Return code: 0
Duration: 91.9s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: defining function generate_asp_program()
  python_exec: defining function solve_car_scheduling()
  python_exec: defining function verify_solution()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the car assembly line scheduling task using Answer  
Set Programming (ASP) with the clingo Python API.                               

                              Solution Highlights:                              

 1 All Constraints Satisfied:                                                   
    • ✓ Each position has exactly one car; correct type counts (A:3, B:3, C:4,  
      D:2)                                                                      
    • ✓ Hierarchical options: Option 5 implies Option 1 for capacity constraints
    • ✓ Positional ban: No Option 4 (EV) at positions 1 or 12                   
    • ✓ Equipment cooldown: Option 2 (Custom Paint) has 3+ slot gaps            
    • ✓ Standard capacity: ≤2 effective Option 1 in any 4-window                
    • ✓ Conditional capacity: Option 3 capacity adjusts based on preceding EV   
 2 Valid Sequence Found:                                                        
    • Position 1: Type C (Custom Paint)                                         
    • Positions 2, 7, 10: Type A (Standard Sunroof)                             
    • Positions 3, 4, 9: Type B (Sport + EV)                                    
    • Positions 5, 8, 11: Type C (Custom Paint)                                 
    • Positions 6, 12: Type D (Panoramic Sunroof)                               
 3 Performance: Solution found in under 1 second with efficient ASP encoding.   

The code has been saved to 037_car_sequencing_hard_task_code.py and outputs the 
solution in the required JSON format.                                           

==================================================
📊 Execution Statistics
==================================================

🔧 Tool Usage:
  python_exec            3 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        94,070
  Output tokens:       4,728
  Total tokens:        98,798

⏱️  Execution time: 1m 30.7s
==================================================


=== STDERR ===
