analysis passes to improve confidence')
    }
    
    // Check for failed chunks
    const failedChunks = chunkResults.filter(r => !r.verification.success).length
    if (failedChunks > 0) {
      recommendations.push(`Re-process ${failedChunks} failed chunks with different parameters`)
    }
    
    // Check for high issue density
    const totalIssues = chunkResults.reduce((sum, r) => 
      sum + (r.result.errors?.length || 0) + (r.verification.issues?.length || 0), 0
    )
    
    if (totalIssues > chunkResults.length * 2) {
      recommendations.push('High issue density detected - consider refactoring or detailed review')
    }
    
    // Performance recommendations
    const avgProcessingTime = chunkResults.reduce((sum, r) => 
      sum + (r.result.processingTime || 0), 0
    ) / chunkResults.length
    
    if (avgProcessingTime > 5000) { // 5 seconds
      recommendations.push('Consider optimizing chunk size for better performance')
    }
    
    return recommendations
  }

  private calculateSynthesisConfidence(chunkResults: ChunkResult[]): number {
    if (chunkResults.length === 0) return 0
    
    const successfulChunks = chunkResults.filter(r => r.verification.success).length
    const avgChunkConfidence = this.calculateAverageConfidence(chunkResults)
    
    // Confidence based on success rate and individual chunk confidence
    const successRate = successfulChunks / chunkResults.length
    return (successRate * 0.6 + avgChunkConfidence * 0.4)
  }

  private calculateTotalCoverage(chunkResults: ChunkResult[], originalContent: string): number {
    const totalChunks = chunkResults.length
    const successfulChunks = chunkResults.filter(r => r.verification.success).length
    
    // Coverage based on successful chunk processing
    return successfulChunks / totalChunks
  }

  private async verifyAnalysis(synthesizedResult: any, originalContent: string, chunks: FileChunk[]): Promise<any> {
    this.log.info("Verifying synthesized analysis")
    
    const verification = {
      completeness: this.verifyCompleteness(synthesizedResult, chunks),
      consistency: this.verifyConsistency(synthesizedResult),
      accuracy: this.verifyAccuracy(synthesizedResult, originalContent),
      recommendations: this.generateVerificationRecommendations(synthesizedResult)
    }
    
    return verification
  }

  private verifyCompleteness(synthesizedResult: any, chunks: FileChunk[]): any {
    const completeness = {
      score: 0,
      issues: [] as string[],
      coverage: 0
    }
    
    // Check if all chunks were processed
    const processedChunks = synthesizedResult.overview?.processingStats?.successfulChunks || 0
    const totalChunks = chunks.length
    
    completeness.coverage = processedChunks / totalChunks
    
    if (completeness.coverage < 0.9) {
      completeness.issues.push(`Only ${Math.round(completeness.coverage * 100)}% of chunks processed successfully`)
    }
    
    // Check if key analysis components are present
    const requiredComponents = ['overview', 'combinedInsights', 'structuralAnalysis', 'issueAggregation']
    const presentComponents = requiredComponents.filter(comp => synthesizedResult[comp])
    
    completeness.score = presentComponents.length / requiredComponents.length
    
    const missingComponents = requiredComponents.filter(comp => !synthesizedResult[comp])
    if (missingComponents.length > 0) {
      completeness.issues.push(`Missing analysis components: ${missingComponents.join(', ')}`)
    }
    
    return completeness
  }

  private verifyConsistency(synthesizedResult: any): any {
    const consistency = {
      score: 1,
      issues: [] as string[]
    }
    
    // Check for internal consistency in the results
    const overview = synthesizedResult.overview
    const structural = synthesizedResult.structuralAnalysis
    
    if (overview && structural) {
      // Verify structural data consistency
      if (overview.fileStats && structural.totalLines) {
        const lineDifference = Math.abs(overview.fileStats.totalLines - structural.totalLines)
        const relativeDifference = lineDifference / overview.fileStats.totalLines
        
        if (relativeDifference > 0.1) { // 10% difference threshold
          consistency.issues.push('Inconsistent line count between overview and structural analysis')
          consistency.score -= 0.2
        }
      }
    }
    
    return consistency
  }

  private verifyAccuracy(synthesizedResult: any, originalContent: string): any {
    const accuracy = {
      score: 0.8, // Default accuracy assumption
      issues: [] as string[]
    }
    
    // Basic accuracy checks
    const detectedLanguage = synthesizedResult.overview?.fileStats?.language
    const actualLanguage = this.detectLanguage(originalContent)
    
    if (detectedLanguage !== actualLanguage) {
      accuracy.issues.push(`Language detection mismatch: detected ${detectedLanguage}, expected ${actualLanguage}`)
      accuracy.score -= 0.1
    }
    
    // Check if insights make sense for the file type
    const insights = synthesizedResult.combinedInsights || []
    if (insights.length === 0) {
      accuracy.issues.push('No insights generated - analysis may be incomplete')
      accuracy.score -= 0.2
    }
    
    return accuracy
  }

  private generateVerificationRecommendations(synthesizedResult: any): string[] {
    const recommendations: string[] = []
    
    const confidence = synthesizedResult.confidence
    
    if (confidence < 0.7) {
      recommendations.push('Low confidence in results - consider re-processing with different parameters')
    }
    
    const coverage = synthesizedResult.coverage
    if (coverage < 0.9) {
      recommendations.push('Incomplete coverage - some parts of the file may not have been analyzed')
    }
    
    const totalIssues = synthesizedResult.issueAggregation?.total || 0
    if (totalIssues > 50) {
      recommendations.push('High number of issues detected - prioritize addressing critical and high-severity items')
    }
    
    return recommendations
  }

  private calculateOverallConfidence(synthesizedResult: any, verificationResult: any): number {
    const synthesisConfidence = synthesizedResult.confidence || 0.5
    const completenessScore = verificationResult.completeness?.score || 0.5
    const consistencyScore = verificationResult.consistency?.score || 0.5
    const accuracyScore = verificationResult.accuracy?.score || 0.5
    
    // Weighted combination of confidence factors
    return (
      synthesisConfidence * 0.4 +
      completenessScore * 0.3 +
      consistencyScore * 0.2 +
      accuracyScore * 0.1
    )
  }

  private analyzeFileStructure(content: string): any {
    // Basic file structure analysis
    const lines = content.split('\n')
    const functions = content.match(/function\s+\w+|def\s+\w+/g) || []
    const classes = content.match(/class\s+\w+/g) || []
    const imports = content.match(/import\s+.*|from\s+.*import|#include/g) || []
    
    return {
      lineCount: lines.length,
      functions: functions.map(f => f.trim()),
      classes: classes.map(c => c.trim()),
      imports: imports.map(i => i.trim()),
      complexity: this.calculateBasicComplexity(content)
    }
  }

  private calculateBasicComplexity(content: string): number {
    // Simple complexity calculation
    const decisions = (content.match(/\b(if|else|while|for|switch|case|catch)\b/g) || []).length
    const functions = (content.match(/function\s+\w+|def\s+\w+/g) || []).length
    
    return decisions + functions
  }
}

// Virtual agent for chunk processing
class VirtualChunkAgent implements IAgent {
  readonly id: string
  readonly type = AgentType.FILE_PROCESSOR
  readonly reasoningModes = [
    ReasoningMode.ULTRATHINKING,
    ReasoningMode.ULTRAREASONING,
    ReasoningMode.HYBRID_REASONING,
    ReasoningMode.HYBRID_THINKING
  ]
  readonly capabilities = ['chunk-processing', 'code-analysis', 'pattern-recognition']
  
  private chunkIndex: number
  private log = Log.create({ service: `chunk-agent` })

  constructor(id: string, chunkIndex: number) {
    this.id = id
    this.chunkIndex = chunkIndex
  }

  async process(task: AgentTask): Promise<AgentResult> {
    const startTime = Date.now()
    
    try {
      const chunk = task.data as FileChunk
      
      this.log.debug("Processing chunk", { 
        chunkIndex: chunk.index,
        chunkSize: chunk.content.length,
        reasoningModes: task.reasoningModes
      })
      
      // Simulate sophisticated analysis of the chunk
      const analysis = await this.analyzeChunk(chunk, task.context)
      
      const processingTime = Date.now() - startTime
      
      return {
        agentId: this.id,
        agentType: this.type,
        taskId: task.id,
        reasoningMode: ReasoningMode.ULTRATHINKING, // Primary mode for this result
        result: analysis,
        confidence: this.calculateConfidence(analysis, chunk),
        processingTime
      }
      
    } catch (error) {
      this.log.error("Chunk processing failed", { error })
      
      return {
        agentId: this.id,
        agentType: this.type,
        taskId: task.id,
        reasoningMode: ReasoningMode.ULTRATHINKING,
        result: { error: 'Processing failed' },
        confidence: 0.1,
        processingTime: Date.now() - startTime,
        errors: [error instanceof Error ? error.message : String(error)]
      }
    }
  }

  private async analyzeChunk(chunk: FileChunk, context: any): Promise<any> {
    const content = chunk.content
    
    // Multi-faceted analysis of the chunk
    const analysis = {
      structure: this.analyzeChunkStructure(content),
      patterns: this.identifyPatterns(content),
      issues: this.detectIssues(content),
      insights: this.generateInsights(content, chunk),
      complexity: this.assessComplexity(content),
      quality: this.assessQuality(content)
    }
    
    return analysis
  }

  private analyzeChunkStructure(content: string): any {
    const lines = content.split('\n')
    const functions = content.match(/function\s+\w+|def\s+\w+|fn\s+\w+/g) || []
    const classes = content.match(/class\s+\w+|struct\s+\w+/g) || []
    const variables = content.match(/(?:let|const|var|int|string)\s+\w+/g) || []
    
    return {
      lineCount: lines.length,
      functions: functions.length,
      classes: classes.length,
      variables: variables.length,
      codeLines: lines.filter(line => line.trim() && !line.trim().startsWith('//')).length,
      commentLines: lines.filter(line => line.trim().startsWith('//')).length
    }
  }

  private identifyPatterns(content: string): any[] {
    const patterns = []
    
    // Common code patterns
    if (content.includes('.map(') || content.includes('.filter(')) {
      patterns.push({ type: 'functional_programming', confidence: 0.8 })
    }
    
    if (content.includes('async') && content.includes('await')) {
      patterns.push({ type: 'async_await', confidence: 0.9 })
    }
    
    if (content.includes('try') && content.includes('catch')) {
      patterns.push({ type: 'error_handling', confidence: 0.9 })
    }
    
    if (content.includes('class') && content.includes('extends')) {
      patterns.push({ type: 'inheritance', confidence: 0.8 })
    }
    
    return patterns
  }

  private detectIssues(content: string): any[] {
    const issues = []
    
    // Basic issue detection
    if (content.includes('console.log')) {
      issues.push({
        type: 'code_quality',
        severity: 'low',
        message: 'Debug console.log statements found'
      })
    }
    
    if (content.includes('// TODO') || content.includes('// FIXME')) {
      issues.push({
        type: 'maintenance',
        severity: 'medium',
        message: 'TODO/FIXME comments indicate incomplete work'
      })
    }
    
    if (content.includes('eval(')) {
      issues.push({
        type: 'security',
        severity: 'high',
        message: 'Use of eval() poses security risks'
      })
    }
    
    // Check for long lines
    const longLines = content.split('\n').filter(line => line.length > 120)
    if (longLines.length > 0) {
      issues.push({
        type: 'readability',
        severity: 'low',
        message: `${longLines.length} lines exceed 120 characters`
      })
    }
    
    return issues
  }

  private generateInsights(content: string, chunk: FileChunk): string[] {
    const insights = []
    
    const structure = this.analyzeChunkStructure(content)
    
    if (structure.functions > 5) {
      insights.push('High function density in this section')
    }
    
    if (structure.commentLines / structure.codeLines > 0.3) {
      insights.push('Well-documented code section')
    }
    
    if (structure.commentLines / structure.codeLines < 0.1) {
      insights.push('Limited documentation in this section')
    }
    
    if (chunk.index === 0) {
      insights.push('File beginning - likely contains imports and initial setup')
    }
    
    return insights
  }

  private assessComplexity(content: string): number {
    const decisions = (content.match(/\b(if|else|while|for|switch|case)\b/g) || []).length
    const nesting = this.calculateNestingDepth(content)
    const functions = (content.match(/function\s+\w+|def\s+\w+/g) || []).length
    
    return (decisions * 0.5 + nesting * 0.3 + functions * 0.2) / 10
  }

  private calculateNestingDepth(content: string): number {
    let maxDepth = 0
    let currentDepth = 0
    
    for (const char of content) {
      if (char === '{') {
        currentDepth++
        maxDepth = Math.max(maxDepth, currentDepth)
      } else if (char === '}') {
        currentDepth--
      }
    }
    
    return maxDepth
  }

  private assessQuality(content: string): number {
    let score = 1.0
    
    // Deduct for potential quality issues
    if (content.includes('console.log')) score -= 0.1
    if (content.includes('// TODO')) score -= 0.1
    if (content.includes('eval(')) score -= 0.3
    
    // Add for good practices
    if (content.includes('try') && content.includes('catch')) score += 0.1
    if (content.includes('const ')) score += 0.05
    
    return Math.max(0, Math.min(1, score))
  }

  private calculateConfidence(analysis: any, chunk: FileChunk): number {
    let confidence = 0.7 // Base confidence
    
    // Adjust based on analysis completeness
    if (analysis.structure) confidence += 0.1
    if (analysis.patterns && analysis.patterns.length > 0) confidence += 0.1
    if (analysis.insights && analysis.insights.length > 0) confidence += 0.1
    
    // Adjust based on chunk characteristics
    if (chunk.content.length < 500) confidence -= 0.1 // Very small chunks
    if (chunk.content.length > 10000) confidence -= 0.1 // Very large chunks
    
    return Math.max(0.1, Math.min(1, confidence))
  }

  async collaborate(agents: IAgent[], context: SharedContext): Promise<void> {
    // Simple collaboration - could be enhanced
    this.log.debug("Collaborating with other agents", { 
      agentCount: agents.length,
      sessionId: context.sessionId
    })
  }

  async isHealthy(): Promise<boolean> {
    return true // Virtual agents are always healthy
  }

  async dispose(): Promise<void> {
    this.log.debug("Disposing chunk agent", { chunkIndex: this.chunkIndex })
  }
}