Return code: 0
Duration: 110.0s

=== STDOUT ===
🚀 Running coder
📦 Dynamic packages: clingo
🤖 Creating agent with model: anthropic/claude-sonnet-4.5
🤖 Using model: anthropic/claude-sonnet-4.5
  python_exec: print("Task 1: Problem Analysis")
  python_exec: print("Task 2: Predicate Design")
  python_exec: import clingo
  python_exec: defining function build_asp_program()
  python_exec: defining function solve_scheduling_problem()
  python_exec: print("Task 6: Solution Verification")
  python_exec: print("Task 7: Final Output")
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...


                                    Summary                                     

I have successfully completed the meeting scheduling task using Answer Set      
Programming (ASP) with the clingo Python API.                                   

                               Solution Approach:                               

 1 Modeled the problem with clear ASP predicates representing meetings, rooms,  
   days, time slots, people, equipment, and attendance relationships            
 2 Implemented key constraints:                                                 
    • Each meeting assigned to exactly one (day, slot, room) via choice rule    
    • Room occupancy constraint preventing double-booking                       
    • Person availability constraint preventing scheduling conflicts            
    • Equipment requirement constraint ensuring rooms have necessary equipment  
 3 Successfully found a valid schedule that assigns all 20 meetings across 4    
   rooms and 5 days, satisfying all constraints                                 
 4 Output format matches the required JSON structure with schedule array and    
   feasible flag                                                                

The solution executes quickly (under 1 second) and produces a valid,            
constraint-satisfying schedule.                                                 

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

🔧 Tool Usage:
  python_exec            7 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        126,578
  Output tokens:       6,117
  Total tokens:        132,695

⏱️  Execution time: 1m 48.9s
==================================================


=== STDERR ===
