Return code: 0
Duration: 133.8s

=== 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: asp_rules = """
  python_exec: defining function solve_stable_matching()
  python_exec: print("Verification:")
  python_exec: defining function generate_asp_program()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'Task completed succe...


                         Task Completed Successfully! ✓                         

I've successfully solved the stable matching problem using Answer Set           
Programming with the clingo Python API. Here's what was accomplished:           

                               Solution Overview:                               

Problem: Find all stable matchings between 40 residents and 20 hospitals with   
capacity constraints and preference rankings.                                   

Approach:                                                                       

 1 Modeled the problem using ASP predicates for residents, hospitals,           
   capacities, and preferences                                                  
 2 Implemented choice rules to generate candidate matchings                     
 3 Encoded constraints:                                                         
    • Capacity limits (using #count aggregates)                                 
    • Mutual acceptability (only match if both parties find each other          
      acceptable)                                                               
    • Stability (no blocking pairs where both parties would prefer each other)  
 4 Solved for all models to enumerate all stable matchings                      

Results:                                                                        

 • ✓ Found exactly 81 stable matchings (as expected: 3×3×3×3 from independent   
   blocks)                                                                      
 • ✓ All 40 residents matched in each solution                                  
 • ✓ Hospital capacities respected                                              
 • ✓ No blocking pairs exist                                                    
 • ✓ Execution time well under 10 seconds                                       
 • ✓ Output formatted as required JSON                                          

The solution has been saved to 006_hospital_matching_hard_task_code.py and is   
ready to use!                                                                   

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

🔧 Tool Usage:
  python_exec            5 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        144,426
  Output tokens:       9,002
  Total tokens:        153,428

⏱️  Execution time: 2m 12.2s
==================================================


=== STDERR ===
