Return code: 0
Duration: 90.0s

=== 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_graph_facts()
  python_exec: defining function build_asp_program()
  python_exec: defining function solve_hamiltonian_path()
  python_exec: optimal_path = solutions[0]['path']
  python_exec: output = {
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the Hamiltonian path problem using Answer Set       
Programming with clingo. Here's what was accomplished:                          

                               Solution Approach:                               

 1 Graph Generation: Parsed the problem specification to generate 240 edges with
   weights (1-6) and identified 48 forbidden edges                              
 2 ASP Model: Created a model that:                                             
    • Uses choice rules to select path edges                                    
    • Enforces exactly one incoming/outgoing edge per vertex (except start/end) 
    • Ensures reachability from start vertex to guarantee a connected path      
    • Filters out forbidden edges during fact generation                        
    • Uses a constraint C > 99 instead of #minimize for efficiency (as suggested
      in the guidelines)                                                        
 3 Result: Found 1 optimal Hamiltonian path with cost 99 (matching the expected 
   optimal value)                                                               

                               The Optimal Path:                                

The solution is the simple sequential path: 0→1→2→3→...→98→99, using all 99     
chain edges (each with weight 1), for a total cost of 99.                       

The code has been saved and produces the required JSON output format with all   
optimal paths, their count, existence flag, and minimum cost.                   

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

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

💬 Token Consumption:
  Input tokens:        149,807
  Output tokens:       4,852
  Total tokens:        154,659

⏱️  Execution time: 1m 28.7s
==================================================


=== STDERR ===
