Return code: 0
Duration: 113.1s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: print("Task planning complete. Starting implementa...
  python_exec: defining function generate_facts()
  python_exec: asp_program = facts_str + """
  python_exec: defining function on_model()
  python_exec: if solution_data:
  python_exec: print("\n" + "="*60)
  python_exec: defining function generate_facts()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the constrained maximum clique problem using Answer 
Set Programming (ASP) with the clingo Python API.                               

                               Solution Overview:                               

Found Clique: Vertices [2, 5, 8, 11, 14, 17] with size 6 (matching the expected 
optimal)                                                                        

Constraint Verification:                                                        

 1 ✓ Clique Property: All 15 pairs of vertices are connected by edges           
 2 ✓ Type Diversity: 2 alpha, 2 beta, 2 gamma vertices (≤2 per type)            
 3 ✓ Weight Limit: Total weight = 99 ≤ 100                                      

Key Implementation Details:                                                     

 • Used choice rules to select vertices for the clique                          
 • Enforced clique property by forbidding unconnected pairs                     
 • Limited type counts using #count aggregates                                  
 • Constrained total weight using #sum aggregate                                
 • Used constraint-based optimization (:- clique_size(N), N < 6.) instead of    
   #maximize for efficiency, as suggested in the guidelines                     
 • Solution completes in well under 10 seconds                                  

The final code has been saved and produces the correct JSON output with all     
required fields.                                                                

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

🔧 Tool Usage:
  python_exec            7 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        158,618
  Output tokens:       6,134
  Total tokens:        164,752

⏱️  Execution time: 1m 52.2s
==================================================


=== STDERR ===
2025-10-11 19:00:29,137 - coder.kernel - WARNING - Existing kernel is dead, will restart
