Return code: 0
Duration: 151.2s

=== 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: import clingo
  python_exec: defining function on_model()
  python_exec: print("=== Task 6: Formatting Output ===")
  python_exec: print("=== Task 7: Verification ===")
  python_exec: defining function on_model()
  save_code: {'code': 'import clingo\nimpor...
  report_issue: {'text': 'All is fine - no iss...

Perfect! I have successfully completed the ASP task for optimal drug regimen    
design. Here's a summary:                                                       


                               Solution Overview                                

The ASP program finds the optimal drug regimen with a total cost of 220         
(matching the expected minimum), prescribing:                                   

 1 cardio_ease (cost: 50) - treats hypertension                                 
 2 metformax (cost: 40) - treats diabetes                                       
 3 anxio_calm (cost: 70) - treats anxiety                                       
 4 pain_off (cost: 60) - treats pain                                            


                                  Key Features                                  

✅ All constraints satisfied:                                                   

 • Drug limit: 4 drugs (max 4)                                                  
 • Budget: 220 (max 250)                                                        
 • Toxicity: 90 (max 100)                                                       
 • All 4 patient conditions treated                                             
 • No contraindications violated                                                
 • No severe interactions present                                               

✅ Safety analysis:                                                             

 • Avoided renal_guard (contraindicated with renal_failure)                     
 • Avoided glucopain (contraindicated with G6PD_deficiency)                     
 • Avoided hydro_stress + metformax (severe interaction when patient has        
   diabetes)                                                                    
 • Selected pain_off over pain_plus to avoid moderate interaction with metformax

✅ Optimization:                                                                

 • Uses #minimize to find the lowest-cost solution                              
 • Correctly identifies 220 as the minimum achievable cost                      

The solution is saved to 062_drug_interaction_hard_task_code.py and outputs the 
required JSON format.                                                           

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

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

💬 Token Consumption:
  Input tokens:        145,663
  Output tokens:       9,384
  Total tokens:        155,047

⏱️  Execution time: 2m 27.6s
==================================================


=== STDERR ===
