Return code: 0
Duration: 87.7s

=== 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 create_asp_program()
  python_exec: defining function solve_exam_scheduling()
  python_exec: defining function verify_solution()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I've successfully completed the exam scheduling task using Answer Set           
Programming (ASP) with the clingo Python API.                                   

Solution Overview:                                                              

The ASP model schedules 8 exams for 6 students across 4 time slots and 3        
specialized rooms while satisfying all constraints:                             

 1 Complete Scheduling: Each exam assigned to exactly one time slot and room    
   (enforced by choice rule)                                                    
 2 Student Conflicts: No student has two exams at the same time                 
 3 Room Conflicts: No room hosts multiple exams simultaneously                  
 4 Room Type Matching: Lab exams (E7, E8) scheduled in lab room (R3), classroom 
   exams in classroom rooms (R1, R2)                                            
 5 Capacity Limits: All exams respect the 2-student capacity of their assigned  
   rooms                                                                        

Verification Results:                                                           

 • ✓ All 8 exams scheduled                                                      
 • ✓ No student conflicts                                                       
 • ✓ No room conflicts                                                          
 • ✓ Room types match requirements                                              
 • ✓ Room capacities respected                                                  

The solution was found efficiently and outputs the required JSON format with    
status "SATISFIABLE" and the complete schedule.                                 

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

🔧 Tool Usage:
  python_exec            3 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        126,588
  Output tokens:       4,999
  Total tokens:        131,587

⏱️  Execution time: 1m 26.6s
==================================================


=== STDERR ===
