Return code: 0
Duration: 87.4s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: import clingo
  python_exec: defining function on_model()
  python_exec: defining function on_model()
  python_exec: defining function on_model()
  python_exec: defining function has_cycle()
  python_exec: print(json.dumps(solution, indent=2))
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': "All is fine - no iss...


                                    Summary                                     

I've successfully solved the feedback vertex set problem using Answer Set       
Programming with clingo.                                                        

Solution Found:                                                                 

 • Feedback set: [1, 4]                                                         
 • Size: 2 (matches expected optimal)                                           
 • Remaining vertices: [2, 3, 5, 6]                                             

How it works:                                                                   

 1 The ASP model uses a choice rule to select vertices for removal              
 2 Defines "active edges" as edges where neither endpoint is removed            
 3 Computes reachability in the remaining graph                                 
 4 Constrains that no vertex can reach itself (preventing cycles)               
 5 Minimizes the number of removed vertices                                     

Verification: After removing vertices 1 and 4, the remaining edges are: (2→5),  
(3→6), (5→3), (5→6). This forms a DAG (directed acyclic graph) with no cycles,  
confirming the solution is valid.                                               

The final code has been saved and outputs the solution in the required JSON     
format.                                                                         

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

🔧 Tool Usage:
  python_exec            6 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        185,823
  Output tokens:       4,274
  Total tokens:        190,097

⏱️  Execution time: 1m 26.0s
==================================================


=== STDERR ===
#models not 0: optimality of last model not guaranteed.
2025-10-12 17:46:05,455 - coder.kernel - WARNING - Existing kernel is dead, will restart
