Return code: 0
Duration: 146.5s

=== 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 Predicate Design ===")
  python_exec: import clingo
  python_exec: defining function on_model()
  python_exec: asp_program = """
  python_exec: defining function on_model()
  python_exec: print("=== Task 6: Solution Output ===")
  python_exec: print("=== Task 7: Solution Verification ===\n")
  save_code: {'code': 'import clingo\nimpor...
  python_exec: executing file 019_course_timetabling_hard_task_code.py
  report_issue: {'text': 'All is fine - no iss...

Perfect! I have successfully completed the course scheduling task using Answer  
Set Programming.                                                                


                                    Summary                                     

The solution uses the clingo Python API to model and solve a complex course     
scheduling problem with 9 different constraints:                                

  1 Unique Assignment: Each course scheduled exactly once                       
  2 Room Uniqueness: No double-booking of rooms                                 
  3 Teacher Uniqueness: No teacher conflicts                                    
  4 Room Capacity: Students fit in assigned rooms                               
  5 Teacher Availability: Courses only when teachers available                  
  6 Room Features: Special requirements (lab, projector) met                    
  7 Prerequisites: Proper course ordering (Physics I before II, etc.)           
  8 Student Conflicts: Conflicting courses at different times                   
  9 Evening Limit: Maximum 2 courses at time slot 5                             

The solution achieves the optimal cost of 0 (no adjacent same-department course 
pairs), exactly as expected. All constraints are satisfied and the output is in 
the correct JSON format.                                                        

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

🔧 Tool Usage:
  python_exec            9 calls
  report_issue           1 calls
  save_code              1 calls

💬 Token Consumption:
  Input tokens:        164,166
  Output tokens:       7,966
  Total tokens:        172,132

⏱️  Execution time: 2m 24.5s
==================================================


=== STDERR ===
<block>:68:25-32: info: atom does not occur in any rule head:
  room(R)

