Return code: 0
Duration: 109.9s

=== 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: asp_program = facts + """
  python_exec: defining function on_model()
  python_exec: if solution_data:
  python_exec: print("=== ADJACENCY VERIFICATION ===")
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the weighted graph coloring task using Answer Set   
Programming (ASP) with the clingo Python API. Here's what was accomplished:     

                               Solution Results:                                

 • Number of colors used: 5 (all colors required)                               
 • Weighted cost: 667 (well below the 850 limit)                                
 • All constraints satisfied:                                                   
    • ✓ All 36 vertices colored                                                 
    • ✓ All 5 colors used (enforced by K5 clique)                               
    • ✓ No adjacency violations (verified all 86 edges)                         
    • ✓ Weighted cost 667 ≤ 850                                                 

                               ASP Model Design:                                

The solution uses a clean ASP encoding with:                                    

 1 Facts: Vertices, colors, weights, and edges for the complex graph structure  
   (K5 core + 3 clusters)                                                       
 2 Choice rule: Each vertex gets exactly one color                              
 3 Constraints:                                                                 
    • Adjacent vertices must have different colors                              
    • Weighted cost bound enforcement                                           
    • All 5 colors must be used                                                 
 4 Aggregates: Efficient cost calculation using #sum                            

The solver found a valid solution quickly (under 1 second), demonstrating the   
efficiency of ASP for this type of constraint satisfaction problem.             

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

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

💬 Token Consumption:
  Input tokens:        181,125
  Output tokens:       6,162
  Total tokens:        187,287

⏱️  Execution time: 1m 48.4s
==================================================


=== STDERR ===
