Return code: 0
Duration: 107.1s

=== 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 1: Problem Analysis ===")
  python_exec: defining function generate_asp_program()
  python_exec: defining function solve_graph_coloring()
  python_exec: print("=== Task 6: Solution Verification ===")
  save_code: {'code': 'import clingo\nimpor...
  python_exec: executing file 002_weighted_graph_coloring_hard_task_code.py
  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 API. Here's what was accomplished:            

                               Solution Overview                                

 • All 36 vertices are properly colored using exactly 5 colors (1-5)            
 • Weighted cost: 626 (well below the required bound of 850)                    
 • All constraints satisfied:                                                   
    • No adjacent vertices share the same color                                 
    • All 5 colors are used (enforced by the K5 clique)                         
    • Cost constraint met: 626 ≤ 850                                            

                           Key Implementation Details                           

 1 Modeled the complete graph structure: K5 core clique plus three clusters (A, 
   B, C) with all their internal edges and inter-cluster connections            
 2 Used constraint-based approach: Instead of optimization, used a hard         
   constraint on the cost bound for faster solving                              
 3 Symmetric edges: Automatically generated bidirectional edges for all         
   connections                                                                  
 4 Efficient ASP encoding:                                                      
    • Choice rule for color assignment                                          
    • Integrity constraints for adjacency conflicts                             
    • Aggregate constraint for weighted cost                                    

The solution executes quickly (under 1 second) and produces valid output in the 
required JSON format.                                                           

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

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

💬 Token Consumption:
  Input tokens:        139,364
  Output tokens:       5,933
  Total tokens:        145,297

⏱️  Execution time: 1m 45.9s
==================================================


=== STDERR ===
