AirCoding/packages/workers/src/roles/ExecutorRole.ts

/**
 * ExecutorRole - Implementation worker
 * Implements DD §8.4. Executes tasks using LLM→tool→LLM loop.
 *
 * @module packages/workers/src/roles/ExecutorRole
 */

import { WorkerRuntime } from '../WorkerRuntime.js'

export interface ExecutorResult {
  status: 'completed' | 'failed' | 'blocked'
  changes?: Array<{ file: string; type: 'create' | 'edit' | 'delete' }>
  verification?: { passed: boolean; output: string }
  error?: string
  evidence_refs?: string[]
}

export class ExecutorRole {
  private runtime: WorkerRuntime
  private max_turns: number = 10

  constructor(runtime: WorkerRuntime) {
    this.runtime = runtime
  }

  async run(task_spec: { id: string; title: string; description: string; acceptance_criteria: string[] }): Promise<ExecutorResult> {
    this.runtime.emit('task.attempt.started', { task_id: task_spec.id })

    try {
      const messages: Array<{ role: string; content: unknown }> = [
        {
          role: 'system',
          content: `You are an AI coding executor. Complete the task by reading files, writing code, and running verification.
When you must read or write a file, output a JSON tool_call block.
When you are done, output "TASK_COMPLETE" followed by a summary.

Available tools: fs.read(path), fs.write(path, content), fs.edit(path, old_str, new_str), fs.list(dir), git.status(), shell.run(command)`
        },
        {
          role: 'user',
          content: `Task: ${task_spec.title}\n\nDescription: ${task_spec.description}\n\nAcceptance criteria:\n${task_spec.acceptance_criteria.map((c, i) => `${i + 1}. ${c}`).join('\n')}`
        }
      ]

      let turn = 0
      const changes: Array<{ file: string; type: 'create' | 'edit' | 'delete' }> = []
      let verification: { passed: boolean; output: string } | undefined

      while (turn < this.max_turns) {
        turn++
        this.runtime.heartbeat()

        // Call LLM
        const llm_response = await this.runtime.call_llm({
          messages,
          max_tokens: 4096,
          temperature: 0.3
        })

        const response_text = llm_response.content || ''

        // Check for completion signal
        if (response_text.includes('TASK_COMPLETE')) {
          const summary = response_text.split('TASK_COMPLETE')[1]?.trim() || 'Task completed'
          await this.runtime.checkpoint('task_completed', { task_id: task_spec.id, summary })
          return {
            status: 'completed',
            changes,
            verification,
            evidence_refs: []
          }
        }

        // Parse tool calls from LLM response
        const tool_calls = this.parse_tool_calls(response_text)

        if (tool_calls.length === 0) {
          // No tool calls - LLM is just talking, add to messages and continue
          messages.push({ role: 'assistant', content: response_text })
          messages.push({ role: 'user', content: 'Continue. What actions will you take? Use tool calls (JSON format) to read/write files.' })
          continue
        }

        // Execute each tool call
        for (const tc of tool_calls) {
          try {
            const result = await this.runtime.call_tool(tc.name, tc.args)
            const tool_output = result.type === 'error'
              ? `Error: ${JSON.stringify(result.content)}`
              : JSON.stringify(result.content)

            // Track file changes
            if (tc.name === 'fs.write' && tc.args.path) {
              changes.push({ file: tc.args.path as string, type: 'create' })
            } else if (tc.name === 'fs.edit' && tc.args.path) {
              changes.push({ file: tc.args.path as string, type: 'edit' })
            }

            // Add assistant tool call + tool result to messages
            messages.push({
              role: 'assistant',
              content: `Tool call: ${tc.name}(${JSON.stringify(tc.args)})`
            })
            messages.push({
              role: 'user',
              content: `Tool result: ${tool_output}`
            })
          } catch (e: any) {
            messages.push({
              role: 'user',
              content: `Tool error: ${e.message}`
            })
          }
        }

        // After tool execution, ask LLM to verify and continue
        messages.push({
          role: 'user',
          content: 'Tools executed. Review the results. If the task is complete, respond with TASK_COMPLETE. Otherwise, continue with more tool calls.'
        })
      }

      // Max turns reached
      return {
        status: 'blocked',
        error: `Task exceeded ${this.max_turns} turns without completion`,
        changes,
        evidence_refs: []
      }

    } catch (error) {
      this.runtime.emit('task.blocked', {
        task_id: task_spec.id,
        error: error instanceof Error ? error.message : String(error)
      })

      return {
        status: 'blocked',
        error: error instanceof Error ? error.message : String(error)
      }
    }
  }

  /**
   * Parse tool calls from LLM response text.
   * Supports JSON tool_call format and function-call markdown blocks.
   */
  private parse_tool_calls(text: string): Array<{ name: string; args: Record<string, unknown> }> {
    const calls: Array<{ name: string; args: Record<string, unknown> }> = []

    // Pattern 1: JSON tool_call blocks
    const json_pattern = /\{[\s\n]*"tool_call"[\s\n]*:[\s\n]*\{[^}]+\}[\s\n]*\}/g
    for (const match of text.match(json_pattern) || []) {
      try {
        const parsed = JSON.parse(match)
        if (parsed.tool_call) {
          calls.push({ name: parsed.tool_call.name, args: parsed.tool_call.args || {} })
        }
      } catch { /* skip invalid JSON */ }
    }

    // Pattern 2: function(name, args) format
    const func_pattern = /(\w+)\.(\w+)\(([^)]*)\)/g
    for (const match of text.matchAll(func_pattern)) {
      const [_, namespace, func, args_str] = match
      const name = `${namespace}.${func}`
      const args: Record<string, unknown> = {}
      if (args_str) {
        // Simple key:value parsing
        const pairs = args_str.match(/(\w+)\s*:\s*("[^"]*"|'[^']*'|[^,]+)/g) || []
        for (const pair of pairs) {
          const [key, ...value_parts] = pair.split(':')
          const value = value_parts.join(':').trim().replace(/^["']|["']$/g, '')
          args[key.trim()] = value
        }
      }
      calls.push({ name, args })
    }

    // Pattern 3: ```tool_call JSON blocks
    const block_pattern = /```(?:json)?\s*\n?\{[\s\n]*"tool"[\s\n]*:[\s\n]*"[^"]+"[\s\n]*,[\s\n]*"args"[\s\n]*:[\s\n]*\{[^}]*\}[\s\n]*\}[\s\n]*```/g
    for (const match of text.match(block_pattern) || []) {
      try {
        const json_str = match.replace(/```(?:json)?\s*\n?/g, '').replace(/```/g, '').trim()
        const parsed = JSON.parse(json_str)
        if (parsed.tool) {
          calls.push({ name: parsed.tool, args: parsed.args || {} })
        }
      } catch { /* skip */ }
    }

    return calls
  }
}