# [LK] agent_executor.py - Feedback-Enabled Orchestrator
import subprocess

def execute_command(brain_tag, task_content):
    workflows = {
        "02_Creative_Assets": "python C:/Users/leonk/Documents/AI_Projects/ai_workspace/scripts/content_pipeline_generator.py",
        "03_Knowledge_Base": "python C:/Users/leonk/Documents/AI_Projects/ai_workspace/scripts/research_archiver.py"
    }

    if brain_tag in workflows:
        result = subprocess.run(workflows[brain_tag].split(), capture_output=True, text=True)
        
        if result.returncode == 0:
            return f"SUCCESS: Workflow {brain_tag} completed. Output: {result.stdout[:50]}..."
        else:
            return f"FAILURE: Workflow {brain_tag} crashed. Error: {result.stderr[:50]}"
    
    return f"LOGGED: Task sent to {brain_tag}"