Return code: 0
Duration: 77.5s

=== 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: print("=== Task 2: ASP Model Design ===")
  python_exec: defining function solve_exam_scheduling()
  python_exec: print("=== Verification ===")
  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 Approach:                               

 1 Modeled the problem with ASP predicates for exams, students, enrollments,    
   time slots, and rooms                                                        
 2 Used a choice rule to assign each exam to exactly one (time_slot, room) pair 
 3 Enforced constraints:                                                        
    • No student can have two exams at the same time slot                       
    • Room capacity cannot be exceeded                                          
 4 Extracted and formatted the solution as JSON                                 

                                    Result:                                     

The solver found a valid schedule that:                                         

 • ✅ Schedules all 6 exams across 3 time slots and 2 rooms                     
 • ✅ Resolves all student conflicts (each student's exams are at different     
   times)                                                                       
 • ✅ Respects room capacities (all exams have ≤3 students, rooms have capacity 
   3)                                                                           
 • ✅ Outputs proper JSON format with schedule details and room utilization     

The solution is efficient and completes quickly within the time limit.          

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

🔧 Tool Usage:
  python_exec            4 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        141,144
  Output tokens:       3,670
  Total tokens:        144,814

⏱️  Execution time: 1m 15.7s
==================================================


=== STDERR ===
