mirror of
https://github.com/thecyberlearn/quantum-ai-v2.git
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7120bfdf98
- Create unified command that calls all individual agent creation commands - Used by Railway's startCommand to populate production database - Idempotent design - safe to run multiple times - Shows detailed summary and environment-specific guidance - Fixes Railway deployment issue where agents marketplace was empty 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
106 lines
4.4 KiB
Python
106 lines
4.4 KiB
Python
from django.core.management.base import BaseCommand
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from django.core.management import call_command
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import os
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class Command(BaseCommand):
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help = 'Populate all agents in the database - calls all individual agent creation commands'
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def add_arguments(self, parser):
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parser.add_argument(
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'--force',
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action='store_true',
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help='Force recreation of agents even if they exist',
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)
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parser.add_argument(
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'--skip-existing',
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action='store_true',
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help='Skip agents that already exist (default behavior)',
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)
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def handle(self, *args, **options):
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self.stdout.write("🤖 Starting agent population process...")
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# List of all agent creation commands
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agent_commands = [
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'create_social_ads_agent',
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'create_job_posting_agent',
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'create_pdf_summarizer_agent',
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'create_five_whys_agent',
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'create_cybersec_career_agent',
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]
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success_count = 0
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error_count = 0
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for command_name in agent_commands:
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try:
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self.stdout.write(f"\n📦 Running {command_name}...")
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# Pass through options to individual commands
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command_options = {}
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if options.get('force'):
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command_options['force'] = True
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# Call the individual agent creation command
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call_command(command_name, **command_options)
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success_count += 1
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self.stdout.write(f"✅ {command_name} completed successfully")
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except Exception as e:
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error_count += 1
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self.stdout.write(
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self.style.ERROR(f"❌ {command_name} failed: {str(e)}")
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)
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# Continue with other commands even if one fails
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continue
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self.stdout.write(f"\n🎯 Agent population summary:")
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self.stdout.write(f"✅ Successful: {success_count}")
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self.stdout.write(f"❌ Failed: {error_count}")
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self.stdout.write(f"📊 Total commands: {len(agent_commands)}")
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if error_count == 0:
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self.stdout.write(self.style.SUCCESS("\n🎉 All agents populated successfully!"))
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else:
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self.stdout.write(self.style.WARNING(f"\n⚠️ {error_count} commands failed. Check logs above."))
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# Show final agent count
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try:
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from agents.models import Agent, AgentCategory
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total_categories = AgentCategory.objects.count()
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total_agents = Agent.objects.count()
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active_agents = Agent.objects.filter(is_active=True).count()
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self.stdout.write(f"\n📈 Database Summary:")
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self.stdout.write(f"🏷️ Categories: {total_categories}")
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self.stdout.write(f"🤖 Total Agents: {total_agents}")
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self.stdout.write(f"⚡ Active Agents: {active_agents}")
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if active_agents > 0:
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self.stdout.write(f"\n🔗 Agents by category:")
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categories = AgentCategory.objects.all()
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for category in categories:
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agent_count = Agent.objects.filter(category=category, is_active=True).count()
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if agent_count > 0:
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self.stdout.write(f" {category.icon} {category.name}: {agent_count} agents")
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except Exception as e:
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self.stdout.write(f"⚠️ Could not generate database summary: {str(e)}")
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# Environment-specific notes
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deployment_env = os.environ.get('DEPLOYMENT_ENVIRONMENT', 'development')
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self.stdout.write(f"\n🌍 Environment: {deployment_env}")
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if deployment_env == 'production':
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self.stdout.write("💡 Production notes:")
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self.stdout.write(" - Webhook URLs should point to production N8N instance")
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self.stdout.write(" - Verify agent pricing and configurations")
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self.stdout.write(" - Test agent execution after deployment")
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else:
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self.stdout.write("💡 Development notes:")
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self.stdout.write(" - Webhook URLs point to localhost:5678")
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self.stdout.write(" - Use ngrok for testing webhooks externally") |